{"title":"使用谷歌Earth Engine进行可扩展和自动化的土壤侵蚀评估：集成RUSLE和SDR进行基于云的建模","authors":"Oumayma Bassairate, Mohamed Chikhaoui, Mustapha Naimi, Chakir Achahboun","doi":"10.1007/s12517-025-12307-0","DOIUrl":null,"url":null,"abstract":"<div><p>This study presents a cloud-based framework for the large-scale assessment of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) and the sediment delivery ratio (SDR) in Google Earth Engine (GEE). The Soil and Water Conservation (SWC) Observatory platform automates the mapping of erosion and sediment yield, which has been validated in Moroccan watersheds (<i>R</i><sup>2</sup> = 0.89). The GEE implementation outperforms conventional GIS methods through enhanced computational efficiency and global dataset integration. Adaptable RUSLE parameters enable worldwide application across diverse climates. The SWC Observatory facilitates real-time scenario analysis for informed land management decisions. This approach provides open-access tools for erosion prediction, particularly valuable in data-scarce regions. The framework advances sustainable land management through replicable, precise assessment methodologies.</p></div>","PeriodicalId":476,"journal":{"name":"Arabian Journal of Geosciences","volume":"18 9","pages":""},"PeriodicalIF":1.8270,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scalable and automated soil erosion assessment using Google Earth Engine: integrating RUSLE and SDR for cloud-based modeling\",\"authors\":\"Oumayma Bassairate, Mohamed Chikhaoui, Mustapha Naimi, Chakir Achahboun\",\"doi\":\"10.1007/s12517-025-12307-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study presents a cloud-based framework for the large-scale assessment of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) and the sediment delivery ratio (SDR) in Google Earth Engine (GEE). The Soil and Water Conservation (SWC) Observatory platform automates the mapping of erosion and sediment yield, which has been validated in Moroccan watersheds (<i>R</i><sup>2</sup> = 0.89). The GEE implementation outperforms conventional GIS methods through enhanced computational efficiency and global dataset integration. Adaptable RUSLE parameters enable worldwide application across diverse climates. The SWC Observatory facilitates real-time scenario analysis for informed land management decisions. This approach provides open-access tools for erosion prediction, particularly valuable in data-scarce regions. The framework advances sustainable land management through replicable, precise assessment methodologies.</p></div>\",\"PeriodicalId\":476,\"journal\":{\"name\":\"Arabian Journal of Geosciences\",\"volume\":\"18 9\",\"pages\":\"\"},\"PeriodicalIF\":1.8270,\"publicationDate\":\"2025-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Arabian Journal of Geosciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12517-025-12307-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arabian Journal of Geosciences","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12517-025-12307-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Scalable and automated soil erosion assessment using Google Earth Engine: integrating RUSLE and SDR for cloud-based modeling
This study presents a cloud-based framework for the large-scale assessment of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) and the sediment delivery ratio (SDR) in Google Earth Engine (GEE). The Soil and Water Conservation (SWC) Observatory platform automates the mapping of erosion and sediment yield, which has been validated in Moroccan watersheds (R2 = 0.89). The GEE implementation outperforms conventional GIS methods through enhanced computational efficiency and global dataset integration. Adaptable RUSLE parameters enable worldwide application across diverse climates. The SWC Observatory facilitates real-time scenario analysis for informed land management decisions. This approach provides open-access tools for erosion prediction, particularly valuable in data-scarce regions. The framework advances sustainable land management through replicable, precise assessment methodologies.
期刊介绍：
The Arabian Journal of Geosciences is the official journal of the Saudi Society for Geosciences and publishes peer-reviewed original and review articles on the entire range of Earth Science themes, focused on, but not limited to, those that have regional significance to the Middle East and the Euro-Mediterranean Zone.
Key topics therefore include; geology, hydrogeology, earth system science, petroleum sciences, geophysics, seismology and crustal structures, tectonics, sedimentology, palaeontology, metamorphic and igneous petrology, natural hazards, environmental sciences and sustainable development, geoarchaeology, geomorphology, paleo-environment studies, oceanography, atmospheric sciences, GIS and remote sensing, geodesy, mineralogy, volcanology, geochemistry and metallogenesis.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
