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IMAP: Image Mapping & Analytics for Phenotyping

    A set of PYTHON programs to implement image processing of ground and aerial images by offering via graphical user interface (GUI) 1) plot-level metrics extraction through a series of algorithms for image conversion, band math, radiometric/geometric calibrations, segmentation, masking, adaptive region of interest (ROI), gridding, heatmap, and batch process, 2) GIS interface for GeoTIFF pixels to Lat/Lon, UTM conversion, read/write shapefile, Lat/Lon to ROI, grid to polygon, and 3) utility GUI functions for zooming, panning, rotation, images to video, file I/O, and histogram.

    Agricultural land use by field: Nebraska 2010-2020

      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: Illinois 2010-2020

        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: U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2018

          The primary greenhouse gas (GHG) sources for agriculture are nitrous oxide (N2O) emissions from cropped and grazed soils, methane (CH4) emissions from ruminant livestock production and rice cultivation, and CH4 and N2O emissions from managed livestock waste. This dataset contains zipped, tabulated data from the figures and tables, and maps of the entire report. Data are presented for Cropland Soils (N2O), Enteric Fermentation (CH4), Managed Livestock Waste (CH4 + N2O), Grazed Lands (CH4 + N2O), Rice Cultivation + Residue Burning (CH4 + N2O), Energy Use, Forests, Harvested Wood, Urban Trees, and Agricultural Soils.

          DRIFTSIM

            DRIFTSIM can be used to determine the effects of major drift-causing factors on the mean drift distances up to 656 feet from the release point for individual water droplets or classes of droplets.

            CALMIM

              The California Landfill Methane Inventory Model is a 1-dimensional soil gas transport and oxidation model that calculates annual landfill methane emissions based on the cover soil characteristics and annual climatic data for a given global location.

              WinDAM

                Prioritization of dam rehabilitation, improved flood warning systems, development of emergency action plans, and inform policy makers on zoning regulations.