VegScape https://nassgeodata.gmu.edu/VegScape/ delivers interactive vegetation indices so that web users can explore, visualize, query, and disseminate current vegetative cover maps and data without the need for specialized expertise, software, or high end computers. New satellite-based data are loaded on a weekly basis during the growing season. One can compare year-to-year change since the year 2000, compare conditions at a given times to mean, median and ratio vegetative cover, and can overlay a crop mask to help identify crop land versus non-crop land, among many functions. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), and mean, median, and ratio comparisons to prior years have proven useful for assessing crop condition and identifying the land area impacted by floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. The National Aeronautics Space Administration's MODIS satellite is used for this project and provides imaging at 250 meter (15 acres) per pixel resolution. Additionally, the data can be directly exported to Google Earth for mashups or delivered to other applications via web services.
NASS Data Visualization provides a dynamic web query interface supporting searches by Commodity (e.g. Cotton, Corn, Farms & Land, Grapefruit, Hogs, Oranges, Soybeans, Wheat), Statistic type (automatically refreshed based upon choice of Commodity - e.g. Inventory, Head, Acres Planted, Acres Harvested, Production, Yield) to generate chart, table, and map visualizations by year (2001-2016), as well as a link to download the resulting data in CSV format compatible for updating databases and spreadsheets.
The United States Department of Agriculture National Agricultural Library Geospatial Data catalog contains geographic location-based agricultural research data, imagery, research location context, and more. Users can search records representing a variety of datasets, maps and graphics, aerial and phenocam images, and other services.
The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by the USDA National Agricultural Statistics Service (NASS). It allows you to customize your query by commodity, location, or time period. You can then visualize the data on a map, manipulate and export the results as an output file compatible for updating databases and spreadsheets, or save a link for future use. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. County level data are also available via Quick Stats.
The USDA-ARS Southwest Watershed Research Center (SWRC) operates the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona as an outdoor laboratory for studying semiarid rangeland hydrologic, ecosystem, climate, and erosion processes.
Since its establishment in 1953, the SWRC in Tucson, Arizona, has collected, processed, managed,…
This record contains C++ code as well as a Docker release for performing curve skeletonization of objects, which have a voxel representation. Curve skeletonization is used to convert a three-dimensional digital object or shape to locally one-dimensional parts; in other words, to reduce the shape information to a more easily processed form. Our algorithm does so for objects whose surface may be noisy, which is a common occurrence when working with data acquired under real-world conditions. This record also includes a test dataset for verifying that the code is running correctly and as examples of how to convert from different file types.
This is an identification key to genera for seeds and fruits of the legume family. The coverage is world wide, and for each genus there are descriptions of the seeds and fruits, distribution data, and images. The interactive software system INTKEY is used for accessing the data and images. The key can be used for identifying to genus unknown legume samples or for querying the data and images for legume genera, and is designed for seed analysts, technicians, port inspectors, weed scientists, ecologists, botanists, and researchers who need to identify isolated legume fruits and seeds.
This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into State-wide extents, and adding a State-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format.
The Digital General Soil Map of the United States or STATSGO2 is a broad-based inventory of soils and non-soil areas that occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped of 1:250,000 in the continental U.S., Hawaii, Puerto Rico, and the Virgin Islands and 1:1,000,000 in Alaska. The level of mapping is designed for broad planning and management uses covering state, regional, and multi-state areas. The U.S. General Soil Map is comprised of general soil association units and is maintained and distributed as a spatial and tabular dataset.