The National Agriculture Imagery Program (NAIP) is administered by the U.S. Department of Agriculture's Farm Production and Conservation Business Center (FPAC-BC) Geospatial Enterprise Operations (GEO) Branch. NAIP acquired aerial imagery at a resolution of 1-meter ground sample distance (GSD) for the United States from 2003-2017 during the agricultural growing season, or leaf-on conditions. The images are orthorectified which combines the image characteristics of an aerial photograph with the georeferenced qualities of a map. In 2018, the ground resolution standard changed to 0.6 meter with the option for 0.3 meter data was added for consideration over coastal states. The repeat flying cycle was also changed to no longer than a 3-year cycle from its 5-year cycle back in 2003-2009. 2009 to present coverage provides a refresh of every 3-years and less responding to user needs across the United States. Each individual image tile is based on a 3.75-minute longitude by 3.75-minute latitude quarter quadrangle plus a 300-meter buffer on all four sides. In 2024 the buffer was changed to 12-meters on all four sides. Tiles in the NAIP collection are natural color (red, green, and blue bands) or color near infra-red (red, green, blue, and near infrared bands) and may contain as much as 10 percent cloud cover per tile.

This image layer features recent high-resolution (1m) aerial imagery for the continental United States made available by the USDA Farm Services Agency. The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental United States. A primary goal of the NAIP program is to make digital ortho photography available to governmental agencies and the public within a year of acquisition. This image layer provides access to the most recent NAIP imagery for each state and will be updated annually as new imagery is made available. This imagery is published in 4-bands (RGB and Near Infrared), where available, with the option to display the imagery as false color to show the IR band or to display the NDVI (Normalized Difference Vegetation Index) showing relative biomass of an area.

The USGS NAIP Imagery service from The National Map (TNM) consists of 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 1 meter, which means that every pixel in the digital orthoimage covers a one meter square of the earth’s surface. 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 1 meter resolution natural color and color infrared aerial imagery, containing NAIP and other imagery sources to complete the mosaic. The National Map viewer allows free downloads of public domain, 1-meter resolution 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 data set contains imagery from the National AgriculturalImagery Program (NAIP). NAIP acquires digital ortho imageryduring the agricultural growing seasons in the continental U.S..A primary goal of the NAIP program is to enable availabilty ofortho imagery within a year of acquisition. NAIP provides twomain products: 1 meter ground sample distance (GSD) orthoimagery rectified to a horizontal accuracy of within +/- 5meters of reference digital ortho quarter quads (DOQQS) fromthe National Digital Ortho Program (NDOP); and, 2 meter GSDortho imagery rectified to within +/- 10 meters of referenceDOQQs. The tiling format of NAIP imagery is based on a 3.75'x 3.75' quarter quadrangle with a 360 meter buffer on all foursides. NAIP quarter quads are rectified to the UTM coordinatesystem NAD83. NAIP imagery can obtain as much as 10% cloudcover per tile. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

Spatial data on soils, land use, and topography, combined with knowledge of conservation effectiveness can be used to identify alternatives to reduce nutrient discharge from small watersheds. This database was developed to be used in conjunction with the Agricultural Conservation Planning Framework Toolkit. Data comprise soil survey information and land use. Soil characterization data were extracted from the Natural Resources Conservation Service (NRCS) Web Soil Survey (Soil Survey Staff, 2013). Land use coverages were developed to represent agricultural fields and the types and rotations of agricultural crops and other land cover types. Land use boundaries were produced by editing a publicly available USDA field boundaries dataset (pre-2008), with all ownership and county-level attributes removed. To ensure these field polygons were consistent with recent land use, the 2009 Cropland Data Layer (USDA-NASS, 2013) was examined for all fields larger than 16 ha. For those fields with multiple cover types, 2009 National Agricultural Imagery Program (NAIP) aerial photography was used as a basis to manually edit field boundaries. A field was considered to have multiple cover types and was edited if the dominant cover occupied <75% of the field, as indicated by the 2009 Cropland Data Layer. Updated field boundaries were then overlaid with data from USDA-National Agricultural Statistics Service (2013) Cropland Data Layer for 2000 – 2014, and each field was classified to represent crop rotations and land cover using the most recent six-year (2009-2014) sequence of land cover. Six-year land-cover strings (e.g., corn-corn-soybean-corn-soybean-corn) generated for each field were classified to represent major crop rotations, which were dominantly comprised of corn (Zea mays L.) and soybean (Glycine max (L.) Merr) annual row crops. The database does not include high-resolution digital elevation models (DEMs) derived from LiDAR (light detection and ranging) survey data, although these are needed by the Agricultural Conservation Planning Framework Toolkit and must be obtained independently. Database is scheduled to become available on October 1, 2015. Resources in this dataset:Resource Title: Land Use and Soils data, viewing and downloading page. File Name: Web Page, url: https://www.nrrig.mwa.ars.usda.gov/st40_huc/dwnldACPF.html Recent land use, field boundary, and soil survey information for individual HUC12 watersheds in Iowa, Illinois, and southern Minnesota. With this land use viewer web page, users may navigate to individual HUC12 watersheds, view land-use maps, and download land use and soils data that can be directly used as input data for the ACPF toolbox. Before developing information on conservation priorities and opportunities using the ACPF toolbox, users will need to obtain elevation data for their watershed, which is usually available from your state government.

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of Assateague Island, located in Maryland and Virginia, changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future vulnerability of wetland systems. Making these assessments will rely on data extracted from current and historical resources such as maps, aerial photographs, satellite imagery, and lidar elevation data, which document physical changes over time. This USGS Data Series publication includes several open-ocean shorelines, back-island shorelines, back-island shoreline points, sand area polygons, and sand lines for Assateague Island that were extracted from orthoimagery (orthoaerial photography) dated from April 12, 1989 to September 5, 2013. This dataset consists of points that were digitized at the intersection of the back-island shoreline and a set of transects spaced at 20 meter (m) intervals. The transects, asis_transects_ln_20m_utm18.shp, are included in this Data Series publication and can be accessed via the Data Download page. Only one back-island shoreline/transect intersection point was digitized per transect. Orthoimagery of Assateague Island were acquired in digital format from U.S. Department of Agriculture (USDA), U.S. Geological Survey (USGS) and Virginia Geographic Information Network (VGIN) courtesy of the Commonwealth of Virginia. The following list provides additional details about the orthoimagery used. The back-island shoreline points for all dates have been compiled into one dataset (shapefile) named asis_bshrln_1989_2013_transect_guided.shp. The orthoimage date for each line is included in the shapefile attribute table Date_ field. Date State Type Source Resolution 198904129(1) MD DOQQ USGS 1 meter (m) 19940320 VA DOQQ USGS 1 m 20041105 VA NAIP USDA 2 m 20050608 VA NAIP USDA 2 m 20050615 MD NAIP USDA 1 m 20060528 VA NAIP USDA 2 m 20060701 MD NAIP USDA 2 m 20070622 MD NAIP USDA 1 m 20080525 VA NAIP USDA 1 m 20090626 MD NAIP USDA 1 m 20090726 VA NAIP USDA 1 m 20090807 VA NAIP USDA 1 m 20110530 VA NAIP USDA 1 m 20110602 MD NAIP USDA 1 m 20120512 VA NAIP USDA 1 m 20130315 VA VBMP VGIN(2) 1 m(3) 20130905 MD NAIP USDA 1 m DOQQ Digital Orthophoto Quarter Quads NAIP National Agriculture Imagery Program VBMP Virginia Base Mapping Program (1)Color Infrared orthoimagery; all others are natural color. (2)Imagery courtesy of the Commonwealth of Virginia. (3)Resampled from 1-foot resolution imagery.

The Pléiades ESA archive is a dataset of Pléiades-1A and 1B products that ESA collected over the years. The dataset regularly grows as ESA collects new Pléiades products. Pléiades Primary and Ortho products can be available in the following modes: Panchromatic image at 0.5 m resolution Pansharpened colour image at 0.5 m resolution Multispectral image in 4 spectral bands at 2 m resolution Bundle (0.5 m panchromatic image + 2 m multispectral image) Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided.

Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm