Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ...

Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

These data are a part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The work was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate species ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps Department of Interior and other resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the elkhorn coral, Acropora palmata, and the symmetrical brain coral, Pseudodiploria strigosa, grown at three sites at Buck Island Reef National Monument in St. ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This GIS layer provides the location where samples from Pellegrino and Hubbard were summarized to provide detailed analysis of 35 common species found in Long Island Sound benthic communities

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This GIS layer provides the location where samples were taken in a survey conducted by D. Franz (1976)

This GIS layer provides the location where samples were taken in a survey conducted by P.L. McCall (1975)

This data layer provides the location where samples were taken in a survey conducted by P. Pellegrino and W. Hubbard (1983)

This GIS layer provides the location where samples were taken in a survey conducted by R.N. Reid, et al (1979)

This GIS layer provides the location where samples were taken in a survey conducted by H.L. Sanders (1956)

This GIS layer provides detailed information from Pellegrino and Hubbard (1983). It shows the sample locations and provides a summary of the total number of species found at each station (species_richness).

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps Department of Interior and other resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral physiology of the elkhorn coral, Acropora palmata, grown at five sites along the Florida outer reef tract including in Biscayne National Park, the Florida Keys National Marine Sanctuary, and Dry Tortugas National Park, ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

The files in this data release (Kellogg and others, 2023) are those referenced in the journal article by Evans and others (2023) entitled “Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD).” They contain an amplicon sequence variant (ASV) table and the raw 16S rRNA gene amplicon files from fifty-six 0.22-micrometer (µm) pore size filters, as well as six reagent blanks, three mock communities, and a 0.22-µm-filtered ultraviolet (UV)-treated ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of an effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000-scale) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The data collected in this study will aid research on the ecology of fish and invertebrate species that inhabit the region. On August 22 and 23, 2017, the U.S. Geological ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ...

The files in this data release (Kellogg and Voelschow, 2023) contain normalized microarray probe intensity values from GeoChip 5.0S microarrays referenced in the journal article entitled “Functional gene composition and metabolic potential of deep-sea coral-associated microbial communities” by Pratte and others (2023). The GeoChip 5.0S microarrays, provided by Glomics Inc., contain 57,498 oligonucleotide probes that target 383 microbial (archaeal, bacterial, and fungal) genes and cover 151,797 coding ...

The files provided in this data release are the DNA sequence files referenced in Goldsmith and others (2019), which represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of Astrangia poculata microbiomes completed using Sanger dideoxy sequencing. The coral samples were collected from Narragansett Bay at Fort Wetherill State Park, Jamestown, Rhode Island in 2015 and 2016 (Sharp and others, 2017). Sequences were obtained by first extracting DNA from a fragment of each A. poculata sample ...

The files provided in this U.S. Geological Survey (USGS) data release (Kellogg and others, 2021) include an amplicon sequence variant (ASV) table and the raw 16S rRNA gene amplicon files from six microbial communities (Mcav17, Mcav18, McH-101, McH-103, McD-57, and McD-58) derived from mesocosms consisting of filtered seawater in which either healthy or diseased (stony coral tissue loss disease) fragments of Montastraea cavernosa had been incubated, as well as sequence files of a mock community and ...

The files in this data release are the raw deoxyribonucleic acid (DNA) sequence files referenced in the submitted journal article by Christina A. Kellogg, Dawn B. Goldsmith and Michael A. Gray entitled "Biogeographic comparison of Lophelia-associated bacterial communities in the western Atlantic reveals conserved core microbiome". They represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of the coral’s microbiomes completed using Roche 454 pyrosequencing with Titanium series reagents. ...

The files in this data release are the raw DNA sequence files referenced in the journal article by Goldsmith and others (2018) entitled "Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype". They represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of the corals’ microbiomes (Primnoa spp.) completed using Roche 454 pyrosequencing with Titanium series reagents. The 16S rRNA gene ...

The files in this this U.S. Geological Survey (USGS) data release (Kellogg and others, 2021) are the raw 16S ribosomal ribonucleic acid (rRNA) gene amplicon deoxyribonucleic acid (DNA) sequence files from 90 samples of tropical and cold-water corals, as well as sequence files from a mock community and extraction blanks for the kits used for DNA extraction. The mock community was sequenced in order to assess any biases in the sequencing technology, while extraction blanks were sequenced in order to identify ...

In 2009, three unique colonies of the cold-water coral Lophelia pertusa were sampled in the western Atlantic Ocean to examine their microbial metagenomes. Nine additional samples were collected from three sites (Viosca Knoll 826, Viosca Knoll 906, and West Florida Slope) around the Gulf of Mexico in 2009 and 2010. Previous studies have examined the bacterial associates of this coral, but to date, no cold-water coral metagenomes have been published. This analysis characterized and identified microbial ...

The USGS Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates for Orbicella sp. coral colonies grown at five sites on the Florida Keys reef tract from 2013 to 2015, survey data for census-based carbonate budgeting at Hen and Chickens Reef (Islamorada, Florida) collected in 2017, and time-series photographs taken of permanent markers ...

The USGS Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the elkhorn coral, Acropora palmata, grown at five sites on the Florida Keys reef tract from Spring 2018 to Autumn 2019. The data will be used to inform resource managers of the capacity for restoration and growth of this ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the mustard hill coral, Porites astreoides, grown at four sites on the Florida Keys reef tract from Spring 2015 to Spring 2017. The data will be used to inform resource managers on the spatial and ...

This data set includes: (1) allele sizes of 11 previously published microsatellites (Kenkel and others, 2013; Shearer and Coffroth, 2004) for 39 individuals of mustard hill coral, Porites astreoides (mustard hill coralP. astreoides) collected in the Spring of 2017 from four locations in the Florida Keys Reef Tract (FKRT): Fowey Rocks, Crocker Reef, Sombrero Reef and Pulaski Shoal and (2) the deoxyribonucleic acid (DNA) concentration of the extracted DNA prior to polymerase chain reaction (PCR) reactions for ...

The files provided in this U.S. Geological Survey (USGS) data release (Kellogg and Voelschow, 2021) are the raw DNA sequence files referenced in the associated journal article (Kellogg and Pratte, 2021) entitled, “Unexpected diversity of Endozoicomonas in deep-sea corals.”. This dataset, PRJNA699458_16S-V3V4_raw_data_1.zip, represents the 16S rRNA gene amplicon surveys of 28 samples of deep-sea corals, including Acanthogorgia aspera (n=5), Acanthogorgia spissa (n=4), Desmophyllum dianthus (n=7), and ...

The U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration's (NOAA) National Marine Sanctuary Program, conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region from 1994 to 2004. The mapped area is approximately 3,700 square km (1,100 square nm) in size and was subdivided into 18 quadrangles. Several series of sea floor maps of the region based on multibeam sonar surveys have been published. In addition, 2,628 seabed ...

These data are a part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The work was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate species ...

The files included in this data release are the raw and processed deoxyribonucleic acid (DNA) sequence files referenced in the journal article by Lawler and others (2016) entitled “Coral-Associated Bacterial Diversity is Conserved Across Two Deep-Sea Anthothela Species”. They represent a 16S rRNA gene amplicon survey of cold-water corals (Anthothela spp.) microbiomes completed using Roche 454 pyrosequencing with titanium reagents. The samples used in this study were collected from cold-water corals ...

Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude ...

The prevalence of antibiotic resistance genes in microbial communities from sewage wastewater streams and from offshore marine sediments in the vicinity of sewage wastewater outfalls in Southeast Florida was investigated from June 2018 to March 2019. Sediment and wastewater samples were analyzed for 15 different antibiotic resistant gene targets via polymerase chain reaction (PCR) presence/absence assays in Southeast Florida coral reef environments. Data collected from five sites (Broward North Wastewater ...

Crocker Reef was the site of an integrated reefscape characterization effort focused on calcification and related biogeochemical processes as part of the USGS Coral Reef Ecosystem Study (CREST) project. This effort included two intensive seasonal sampling trips to capture summer (July 8 to 17, 2014) and winter (January 29 to February 5, 2015) conditions. This data release represents water column microbial and environmental data collected for use as metadata in future publications examining reef metabolic ...

Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude ...

Observations of elevated barium-to-calcium ratio (Ba/Ca) in Globorotalia truncatulinoides have been attributed to contaminant phases, deep calcification depth and diagenetic processes. U.S. Geological Survey (USGS) scientists and their collaborators investigated intra- and inter-test Ba/Ca variability in the non-spinose planktic foraminifer, G. truncatulinoides, from a sediment trap time series (2009-2017) in the northern Gulf of Mexico (generally 27.5°N and 90.3°W) to gain insights into the environmental ...

In July of 2016, Florida Institute of Technology researchers, in collaboration with the U.S. Geological Survey (USGS), conducted reef-census surveys at 54 sites around Buck Island Reef National Monument, St. Croix, U.S. Virgin Islands. The sites are divided across two reef sectors (North and South) and three reef habitats (fore reef, reef crest, and back reef). The surveys provided data on the percent coverage of corals and other benthic taxa, and abundance of bioeroding parrotfishes and urchins.

The U.S. Geological Survey (USGS) deployed a sediment trap (McLane PARFLUX 78H) mooring in the northern Gulf of Mexico (27.5 °N and 90.3°W, water depth 1150 meters [m]) in January 2008 to collect seasonal time-series data on the flux and assemblage composition of planktic foraminifers. The trap was positioned in the water column at a depth of 700 m on the mooring cable to enable the collection of deeper dwelling species of planktic foraminifera. The trap contains 21 collection cups that were programmed to ...

Modern observations of planktic foraminifera from sediment trap studies help to constrain the regional ecology of paleoceanographically valuable species. Results from a weekly-resolved sediment trap time series (2008–2014) in the northern Gulf of Mexico demonstrate that 92% of Globorotalia truncatulinoides flux occurs in winter (January, February, and March), and that encrusted and non-encrusted individuals represent calcification in distinct depth habitats. Individual foraminiferal analysis (IFA) of G. ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

This is a set of 1132 oblique aerial photogrammetric images and their derivatives, collected from Capitola to Pajaro Dunes with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1836 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3494 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1309 oblique aerial photogrammetric images and their derivatives, collected from Santa Cruz to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2753 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1600 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1569 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ano Nuevo with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3234 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3036 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4521 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 4808 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Lucia with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5642 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5044 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 1975 oblique aerial photogrammetric images and their derivatives, collected from Pedro Point to Sunset Beach with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 628 oblique aerial photogrammetric images and their derivatives, collected from SeaCliff Beach to Fort Ord with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3045 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3164 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 642 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 410 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 757 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 5069 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2948 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2072 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 5365 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5355 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3550 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1533 oblique aerial photogrammetric images and their derivatives, collected from Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 5846 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4734 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2541 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1967 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 5042 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3777 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1911 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 1782 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Davenport with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1444 oblique aerial photogrammetric images and their derivatives, collected from Davenport to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3072 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1880 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 1979 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4835 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1890 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 3862 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1982 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1896 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 3796 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 4919 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2049 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 5626 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2678 oblique aerial photogrammetric images and their derivatives, collected from PigeonPt to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4722 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2066 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 2269 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2098 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 4595 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3661 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2105 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2763 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5039 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2943 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1939 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1839 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2758 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2195 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2915 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2077 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2374 vertical aerial photogrammetric images and their derivatives, collected from Half Moon Bay to Santa Cruz with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2123 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3929 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4930 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2869 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4772 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1821 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1965 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 4787 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2323 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 3059 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2161 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2286 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5140 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2003 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 8762 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 11207 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 11776 near-nadir aerial photogrammetric images and their derivatives, collected from CZU fire with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 4889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 5954 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1160 oblique aerial photogrammetric images and their derivatives, collected from Mud Creek Slide to Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera ...

This is a set of 11805 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Mussel Rock CA with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 14032 oblique aerial photogrammetric images and their derivatives, collected from Hoh Head to Cape Mendocino with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1712 oblique aerial photogrammetric images and their derivatives, collected from Cape Falcon to Cascade Head with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2060 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Nestucca River OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 2324 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2158 oblique aerial photogrammetric images and their derivatives, collected from NW WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

This is a set of 2413 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 10139 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is an ongoing collection of aerial oblique and near-nadir images, ancillary data, and derivatives, from aerial surveys of coastal and near-coastal environments with a crewed light aircraft using the "PCMSC PlaneCam," a mounted fixed-lens DSLR camera with an attached consumer-grade GPS for time-keeping and approximate position, and a Global Navigation Satellite System (GNSS) for precise positioning. Data are collected and produced primarily for coastal monitoring using structure-from-motion ...

This is a set of 2671 oblique aerial photogrammetric images and their derivatives, collected from ptConception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2979 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2392 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Santa Barbara with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 2062 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2167 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 1968 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2212 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by ...

This is a set of 2006 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 2013 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Port Hueneme with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 2061 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 2371 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

This is a set of 4838 oblique aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 3086 vertical aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 645 oblique aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

This is a set of 4116 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 4281 oblique and near nadir aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the ...

This is a set of 7809 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

This is a set of 6976 oblique aerial photogrammetric images and their derivatives, collected from Juan de Fuca Strait to Grays Harbor with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

Microfossil (benthic foraminifera) and coordinate/elevation data were obtained from sediments collected in the coastal zones of Mississippi and Alabama, including marsh and estuarine environments of eastern Mississippi Sound and Mobile Bay, in order to develop a census for coastal environments and to aid in paleoenvironmental reconstruction. These data provide a baseline dataset for use in future wetland and estuarine change studies and assessments, both descriptive and predictive types. The data presented ...

Microfossil (benthic foraminifera) data from coastal areas were collected from state and federally managed lands within the Grand Bay National Estuarine Research Reserve and Grand Bay National Wildlife Refuge, Grand Bay, Mississippi/Alabama; federally managed lands of Bon Secour National Wildlife Refuge on Cedar Island and Little Dauphin Island, Alabama; and municipally managed land around Dauphin Island, Alabama. Samples were analyzed and quantified for foraminiferal census in order to document changes to ...

Microfossil (benthic foraminifera) data from coastal areas were collected from state and federally managed lands within the Grand Bay National Estuarine Research Reserve and Grand Bay National Wildlife Refuge, Grand Bay, Mississippi/Alabama; federally managed lands of Bon Secour National Wildlife Refuge on Cedar Island and Little Dauphin Island, Alabama; and municipally managed land around Dauphin Island, Alabama. Samples were analyzed and quantified for foraminiferal census in order to document changes to ...

Microfossil (benthic foraminifera) and coordinate/elevation data were obtained from sediments collected in the coastal zones of Mississippi and Alabama, including marsh and estuarine environments of eastern Mississippi Sound and Mobile Bay, in order to develop a census for coastal environments and to aid in paleoenvironmental reconstruction. These data provide a baseline dataset for use in future wetland and estuarine change studies and assessments, both descriptive and predictive types. The data presented ...

Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier Plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ...

Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ...

Wetland sediment data was collected from coastal Louisiana as part of a pilot study to develop a diatom-based proxy for past wetland water chemistry and the identification of sediment deposits for tropical storms. The complete dataset includes forty-six surface sediment samples and nine sediment cores. The surface sediment samples were collected in fresh to brackish marsh throughout the southwest Louisiana Chenier plain and are located coincident with Coastwide Reference Monitoring System (CRMS). Sediment ...

Fire in the Everglades National Park (ENP) has historically been influential in shaping the Everglades ecosystem. As a result, ENP has been documenting fire events since 1948, and these data have been incorporated into an Esri ArcGIS geodatabase (Smith, T.J. III, and others, 2015). According to this geodatabase, 757,078 hectares of wetlands burned from 1948 to 2011. The main type of vegetation that has burned is comprised of palustrine and estuarine wetlands; however, there are areas in ENP that are ...

This data release provides a summary of the absolute percent composition of all recovered material and relative percent composition of coral taxa in the Holocene-aged intervals of 61 coral-reef cores collected throughout the Florida Keys reef tract (FKRT) housed in the USGS Core Archive in St. Petersburg, FL (Estimated ages for distinct depths within each core are also provided; those ages were either measured by radiometric dating of coral samples at those depths or estimated by linear interpolation ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

This dataset is the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3800 observations representing 27 temperature manipulation studies, spanning nine biomes and nearly two decades of warming experiments. Data for this study were obtained from a combination of unpublished data and published literature values. We find that although warming increases soil respiration rates, there is limited evidence for a shifting respiration response with experimental ...

Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ...

Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ...

Saline tidal wetlands are important sites of carbon sequestration and produce negligible methane (CH4) emissions due to regular inundation with sulfate-rich seawater. Yet, widespread management of coastal hydrology has restricted vast areas of coastal wetlands to tidal exchange. These ecosystems often undergo impoundment and freshening, which in turn cause vegetation shifts like invasion by Phragmites, that affect ecosystem carbon balance. Understanding controls of carbon exchange in these understudied ...

Cores from living coral colonies were collected from Dry Tortugas National Park, Florida, to obtain skeletal records of past coral growth and allow geochemical reconstruction of environmental variables during the corals’ centuries-long lifespans. The samples were collected as part of the U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/) that provides science to assist resource managers tasked with the stewardship of coral reef resources. Three colonies ...

Massive corals are used as environmental recorders throughout the tropics and subtropics to study environmental variability during time periods preceding ocean-observing instrumentation. However, careful testing of paleoproxies is necessary to validate the environmental-proxy record throughout a range of conditions experienced by the recording organisms. As part of the USGS Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/), we tested the hypothesis that the coral Siderastrea siderea ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

Since 2002, the Woods Hole Coastal and Marine Science Center’s Samples Repository supports research by providing secure storage for geological, biological, and geochemical samples; maintaining organization and an active inventory of these sample collections; and providing access to these collections for study and reuse. This collections inventory has been compiled, organized, and released as a searchable database to provide researchers and the general public with means to discover and request scientific ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (http://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. It is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature tolerance. This ...

The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. Coral reef organisms are very sensitive to high and low water-temperature extremes. Therefore, it is critical to precisely know water temperatures experienced by corals and associated plants and animals that live in the dynamic nearshore environment to document thresholds in temperature ...

Coral reefs around the world have degraded over the last half-century as evidenced by loss of live coral cover. This ubiquitous observation led to the establishment of long-term, ecological monitoring programs in several regions with sizable coral-reef resources. As part of the U.S. Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis working group "Local-scale ecosystem resilience amid global-scale ocean change: the coral reef example," scientists gathered resultant data from four ...

Understanding the processes that govern whether a coral reef is accreting (growing) or dissolving are fundamental to questions of reef health and resiliency. A total of 52 surficial sediment samples were collected within a 1-km x 1-km area around Crocker Reef in the Florida Keys, USA, between 2013 and 2014. Samples 1-35 were collected in July 2013 and samples 36-52 were collected in July 2014. The samples were processed using conventional, published techniques (see process step section) to yield grain size ...

Understanding the processes that govern whether a coral reef is accreting (growing) or dissolving are fundamental to questions of reef health and resiliency. A total of 52 surficial sediment samples were collected within a 1-km x 1-km area around Crocker Reef in the Florida Keys, USA, between 2013 and 2014. Samples 1-35 were collected in July 2013 and samples 36-52 were collected in July 2014. The samples were processed using conventional, published techniques (see process step 2) to yield grain size and ...

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected June 24-25, 2014, within a 1-kilkometer (km) x 1-km area around Crocker Reef in the Florida Keys, USA. A total of 91,206 images of the seafloor and water column were collected along pre-defined transect lines and organized into three sets: track1, track2, and track3. This data release contains a subset of those images (25,485 images), all of which were used for benthic habitat classification, and ...

The distribution of benthic habitats for a 1-kilometer (km) x 1-km area around Crocker Reef in the Florida Keys, USA, is based upon underwater digital images of the seafloor collected on June 24 and 25, 2014 (Zawada and others, 2016). The imagery was collected using the U.S. Geological Survey (USGS) shallow Along-Track Reef-Imaging System (sATRIS), a boat-based, pole-mounted sensor package for mapping shallow-water benthic environments. The polygons contained in the shapefile included in this data release, ...

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected June 13-14, 2009 at Pulaski Shoal within Dry Tortugas National Park, Florida, USA. A total of 195,406 images of the seafloor and water column were collected along pre-defined transect lines and organized into 3 sets: track1, track2, and track3. This data release contains a subset of those images (32,135 images), all of which were used for benthic habitat classification, and contain GPS data. The data ...

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected July 13 to July 17, 2011 within Dry Tortugas National Park, Florida, USA. A total of 272,828 images of the seafloor and water column were collected along pre-defined transect lines and organized into 14 sets, track1-track14. This data release contains a subset of those images (43,991 images), all of which were used for benthic habitat classification and contain GPS data. The data were collected using ...

This data release includes new sub annual and mean annual Sr/Ca records from two species of massive coral, Orbicella faveolata (coral B3) and Siderastrea siderea (coral CG2), from the Dry Tortugas National Park, FL (DTNP). We combine these new records with published Sr/Ca data from three additional S. siderea coral (DeLong et al., 2014) to generate a 278-year long multi-species stacked Sr/Ca-SST record from DRTO.

This data release contains time-series photographs taken of corals and coral habitats in the Florida Keys between 1959 and 2015 at Carysfort Reef and Grecian Rocks (a total of six sites). The original intent was to show coral reef recovery after Hurricane Donna devastated the area in 1960. Corals, especially elkhorn and staghorn coral, grew prolifically after the storm until the late 1970s, then began to decline, with the maximum period of decline centered around 1983 and 1984. These time-series photographs ...

Underwater digital images, single-beam bathymetry, and global-positioning system (GPS) data were collected September 29-30, 2011 around Dustan Rocks Patch Reef, Thor Patch Reef, West Turtle Shoal Patch Reef, and Rawa Patch Reef in the Florida Keys. A total of 101,734 images were collected, covering 4672 square meteres (m2) of reef habitat. This data release contains a subset of 1,420 images, organized into four sets: Track1, Track2, Track3, and Track4. These images were used for coral bleaching assessments ...

The tetraether index of C86 (TEX86) and alkenone unsaturation index (Uk37Õ) molecular biomarker proxies have been broadly applied in down-core marine sediments to reconstruct past sea surface temperature (SST). Although both TEX86 and Uk37 have been interpreted as proxies for mean annual SST throughout the global ocean, regional studies of glycerol dibiphytanyl glycerol tetraethers (GDGT)s and alkenones in sinking particulate matter (SPM) are required to understand the influence of seasonality, depth ...

Staghorn coral, Acropora cervicornis, is a threatened species and the primary focus of western Atlantic reef-restoration efforts to date. As part of the USGS Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/), scientists investigated skeletal characteristics of nursery-grown staghorn coral reared using two commonly used grow-out methods at Mote Tropical Research Laboratory’s offshore nursery. USGS staff compared linear extension, calcification rate, and skeletal density of nursery ...

Vegetation type and density data were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Vegetation samples were collected by divers, and used to determine dry biomass density. These data were collected as part of a cooperative project, with the USGS California Water Science Center and the California ...

Extended time-series sensor data were collected between 2012 and 2016 in surface water of a tidal salt-marsh creek on Cape Cod, Massachusetts. The objective of this field study was to measure water chemical characteristics and flows, as part of a study to quantify lateral fluxes of dissolved carbon species between the salt marsh and estuary. Data consist of in-situ measurements including salinity, temperature, pH, dissolved oxygen, redox potential, fluorescent dissolved organic matter, turbidity, ...

This data release provides census counts of palynomorphs in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay.

Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ...

Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ...

Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ...

Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use along their Atlantic Coast breeding range. A smartphone application called iPlover was developed to collect standardized ...

The information contained in this data release are the results observed and collected during an experiment that tested the efficacy of nine compounds (2’4’ dihydroxychalcone, bithionol sulfoxide, carnidazole, furaltadone, plumbagin, oxyclozanide, quinacrine, tomatine, and toltrazuril), previously found to be effective against the parasitic ciliate family Philasteridae (Iglesias and others, 2002; Sueiro and others, 2022). One commercially available product (Kordon Ich Attack) was also tested, however was ...

The files in this data release (Kellogg and others, 2022) are those referenced in the journal article by Evans and others (2022) entitled “Biofilms as Potential Reservoirs of Stony Coral Tissue Loss Disease.” They contain an amplicon sequence variant (ASV) table and the raw 16S ribosomal ribonucleic acid (rRNA) gene amplicon deoxyribonucleic acid (DNA) sequence files from 15 microbial communities (sample names: CnD16B, CnD17B, CnD18B, CnD19B, CnD21B, CnD22B, CnD23B, CnD24B, CnD25B, PsD5B, CnH101B, ...