Starting in 2009, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology …
Note: This dataset is not yet peer-reviewed. Please see the GitHub README associated with this model for more information. This image collection provides per-pixel probability that the underlying area is occupied by cocoa. The probability estimates are provided at 10 meter resolution, and have been …
The European Space Agency (ESA) WorldCereal 10 m 2021 product suite consists of global-scale annual and seasonal crop maps and their related confidence. They were generated as part of the ESA-WorldCereal project. More information on the content of these products and the methodology used to …
The European Space Agency (ESA) WorldCereal classification system aims for product generation within one month after the end of a particular growing season. Due to the dynamic nature of these growing seasons across the globe, a global stratification into Agro-Ecological Zones (AEZ) was performed based …
The European Space Agency (ESA) WorldCereal Active Cropland 10 m 2021 product suite contains global-scale seasonal active cropland markers. They were generated as part of the ESA-WorldCereal project. The active cropland products indicate whether or not a pixel identified as temporary crops has been actively …
European crop type map based on Sentinel-1 and LUCAS Copernicus 2018 in-situ observations for 2018; and one based on Sentinel-2 and LUCAS Copernicus 2022 for 2022. Capitalizing on the unique LUCAS 2018 Copernicus in-situ survey, the 2018 dataset is the first continental crop type map …
The GFSAD is a NASA-funded project to provide high-resolution global cropland data and their water use that contributes towards global food security in the twenty-first century. The GFSAD products are derived through multi-sensor remote sensing data (e.g., Landsat, MODIS, AVHRR), secondary data, and field-plot data …
This dataset contains drought indices derived from the 4-km daily Gridded Surface Meteorological (GRIDMET) dataset. The drought indices provided include the standardized precipitation index (SPI), the evaporative drought demand index (EDDI), the standardized precipitation evapotranspiration index (SPEI), the Palmer Drought Severity Index (PDSI) and Palmer …
The dataset is a 10m global industrial and smallholder oil palm map for 2019. It covers areas where oil palm plantations were detected. The classified images are the output of a convolutional neural network based on Sentinel-1 and Sentinel-2 half-year composites. See article for additional …
Note: This dataset is not yet peer-reviewed. Please see the GitHub README associated with this model for more information. This image collection provides per-pixel probability that the underlying area is occupied by palm. The probability estimates are provided at 10 meter resolution, and have been …
Note: This dataset is not yet peer-reviewed. Please see the GitHub README associated with this model for more information. This image collection provides per-pixel probability that the underlying area is occupied by rubber trees. The probability estimates are provided at 10 meter resolution, and have …
The Cropland Data Layer (CDL) is a crop-specific land cover data layer created annually for the continental United States using moderate resolution satellite imagery and extensive agricultural ground truth. The CDL is created by the USDA, National Agricultural Statistics Service (NASS), Research and Development Division, …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["This webpage provides access to a variety of datasets related to global crop mapping and monitoring."],["Datasets include information on crop type, extent, and agricultural practices."],["Data is derived from various sources, including satellite imagery and ground truth observations."],["Several datasets offer global coverage, while others focus on specific regions like the US, Canada, and Europe."],["These datasets can be used for agricultural research, land management, and food security analysis."]]],["Agricultural agencies and projects are creating datasets for crop mapping and analysis. Actions include generating annual crop maps, like Canada's AAFC using a Decision Tree methodology, and ESA's WorldCereal project producing global-scale crop maps. Other datasets provide oil palm plantation maps, cropland extent data, and drought indices. Recent models also estimate cocoa, palm, and rubber tree probabilities at a per-pixel level, with some data focused on specific regions like Europe, the US, or Canada, while others are global.\n"]]
