This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Minnesota 2010-2019
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Agricultural land use by field: Iowa 2010-2019
This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.
Data from: Responses to environmental variability by herbivorous insects and their natural enemies within a bioenergy crop, Miscanthus x giganteus
This dataset consists of field data (arthropods, nematodes and NDVI) collected over the course of 6 field excursions in 2015 and 2016 near TyTy, GA, in a field used for growing Miscanthus x giganteus. It also includes interpolated values of soil measurements collected in 2015 and meteorological data collected on an adjacent farm.
Ameriflux data: Goodwin Creek, Mississippi, 1980-2014
NAL Geospatial Catalog
This dataset links to a data download from the Daymet website. Data parameters are Latitude: 34.2547 Longitude: -89.8735 X & Y on Lambert Conformal Conic: 897941.75 -822030.73; Tile: 11206; Elevation: 91 meters; Years: 1980-2014. Archived and distributed through the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), the Daymet dataset for Goodwin Creek provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length.
SGP97 Electronically Scanned Thinned Array Radiometer Quick Look Images
NAL Geospatial Catalog
The core of the 1997 experiment involves the deployment of the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) for daily mapping of surface soil moisture over an area greater than 10,000 km2 and a period on the order of a month. The region selected for investigation is the best instrumented site for surface soil moisture, hydrology and meteorology in the world. This includes the USDA/ARS Little Washita Watershed, the USDA/ARS facility at El Reno, Oklahoma, the ARM/CART central facility, as well as the Oklahoma Mesonet. The region covered by the experiment is 34.5 to 37 North latitude and 97 to 99 West longitude. The aircraft mapping took place over the period 18 June to 18 July 1997. This dataset presents brightness temperature images from the Electronically Scanned Thinned Array Radiometer (L band passive microwave radiometer)
Grass-Cast Database - Data on aboveground net primary productivity (ANPP), climate data, NDVI, and cattle weight gain for Western U.S. rangelands
Grass-Cast - the grassland productivity forecast system - uses almost 40 years of historical data on weather and vegetation growth to provide estimates of growing season aboveground net primary production (ANPP). This Database details the data sets that are used for informing the projection model.
Data from: Genotypic characterization of the U.S. peanut core collection
This collection contains supplementary data for the manuscript "Genotypic characterization of the U.S. Peanut Core Collection", which describes genotyping results for the USDA peanut core collection. Supplementary files include: descriptive information about the genotyped accessions, SNP genotype calls in several formats, a phylogenetic tree calculated from the genotype data, Structure analysis, PCA analysis, and comparisons with the diploid progenitors.
Global Land Analysis & Discovery (GLAD) Global Cropland Extent
This study utilized 250m MODIS (MODerate Resolution Imaging Spectroradiometer) data to map global production cropland extent. A set of multi-year MODIS metrics incorporating four MODIS land bands, NDVI (Normalized Difference Vegetation Index) and thermal data was employed to depict cropland phenology over the period 2000-2008. The probability and discrete cropland/non-cropland data are available for download by MODIS tile at the full ~250m resolution or as global mosaics at ~1km resolution.
United States Drought Monitor
The U.S. Drought Monitor is a map released every Thursday, showing parts of the U.S. that are in drought. The map uses five classifications: abnormally dry (D0), showing areas that may be going into or are coming out of drought, and four levels of drought: moderate (D1), severe (D2), extreme (D3) and exceptional (D4).