7 posts
A free, phone-friendly check for any farm: whether the rains have started, when they usually start, rain and heat for the next 10 days and how green the crops are. Examples from Lilongwe, Malawi, and Gazipur, Bangladesh.
Five new free tools for herders, district offices and cooperatives: a pasture and water bulletin, a water point check, a weekly fire count, flood water near a village today and a rainfall insurance check. Real answers from Kenya and South Sudan.
Two free tools for any district: is this season's rain and crop growth better or worse than usual, and where did it flood and how many people live there? Worked examples from Marsabit, Kenya, in 2022 and Feni, Bangladesh, in 2024.
An introduction to the TechnicalGIS climate time-series tools: five open datasets, how to draw an area on the map, worked examples from London, north Evia, Nairobi and Las Vegas, the processing limits and the terms for reusing every output.
Run a pixel-wise Mann-Kendall trend test and Theil-Sen slope on 24 years of MODIS NDVI in Python. Read MOD13A1 from the Microsoft Planetary Computer, mask it with the QA layer, aggregate to growing-season means, vectorise the tests with xarray.apply_ufunc (checked against pymannkendall), compare the seasonal and modified Mann-Kendall tests, control the false discovery rate across 229,229 pixels, and map greening and browning on China's Loess Plateau.
Map snow cover in Python with the Normalised Difference Snow Index (NDSI) from Sentinel-2 and the daily MODIS snow product on the Microsoft Planetary Computer: choosing the NDSI threshold, separating snow from cloud, snow-covered area through the winter of 2025–26 in the Cairngorms, and the snowline by elevation and aspect with the Copernicus DEM.
Map forest loss and deforestation in Python with the Hansen/UMD Global Forest Change v1.13 data: read the open tiles with no login, compute loss by year in hectares with correct pixel areas, compare Landsat and Sentinel-2 images before and after, and check the GFC loss year against Sentinel-2 NBR and MODIS burned area for central Rondônia, Brazil.