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This composite shaded relief image dataset depicts generalized bathymetry and topography of the Caribbean region.
Categories: Data, pre-SM502.8; Tags: AG, AI, AN, AW, Anguilla, All tags...
The Caribbean region is part of World Energy Assessment region 6 (Central and South America). A fundamental task in the assessment is to map the locations and type of production for existing oil and gas fields. The Petroconsultants database is the only available database that has coverage for the Caribbean region. Oil and gas field symbols represent field center-points and are published with permission from Petroconsultants International Data Corporation, 2002 database.
Categories: Data, pre-SM502.8; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AG, AI, AN, AW, Anguilla, All tags...
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The Streams and Rivers Condition Index is a broad ecological system index that classifies the landscape’s streams and river catchments into condition categories. The classification of the landscape in this manner is used to measure the relative departure of current wildlife habitat conditions from desired conditions as defined by parcel-level wildlife managers and landscape planners. The purpose of the index is to help practitioners determine appropriate next actions in each catchment, especially when used in conjunction with relevant species information. There are four condition categories, or classes, which range from the most ideal habitat conditions to the least ideal habitat conditions.
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Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the map feature extraction challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided...
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Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the map georeferencing challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided...
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Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training and validation data from the competition are provided here, as well as competition details and baseline solutions. The data are derived from published sources and are provided to the public to...
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This dataset includes a modified subset of polygon features that describe U.S. Geological Survey's defined geologic provinces of the World. Each province has a set of geologic characteristics that distinguish it from surrounding provinces. These characteristics may include dominant lithologies, the age of the strata, and/or structural type. Each province is assigned a unique numeric code and may fall within two or more countries or assessment regions.
Categories: Data, pre-SM502.8; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AG, AI, AN, AW, Anguilla, All tags...
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We provide annotated fish imagery data for use in deep learning models (e.g., convolutional neural networks) for individual and species recognition. For individual recognition models, the dataset consists of annotated .json files of individual brook trout imagery collected at the Eastern Ecological Science Center's Experimental Stream Laboratory. For species recognition models, the dataset consists of annotated .json files for 7 freshwater fish species: lake trout, largemouth bass, smallmouth bass, brook trout, rainbow trout, walleye, and northern pike. Species imagery was compiled from Anglers Atlas and modified to remove human faces for privacy protection. We used open-source VGG image annotation software developed...
This dataset describes faults and structural features of the Caribbean region (Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, Belize, British Virgin Islands, Cayman Islands, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Netherlands Antilles, Nicaragua, Panama, Puerto Rico, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago, Turks and Caicos Islands, United States, Venezuela, and the Virgin Islands (named countries may not be completely shown on map)).
Categories: Data, pre-SM502.8; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AG, AI, AN, AW, Age, All tags...
This dataset includes polygons that describe the geologic age of surface outcrops of bedrock of the Caribbean region (Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, Belize, British Virgin Islands, Cayman Islands, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Netherlands Antilles, Nicaragua, Panama, Puerto Rico, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago, Turks and Caicos Islands, United States, Venezuela, and the Virgin Islands (named countries may not be completely shown on map)).
Categories: Data, pre-SM502.8; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AG, AI, AN, AW, Age, All tags...


    map background search result map search result map Annotated fish imagery data for individual and species recognition with deep learning Oil and Gas Fields of the Caribbean Region, 2004 (fld6bg) Faults of the Caribbean Region (flt6bg) Surface Geology of the Caribbean Region (geo6bg) Geologic Provinces of the Caribbean Region, 2004 (prv6bg) Shaded Relief Image of the Caribbean Region (shadedrelief.jpg) Streams and Rivers Condition Index Training and validation data from the AI for Critical Mineral Assessment Competition Map georeferencing challenge training and validation data Map feature extraction challenge training and validation data Streams and Rivers Condition Index Oil and Gas Fields of the Caribbean Region, 2004 (fld6bg) Faults of the Caribbean Region (flt6bg) Surface Geology of the Caribbean Region (geo6bg) Shaded Relief Image of the Caribbean Region (shadedrelief.jpg) Geologic Provinces of the Caribbean Region, 2004 (prv6bg) Annotated fish imagery data for individual and species recognition with deep learning Training and validation data from the AI for Critical Mineral Assessment Competition Map georeferencing challenge training and validation data Map feature extraction challenge training and validation data