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@NASA's Global Food Supply & Agriculture Consortium est. 2017 Earth Data for Informed Ag Decisions (Tweets our own, for official NASA comms visit @NASAEarth)
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ALT The 2023 cultivation map shows how non-cultivated cropland was concentrated near the frontlines. The national map (A) is paired with examples from an area far from the front (B) and along the 2022–2023 frontline (C), where large areas of cropland were no longer being cultivated. At this mapping stage, fallow and abandoned fields were grouped together as non-cultivated cropland.
ALT The Crop Cycle Detection model analyzes changes in NDVI over time to identify individual growing seasons. In this example, the model detects three cropping cycles and estimates the start, peak, and end of each season. Orange points show the raw NDVI observations, while the blue line shows the processed, interpolated time series used by the model.
ALT Partners from diverse institutions gathered to formally establish ADAPT-Kenya. Following months of governance design, stakeholder alignment, and policy integration, ADAPT-Kenya is now positioned to deliver impact through crop monitoring, yield forecasting, insurance zone delineation, and disaster risk reduction.
ALT Partners from diverse institutions gathered to formally establish ADAPT-Kenya. Following months of governance design, stakeholder alignment, and policy integration, ADAPT-Kenya is now positioned to deliver impact through crop monitoring, yield forecasting, insurance zone delineation, and disaster risk reduction.
ALT This 2023 cultivation map shows how non-cultivated cropland was concentrated near the frontlines. The national map (A) is paired with examples from an area far from the front (B) and along the 2022–2023 frontline (C), where large areas of cropland were no longer being cultivated. At this mapping stage, fallow and abandoned fields were grouped together as non-cultivated cropland.
ALT Satellite images show how researchers distinguished cultivated, fallow, and abandoned cropland over the course of a growing season. Crop growth and harvest patterns identify actively cultivated fields, while signs of tillage can distinguish managed fallow land from abandoned fields with no visible farmer intervention. The red dots mark the locations being evaluated.
ALT These maps show tillage patterns during the study period. The left map indicates the percentage that a given field used low intensity tillage during the study period, while the right map indicates how frequently the given field changed from low- to high-intensity or high- to low-intensity tillage during the study period. From this, we can see that many of the fields in the SW corner of the study area (on the left map) remained high-intensity tillage during the entirety of the study. Likewise, we can see that a small number of fields (those in blue scattered across the study area in the left map) stayed low-intensity tillage during the entirety of the study period. And in the right map, the red fields changed with 100% frequency, meaning that those fields changed annually during the study period. Blue fields in this map did not change tillage intensity year to year.