The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental U.S. NAIP projects are contracted each year based upon available funding and the imagery acquisition cycle. Beginning in 2003, NAIP was acquired on a 5-year cycle. 2008 was a transition year, and a …

The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental United States. This service contains NAIP imagery in the Web Mercator projection.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/imagery/rest/services/NAIP/MD_NAIPImagery/ImageServer

The USGS NAIP Imagery service from The National Map consists of 4-band high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. Resolution of National Agriculture Imagery Program (NAIP) data is most commonly 1 meter, which means that every pixel in the digital orthoimage covers a one meter square of the earth’s surface. Some states to include Wyoming and New York began collection of 0.5 meter pixel resolution NAIP in 2015. Many states contribute orthoimagery to The National Map, and USGS relies on a partnership with the U.S. Department of Agriculture’s Farm Service Agency for NAIP data. The USGS NAIP Imagery service is a mosaic of natural color and color infrared (4-band) aerial imagery, containing NAIP and other imagery sources to complete the mosaic. The National Map download client allows free downloads of public domain compressed orthoimagery in JPEG 2000 (.jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution, also in JPEG 2000 (.jp2) format. For additional information on orthoimagery, go to https://nationalmap.gov/ortho.html. This imagery service is for viewing only, no downloading of the raster images available. NAIP/Statewide_NAIP_2009_3ft_4band_wsps_83h_img

Color infrared (CIR) representation of NAIP 2016 60cm aerial imagery. Band1=NearIR, Band2=R, Band3=G.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

Natural color representation of NAIP 2014 aerial imagery. Band1=R, Band2=G, Band3=B.This service is offered by the California Department of Fish and Wildlife (CDFW). For more information about CDFW map services, please visit: https://wildlife.ca.gov/Data/GIS/Map-Services

This data layer contains the index grid for the National Agriculture Imagery Program (NAIP) 2006 imagery. The NAIP program is administered by the U.S. Department of Agriculture Farm Service Agency and has been established to support two main FSA strategic goals centered on agricultural production.Owner: U.S. Department of Agriculture Farm Service AgencyThis is a MD iMAP hosted service. Find more information on https://imap.maryland.gov.Map Service Link:https://mdgeodata.md.gov/imagery/rest/services/NAIP/HistoricNAIPImageryGrid/MapServer/1

The USGS NAIP Imagery service from The National Map consists of 4-band high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. Resolution of National Agriculture Imagery Program (NAIP) data is most commonly 1 meter, which means that every pixel in the digital orthoimage covers a one meter square of the earth’s surface. Some states to include Wyoming and New York began collection of 0.5 meter pixel resolution NAIP in 2015. Many states contribute orthoimagery to The National Map, and USGS relies on a partnership with the U.S. Department of Agriculture’s Farm Service Agency for NAIP data. The USGS NAIP Imagery service is a mosaic of natural color and color infrared (4-band) aerial imagery, containing NAIP and other imagery sources to complete the mosaic. The National Map download client allows free downloads of public domain compressed orthoimagery in JPEG 2000 (.jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution, also in JPEG 2000 (.jp2) format. For additional information on orthoimagery, go to https://nationalmap.gov/ortho.html. This imagery service is for viewing only, no downloading of the raster images available. NAIP/NAIP_2003_2m_color_wsps_83h_img

APFO is home to one of the country's largest aerial film libraries. We currently house more than 70,000 rolls of film (10 million plus images). Our film dates from 1955 to the present. We have coverage of most of the United States and its territories. Historic aerial images play a more vital role today than ever before with environmental assessments, change detection, and property boundary disputes. Over the years, APFO (Aerial Photography Field Office) joined with other federal agencies in cooperative photography programs. The latest program is the National Agriculture Imagery Program (NAIP). APFO now provides NAIP digital imagery to the USDA Service Center Agencies that utilize Geographic Information Systems (GIS) as the method for administering federal farm programs. GIS streamlines daily operation and facilitates updates of vital information which also helps support our nation's farmers and ranchers. The files for locating available aerial imagery include a comprehensive PDF file of all states, Forest Service PDF file, Alpha FIPS PDF file, ability to search for a particular state and county, APFO Historical Availability of Imagery, and ArcGIS Historical Availability of Imagery interactive map. Resources in this dataset:Resource Title: Imagery Catalogs. File Name: Web Page, url: https://www.fpacbc.usda.gov/geo/customer-service/imagery-catalogs/index.html

This data release includes cross section survey data collected during site visits to USGS gaging stations located throughout the Willamette and Delaware River Basins and multispectral images of these locations acquired as close in time as possible to the date of each site visit. In addition, MATLAB source code developed for the Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) framework is also provided. The site visit data were obtained from the Aquarius Time Series database, part of the USGS National Water Information System (NWIS), using the Publish Application Programming Interface (API). More specifically, a custom MATLAB function was used to query the FieldVisitDataByLocationServiceRequest endpoint of the Aquarius API by specifying the gaging station ID number and the date range of interest and then retrieve the QRev XML attachments associated with site visits meeting these criteria. These XML files were then parsed using another custom MATLAB function that served to extract the cross section survey data collected during the site visit. Note that because many of the site visits involved surveying cross sections using instrumentation that was not GPS-enabled, latitude and longitude coordinates were not available and no data values (NaN) are used in the site visit files provided in this data release. Remotely sensed data acquired as close as possible to the date of each site visit were also retrieved via APIs. Multispectral satellite images from the PlanetScope constellation were obtained using custom MATLAB functions developed to interact with the Planet Orders API, which provided tools for clipping the images to a specified area of interest focused on the gaging station and harmonizing the pixel values to be consistent across the different satellites within the PlanetScope constellation. The data product retrieved was the PlanetScope orthorectified 8-band surface reflectance bundle. PlanetScope images are acquired with high frequency, often multiple times per day at a given location, and so the search was restricted to a time window spanning from three days prior to three days after the site visit. All images meeting these criteria were downloaded and manually inspected; the highest quality image closest in time to the site visit date was retained for further analysis. For the gaging stations within the Willamette River Basin, digital aerial photography acquired through the National Agricultural Imagery Program (NAIP) in 2022 were obtained using a similar set of MATLAB functions developed to access the USGS EarthExplorer Machine-to-Machine (M2M) API. The NAIP quarter-quadrangle image encompassing each gaging station was downloaded and then clipped to a smaller area centered on the gaging station. Only one NAIP image at each gaging station was acquired in 2022, so differences in streamflow between the image acquisition date and the date of the site visit closest in time were accounted for by performing separate NWIS web queries to retrieve the stage and discharge recorded at the gaging station on the date the image was acquired and on the date of the site visit. These data sets were used as an example application of the framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) and this data release also provides MATLAB source code developed to implement this approach. The code is packaged in a zip archive that includes the following individual .m files: 1) getSiteVisit.m, for retrieving data collected during site visits to USGS gaging stations through the Aquarius API; 2) Qrev2depth.m, for parsing the XML file from the site visit and extracting depth measurements surveyed along a channel cross section during a direct discharge measurement; 3) orderPlanet.m, for searching for and ordering PlanetScope images via the Planet Orders API; 4) pollThenGrabPlanet.m, for querying the status of an order and then downloading PlanetScope images requested through the Planet Orders API; 5) organizePlanet.m, for file management and cleanup of the original PlanetScope image data obtained via the previous two functions; 6) ingestNaip.m, for searching for, ordering, and downloading NAIP data via the USGS Machine-to-Machine (M2M) API; 7) naipExtractClip.m, for clipping the downloaded NAIP images to the specified area of interest and performing file management and cleanup; and 8) crossValObra.m, for performing spectrally based depth retrieval via the Optimal Band Ratio Analysis (OBRA) algorithm using a k-fold cross-validation approach intended for small sample sizes. The files provided through this data release include: 1) A zipped shapefile with polygons delineating the Willamette and Delaware River basins 2) .csv text files with information on site visits within each basin during 2022 3) .csv text files with information on PlanetScope images of each gaging station close in time to the date of each site visit that can be used to obtain the image data through the Planet Orders API or Planet Explorer web interface. 4) A .csv text tile with information on NAIP images of each gaging station in the Willamette River Basin as close in time as possible to the date of each site visit, along with the stage and discharge recorded at the gaging station on the date of image acquisition and the date of the site visit. 5) A zip archive of the clipped NAIP images of each gaging station in the Willamette River Basin in GeoTIFF format. 6) A zip archive with source code (MATLAB *.m files) developed to implement the Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) framework.

Polygons of Urban Tree Canopy in Washington, DC in 2015. These data represent detailed urban tree canopy cover in Washington, D.C. The data were derived using remote sensing technologies on aerial imagery from the National Agriculture Imagery Program (NAIP), flown in July 2015, and aerial imagery and LiDAR data from Sanborn and the DC Office of the Chief Technology Officer, flown in April 2015.

A Green Infrastructure map of Prince William county, VA was developed to provide quantification of canopy and associated data for environmental monitoring. Digital aerial imagery, collected for the National Agriculture Imagery (NAIP) 2012 program at 1 meter resolution was classified to a Green Infrastructure Level 1 classification scheme with the following classes: 1) Non Woody Vegetation, 2) Woody Vegetation, 3) Impervious, 4) Water and 5) Bare Soil. The image was classified using Classification and Regression Tree techniques (CART analysis) and raster modeling. The classification accuracy assessment gave an overall accuracy of 95.25%This 2012 update is the result of a change detection process which buillt on the original 2008 classification. Changed areas were updated, and several other classification scheme changes were made, such as the reclassification of pools as impervious surfaces.Woods feature class is a subset of the Landcover classification of 2) Woody Vegetation. The Woody Vegetation features were selected and copied into a seperate stand alone dataset for tree cover.

Polygons of Urban Tree Canopy in Washington, DC in 2015. These data represent detailed urban tree canopy cover in Washington, D.C. The data were derived using remote sensing technologies on aerial imagery from the National Agriculture Imagery Program (NAIP), flown in July 2015, and aerial imagery and LiDAR data from Sanborn and the DC Office of the Chief Technology Officer, flown in April 2015.

BTPrairieDogColonyPotentialOccurrence is an ESRI SDE Feature Class depicting the probability of black-tailed prairie dog colonies occurring within the Overall Range within Colorado. This information was derived from field personnel. A variety of data capture techniques were used including implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).CPW staff delineated and categorized these areas of potential occurrence based on the results of a 2016 rangewide survey (see Howlin, S., J. Mitchell. December 2016. Monitoring Black-Tailed Prairie Dogs in Colorado with the 2015 NAIP Imagery.)These data are updated as needed and were last updated in 2017.

Data created from the combination of Wind Turbine Data created by the FAA and USGS. Duplicate turbines were removed. Below is the discription for each.FAA - Point shapefile of Wind Turbine locations in Wyoming as of December 2010. Turbine location and attribute data extracted from the FAA Obstruction Evaluation Database (https://oeaaa.faa.gov/oeaaa/external/portal.jsp). The FAA requires evaluation of any wind turbine (or structure) over 200ft. Therfore any wind turbine under 200ft would not be included in this data layer. In 2008 the FAA put a focus on wind turbines creating region categories specifically for wind turbines. With this, records for wind turbines before 2008 are less inclusive. The FAA database provides no determination of Wind Turbines that have been built and Wind Turbines that are still in planning stages. Therefore this layer includes Wind Turbines that may not be constructed yet but are in planning/development stages.USGS - The Wyoming wind turbine data set was developed for the project "Seasonal predictive habitat models for Greater Sage-grouse in Wyoming". This project is aimed at developing spatially-explicit seasonal distribution models for Sage-Grouse in Wyoming, which will provide resource managers tools for conservation planning. These specific data are being used for assessing the impact of disturbance resulting from wind energy development within Wyoming on sage-grouse populations. Additionally, this data will also support the Wyoming Landscape Conservation Initiative (WLCI). WLCI is a long-term, science-based, collaborative effort to ensure that the Southwest Wyoming's wildlife and its habitats are sustained over time with increased land-use pressures. Additional information about WLCI can be found at www.wlci.gov or in the Wyoming Landscape Conservation Initiative Science Workshop Proceedings (U.S. Geological Survey Scientific Report 2008-5073 found on-line at http://pubs.usgs.gov/sir/2008/5073/). These data represent locations of wind turbines found within Wyoming as of 08/01/2009. The attributes are estimates based on what information could be found via American Wind Energy Association (AWEA) and miscellaneous on-line reports. Caution should be used when using the data attributes. The locations are derived from NAIP August 2009 true color imagery and have a positional accuracy of approximately +/-5 meters. Because some wind turbines were under construction, under construction wind turbine locations will likely be less accurate, and therefore caution is required while using these data.

The dataset displays the presence and absence of forested areas within a 100 foot-buffer of a stream or waterbody. The National Hydrography Dataset (NHD) stream layer developed by the United States Geological Survey was buffered 100-feet on each side of the stream centerline to determine stream buffers in Maryland. A shoreline file developed by the Maryland State Highway Administration was buffered 100-feet to determine the shoreline buffer in Maryland. The resulting buffer layers were clipped with a forest cover layer to determine the presence and absence of forest in those buffers. The forest cover layer was derived from a tree canopy layer developed by the Community College of Baltimore County, Catonsville, Geography Department. The tree canopy was developed using 2007 National Agriculture Imagery Program (NAIP) color infra-red 1-meter imagery. To determine areas forested, contiguous areas of tree cover less than 1 acre were removed from the dataset and then used for clipping the stream and shoreline buffers.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Biota/MD_Forests/FeatureServer/1**Please note, due to the size of this dataset, you may receive an error message when trying to download the dataset. You can download this dataset directly from MD iMAP Services at: https://mdgeodata.md.gov/imap/rest/services/Biota/MD_Forests/MapServer/exts/MDiMAPDataDownload/customLayers/1**