This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

The data in the csv and text files provided in this release are an update to the data tables originally published in USGS Open-File Report (OFR) 83-250 (https://doi.org/10.3133/cir892). Those data were published as paper tables and have until now only been available as pdf image documents that were not machine readable. USGS OFR 83-250 presented data for 2071 geothermal sites which are representative of 1168 low-temperature geothermal systems identified in 26 states. The low-temperature geothermal systems consist of 978 isolated hydrothermal-convection systems, 148 delineated-area hydrothermal-convection systems, and 42 delineated-area conduction-dominated systems. The basic data and estimates of reservoir conditions are presented for each geothermal system, and energy estimates are given for the accessible resource base, resource, and beneficial heat for each isolated system. This electronic version of USGS OFR 83-250 tables includes several changes. Typographical errors wer ...

Data collected on various vessel operations on the Great Lakes and select connecting waterways. This vessel operations data set is part of and connected to a larger database of Great Lakes research that includes trawl and gillnet catch data, sample information, as well as effort, operation conditions, and location details. Multiple operations were conducted on all Great Lakes each year (1958-2016) beginning in early spring and ending in late fall. Each vessel operation was completed for a specific purpose, or target mission, which are enumerated in this data set. RVCAT stores data from the research vessels associated with the United States Geological Survey, Great Lakes Science Center and it's partners. The Trawl Tables contain data collected from the research vessel deploying various trawl gear.

USGS Quad grid

USGS Topo is a tile cache base map service that combines the most current data in The National Map (TNM), and other public-domain data, into a multi-scale topographic reference map. Data themes included are Boundaries, Geographic Names, Transportation, Contours, Hydrography, Land Cover, Shaded Relief, and Bathymetry. This service is designed to provide a seamless view of TNM data in a geographic information system (GIS) accessible format.This service is published by USGS on The National Map and is refreshed annually.Please reference metadata and USGS for contact information. Contact: GIS.Librarian@FloridaDEP.gov

This product contains plot location data for LCMAP Hawaii Reference Data in a .shp format as well as annual land cover, land use, and change process variables for each reference data plot in a separate .csv table. The same information available in the.csv file is also provided in a .xlsx format. The LCMAP Hawaii Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Hawaii Reference Data Product includes the collection of an independent dataset of 600 30-meter by 30-meter plots across the island chain of Hawaii. The LCMAP Hawaii Reference Data Products collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across Hawaii from 2000-2019. The sites in this dataset were collected via manual image interpretation. These samples were selected using a stratified random sampling process via stratification using a hybrid NLCD 2001 Hawaii and NOAA C-Cap 2011 land cover map.

description: Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow, and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding past and present shoreline changes. There is also need for a comprehensive analysis of shoreline movement that is regionally consistent. To meet these national needs, the USGS National Assessment of Shoreline Change Project has collected and analyzed a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. This dataset consists of long-term (100+ years) shoreline change rates. Rate calculations were computed using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate based on all available shoreline data. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate long-term rates. To make these results more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. This service meets open geospatial consortium standards. The data compilation used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Historic Shorelines by State. The reference baseline used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Offshore Baseline. The locations of the transects used in the change rate calculation are available in a service with the title USGS Map service: National Shoreline Change - Intersection Points. The geographic information system (GIS) data layers from this web service are cataloged by state for ease of access.; abstract: Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow, and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding past and present shoreline changes. There is also need for a comprehensive analysis of shoreline movement that is regionally consistent. To meet these national needs, the USGS National Assessment of Shoreline Change Project has collected and analyzed a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. This dataset consists of long-term (100+ years) shoreline change rates. Rate calculations were computed using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate based on all available shoreline data. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate long-term rates. To make these results more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. This service meets open geospatial consortium standards. The data compilation used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Historic Shorelines by State. The reference baseline used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Offshore Baseline. The locations of the transects used in the change rate calculation are available in a service with the title USGS Map service: National Shoreline Change - Intersection Points. The geographic information system (GIS) data layers from this web service are cataloged by state for ease of access.

These environmental raster covariate, geospatial vector data, and tabular data were compiled as input data for the Automated Reference Toolset (ART) algorithm.

This collection of the 3D Elevation Program (3DEP) is at 1/3 arc-second (approximately 10 m) resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. The seamless 1/3 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The vertical reference will vary in other areas. The seamless 1/3 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and in limited areas of Alaska. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. All 3DEP products are public domain.

File AET2RET_Ratios.csv lists the AET to RET (actual to reference evapotranspiration) ratios, or AET/RET, used to calculate actual evapotranspiration for each land cover type. The daily measured AET data collected at the ET stations were used to calculate the monthly totals for each month of the year. These monthly AET totals were then used to calculate the average AET/RET monthly ratios for the land cover of the ET station by dividing the AET rates by the RET rates obtained from the Florida ET network (http://fl.water.usgs.gov/et/; USGS, 2016). The land cover types represented in these data are forest, grass, marsh, open water, ridge, urban, and agriculture. The AET/RET ratios for these land cover types were presented in O’Reilly, 2007; Sumner and others, 2017; Sumner, 2017; and U.S. Geological Survey, 2017. These ratios are used as an extrapolation of AET rates for all months in the entire 2000-2016 period of record, not just the months when the ET stations were in operation. Land-cover based types were obtained from a generalized land use map provided by the Florida Geological Survey ( https://floridadep.gov/fgs ). Average monthly AET/RET rates for the period of record were calculated from measured AET data from the ET stations listed in file AET_Monthly_Totals.csv. These references were used in the generation of the AET/RET ratios for the land cover types in east-central Florida: O’Reilly, A.M., 2007, Effects of the temporal variability of evapotranspiration on hydrologic simulation in central Florida: U.S. Geological Survey Scientific Investigations Report 2007–5100, 36 p. Sumner, D.M., Hinkle, C.R. and Becker, K.E., 2017, Evapotranspiration (ET) at University of Central Florida urban site, daily data, Orange County, Florida, January 29, 2009–September 27, 2012: U.S. Geological Survey data release, accessed September 20, 2017, at https://doi.org/10.5066/F7JS9NZB. Sumner, D.M., 2017, Evapotranspiration (ET) at Tiger Bay State Forest site, Volusia County, Florida, January 1, 1998–December 31, 1999: U.S. Geological Survey data release, accessed September 20, 2017, at https://doi.org/10.5066/F7SB447H. U.S. Geological Survey, 2016, Evapotranspiration information and data: Caribbean-Florida Water Science Center website, accessed June 29, 2016, at http://fl.water.usgs.gov/et/. U.S. Geological Survey, 2017, National Water Information System—Web interface: Accessed September 20, 2017, at http://dx.doi.org/10.5066/F7P55KJN.

The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program (NWQP). The NWQN represents the consolidation of four historical national networks: the USGS National Water-Quality Assessment (NAWQA) Project, the USGS National Stream Quality Accounting Network (NASQAN), the National Monitoring Network (NMN), and the Hydrologic Benchmark Network (HBN). The NWQN includes 22 large river coastal sites, 41 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Matching Funds program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release provides estimated agricultural pesticide use for 83 NWQN watersheds for 110 pesticide compounds from 1992-2014. Pesticide use was not estimated for the 30 wadeable stream reference sites, or from 3 large river coastal sites (07381590, "Wax Lake Outlet at Calumet, LA3"; 07381600, "Lower Atchafalaya River at Morgan City, LA2"; or 15565477, "Yukon River at Pilot Station, AK"). Use was not estimated for reference sites because pesticides are not monitored at reference water-quality sampling sites. Pesticide use data are not available for Alaska and thus no data is available for the Yukon River site. The other two coastal sites (07381590 and 07381600) where use was not estimated are outflow distributaries into the Gulf of Mexico. This data release provides use estimates for the same pesticide parent compounds sampled in water and analyzed by USGS, National Water Quality Laboratory (NWQL), Schedule 2437: http://wwwnwql.cr.usgs.gov/USGS/catalog/index.cfm. Pesticide use data are not available for degradate compounds or for compounds not used in agricultural applications. County-level pesticide use estimates and methods for making the estimates are available on the USGS Pesticide National Synthesis Project (PNSP) page: https://water.usgs.gov/nawqa/pnsp/usage/maps/ , https://dx.doi.org/doi:10.5066/F7NP22KM . County-level estimates are based on farm surveys of pesticide use. Two estimates, EPestLOWkg and EPestHIGHkg, provide a range of values of pesticide use and differ in how they treated situations where surveys were done but pesticide use was not reported for a particular pesticide-by-crop combination. The HIGH method tends to spread estimated use over a larger geographic area. EPestLOWkg annual-use totals can be greater than EPestHIGHkg totals when the LOW method of estimation concentrates the use to a particular area while the HIGH method spreads the use over a larger area. Details on the difference between the two estimates are explained on the PNSP page. There is uncertainty in both the HIGH and LOW estimates that is difficult to quantify. A user should become familiar with the two methods to decide which estimate is best for a specific application. To obtain estimates for NWQN watersheds county-level estimates were proportionally allocated to agricultural land within each NWQN watershed. Zero values indicate that pesticide use was estimated for that watershed but that the total use for the watershed was less than 0.1 kg. Null values indicate that use was not estimated because there was not enough farm survey data available to make an estimate for that particular compound in that watershed. Place holder rows were kept for all compounds and years regardless of whether an estimate was made so that users know which compounds were included in the estimation process. Data from this release are presented at the USGS Tracking Water Quality page: http://cida.usgs.gov/quality/rivers/home, authored by Deacon, J.R., Lee, C.J., Toccalino, P.L., Warren, M.P., Baker, N.T., Crawford, C.G., Gilliom, R.G., and Woodside, M.D., 2015, Tracking water-quality of the Nation’s rivers and streams, U.S. Geological Survey Web page: http://cida.usgs.gov/quality/rivers, https://dx.doi.org/doi:10.5066/F70G3H51.

The data are 475 thematic land cover raster’s at 2m resolution. Land cover classification was to the land cover classes: Tree (1), Water (2), Barren (3), Other Vegetation (4) and Ice & Snow (8). Cloud cover and Shadow were sometimes coded as Cloud (5) and Shadow (6), however for any land cover application would be considered NoData. Some raster’s may have Cloud and Shadow pixels coded or recoded to NoData already. Commercial high-resolution satellite data was used to create the classifications. Usable image data for the target year (2010) was acquired for 475 of the 500 primary sample locations, with 90% of images acquired within ±2 years of the 2010 target. The remaining 25 of the 500 sample blocks had no usable data so were not able to be mapped. Tabular data is included with the raster classifications indicating the specific high-resolution sensor and date of acquisition for source imagery as well as the stratum to which that sample block belonged. Methods for this classifi ...

The Landsat 7 Data Users Handbook is prepared by the U.S. Geological Survey (USGS) Landsat Project Science Office at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD, and the National Aeronautics and Space Administration (NASA) Landsat Project Science Office at NASA’s Goddard Space Flight Center (GSFC) in Greenbelt, Maryland.

City of Riverside Open Data for use in the city.

The Shuttle Radar Topography Mission (SRTM, see Farr et al. 2007) digital elevation data is an international research effort that obtained digital elevation models on a near-global scale. This SRTM V3 product (SRTM Plus) is provided by NASA JPL at a resolution of 1 arc-second (approximately 30m). This dataset has undergone a void-filling process using open-source data (ASTER GDEM2, GMTED2010, and NED), as opposed to other versions that contain voids or have been void-filled with commercial sources. For more information on the different versions see the SRTM Quick Guide. Documentation: User's Guide General Documentation Algorithm Theoretical Basis Document (ATBD)

Potential evapotranspiration (PET), and reference evapotranspiration (RET) are estimated at an approximately 2-kilometer spatial grid and daily time-scale from January 1, 2018 to December 31, 2018 for the entire State of Florida.
Missing values are indicated with -9999.99. Missing values are due to unavailable solar radiation data, derived from the GOES satellite. Potential and reference evapotranspiration were computed on the basis of albedo, solar radiation, and meteorological data observed at weather stations. Solar radiation data obtained from Geostationary Operational Environmental Satellites (GOES) were used to estimate daily PET and RET at grid points. Albedo at grid points was computed on the basis of observations from the Moderate Resolution Imaging Spectrometer (MODIS) satellite.Meteorological data for 2018 was interpolated to grid points using a radial basis function.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Monterey map area, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. The raster data file is included in "SeafloorCharacter_2m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. This raster-format seafloor-character map shows four substrate classes in the Offshore of Monterey map area, California. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Depth Zone 5 (deeper than 200 m), Slope Class 1 (0 degrees - 5 degrees; flat), and Slope Class 2 (5 degrees - 30 degrees; sloping). Depth Zone 1 (intertidal), and Slopes Classes 3 and 4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008), using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014. Bathymetry data were collected at two different resolutions: at 2-m resolution, down to approximately 90-m water depth (1998-2012 CSUMB and MBARI data); and at 5-m resolution, in the deeper areas (1998-2012 MBARI data). The final resolution of the seafloor-character map is determined by the resolution of both the backscatter and bathymetry datasets; therefore, separate seafloor-character maps were generated to retain the maximum resolution of the source data. Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This data collection of the 3D Elevation Program (3DEP) consists of Lidar Point Cloud (LPC) projects as provided to the USGS. These point cloud files contain all the original lidar points collected, with the original spatial reference and units preserved. These data may have been used as the source of updates to the 1/3-arcsecond, 1-arcsecond, and 2-arcsecond seamless 3DEP Digital Elevation Models (DEMs). The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Lidar (Light detection and ranging) discrete-return point cloud data are available in LAZ format. The LAZ format is a lossless compressed version of the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. Point Cloud data can be converted from LAZ to LAS or LAS to LAZ without the loss of any information. Either format stores 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of geo-referenced x, y coordinates and z (elevation), as well as other attributes for each point. Additonal information about the las file format can be found here: https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities. All 3DEP products are public domain.

These data include water chemistry from headwater streams to large rivers that have recently turned orange and reference rivers that have not. These samples were collected in two national parks in Arctic Alaska: Kobuk Valley National Park, and Noatak National Preserve.

Potential evapotranspiration (PET), and reference evapotranspiration (ETo) are estimated at a 1-kilometer spatial resolution and daily time-scale from January 1, 2022 to December 31, 2022 for Florida, Alabama, Georgia, South Carolina, and parts of Mississippi, North Carolina, and Tennessee. PET and ETo were computed on the basis of solar radiation, meteorological data (min/max temperature, min/max relative humidity, and mean wind speed at 2-meter height), and shortwave blue-sky albedo data. Solar radiation was computed from Geostationary Operational Environmental Satellite (GOES) sensor data, blue-sky albedo was computed from the Moderate Resolution Imaging Spectrometer (MODIS) MCD43A1 BRDF/Albedo data product, and meteorological data were simulated using the Weather Research and Forecasting (WRF) model. Open-source tools for managing the NetCDF files in this data release can be found at https://code.usgs.gov/jbellino/florida-goes-et.