Random Forest Maps Desertification Hotspots in Southeastern Iran, With About 88,678 Hectares of Expansion Projected by 2040
A study published November 14 in Scientific Reports used machine learning to predict desertification hotspots in southeastern Iran. The authors, Farahi and Boali, worked within the IMDPA framework, combining remote sensing data with Google Earth Engine, and compared six machine learning algorithms using AUC, Kappa, TSS, F1, and Deviance.
Random forest performed best, with an AUC of 0.94, Kappa of 0.72, TSS of 0.82, and F1 of 0.86. Hotspot cities identified include Zahedan, Khash, Fanuj, Nikshahr, Chabahar, and Saravan.
Land use for 2040 was simulated with a Markov chain under the SSP2-4.5 and SSP5-8.5 scenarios. The results project that desertified land will expand by about 88,678 hectares by 2040.
Source: Scientific
Published by GSM · USA (original Chinese edition)
Photo: 图：NASA Terra 卫星 2024 年 4 月拍摄的伊朗 Lut 荒漠，可见风蚀雅丹地貌与沙丘。来源：NASA Earth Observatory (Wanmei Liang)，Wikimedia Commons，Public domain。 / Photo: The Lut Desert in Iran photographed by NASA Terra satellite in April 2024, showing wind-eroded yardangs and sand dunes. Source: NASA Earth Observatory (Wanmei Liang), Wikimedia Commons, Public domain.
