Users can download the Cropland Data Layer (CDL) by year from theCropland Data Layer page hosted by the USDA’s National Agricultural Statistics Service web site.Cropland data can be accessed by year from 2008 to 2022. Each year has the data in raster format as a TIFF file. ...
Download: Download full-size image Fig. 2. Flowchart of the methodology. 2.2.1. Cropland data layer (CDL) The cropland data layer (CDL) dataset produced by the US Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) provides a detailed land use map of 132 land ...
Two validation experiments were also developed to examine the data at both the pixel and county level. Data generated from this research was published online in two repositories, while both applications allow users to download the entire dataset at no cost....
For example, to facilitate the management of agriculture, existing mapping produces such as the Cropland Data Layer7 (CDL) in the US, and the Agriculture and Agri-Food Canada’s Annual Crop Inventory8 (AAFC) have been widely used for crop yield estimation9, land use change detection10, and...
Cropland quality is essential for sustainable agriculture and food security. However, its evaluation has faced challenges due to inconsistent definitions,
It delivers admirable visualization features that serve as a pre-requisite to exploring the data before submitting it to any automated learning methods and allows access to the algorithm's results. It provides access to download automatically and processes Sentinel-2 data using the toolbox “sen2r...
A slab-ocean/sea-ice model, which prescribes horizontal ocean heat transport beneath the oceanic surface mixed layer to ensure realistic sea surface temperatures and ice distributions for the present climate, was linked to CAM to allow interaction between ocean, ice, and atmospheric temperatures. ...
Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of ...
such as differences in forest stages and local water supply conditions. We thereby present the uncertainty of the carbon sequestration map and its impact on our climate change mitigation estimation using the corresponding error rate layer (i.e., one standard deviation of spatial variability across 10...
as well as globally. The regional boundaries were aligned with national boundaries to enable comparison with national data. Only land pixels were considered; pixels labelled as permanent water and snow/ice in the Landsat ARD data quality layer were excluded. In each region, we selected five strata...