{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T08:40:21Z","timestamp":1768812021702,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Major Special Project of High Resolution Earth Observation System","award":["80-Y50G19-9001-22\/23"],"award-info":[{"award-number":["80-Y50G19-9001-22\/23"]}]},{"name":"Major Special Project of High Resolution Earth Observation System","award":["U21A2014"],"award-info":[{"award-number":["U21A2014"]}]},{"name":"Major Special Project of High Resolution Earth Observation System","award":["2021YFE0106700"],"award-info":[{"award-number":["2021YFE0106700"]}]},{"name":"Key projects of the Joint Fund of the National Natural Science Foundation of China","award":["80-Y50G19-9001-22\/23"],"award-info":[{"award-number":["80-Y50G19-9001-22\/23"]}]},{"name":"Key projects of the Joint Fund of the National Natural Science Foundation of China","award":["U21A2014"],"award-info":[{"award-number":["U21A2014"]}]},{"name":"Key projects of the Joint Fund of the National Natural Science Foundation of China","award":["2021YFE0106700"],"award-info":[{"award-number":["2021YFE0106700"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["80-Y50G19-9001-22\/23"],"award-info":[{"award-number":["80-Y50G19-9001-22\/23"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["U21A2014"],"award-info":[{"award-number":["U21A2014"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFE0106700"],"award-info":[{"award-number":["2021YFE0106700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Soil erosion risk assessment enables the identification of areas requiring priority treatment and avoids wasting human and material resources. The factor scoring method used in existing studies has high subjectivity, and the method of expressing erosion risk according to the soil erosion intensity ignores the random nature of the occurrence of erosion; therefore, neither method accurately reflects the risk of soil erosion. In order to address this issue, this study proposes a soil erosion risk assessment method that integrates the outcome and the probability of occurrence of soil erosion by means of a probabilistic statistical model. Subsequently, experimental research is conducted in the Dali River Basin. On the basis of long time-series data, using mathematical statistics as a tool and drawing on the empirical frequency formula, the probabilistic statistical risk assessment model is combined with the Modified Universal Soil Loss Equation (RUSLE) model to account for the probability of regional soil erosion at different intensity levels in the long time-series, which is combined with the intensity of erosion to carry out soil erosion risk assessment. The results of our study show the following: (1) The central and southwestern regions of the Dali River Basin (DRB) present medium and high levels of soil erosion risk, with the proportion of low-risk areas increasing annually, accounting for 78.97% of the DRB in 2020, while extremely high-risk areas account for only 0.40% of the DRB. (2) The major components impacting soil erosion risk in the DRB, as revealed by the geodetector, are the normalized difference vegetation index (NDVI) and slope, where the interaction between the two dominated the spatial variation in soil erosion risk. (3) Comparing the soil erosion risk and its status in the coming years, the proposed assessment method based on the occurrence probability can reveal the future soil erosion risk better than the traditional assessment method.<\/jats:p>","DOI":"10.3390\/rs16183491","type":"journal-article","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T07:38:57Z","timestamp":1726817937000},"page":"3491","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Probabilistic Statistical Risk Assessment Method for Soil Erosion Using Remote Sensing Data: A Case Study of the Dali River Basin"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4302-3758","authenticated-orcid":false,"given":"Hao","family":"Zhao","sequence":"first","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhui","family":"Cheng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiwang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiqi","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengwei","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengqiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.catena.2017.01.024","article-title":"The role of soil surface properties on the particle size and carbon selectivity of interrill erosion in agricultural landscapes","volume":"153","author":"Koiter","year":"2017","journal-title":"CATENA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.still.2016.10.004","article-title":"Response of soil organic carbon and nitrogen stocks to soil erosion and land use types in the Loess hilly\u2013gully region of China","volume":"166","author":"Li","year":"2017","journal-title":"Soil Tillage Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"110976","DOI":"10.1016\/j.ecolind.2023.110976","article-title":"Spatiotemporal dynamics and driving factors of soil erosion in the Beiluo River Basin, Loess Plateau, China","volume":"155","author":"Wen","year":"2023","journal-title":"Ecol. 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