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When extracting tributaries and small water bodies based on remote sensing images, there are problems such as uncertain threshold selection, more edge voids, and extraction difficulties. The improved water body extraction method (Combination Normalized Difference Water Index), fuses Digital Elevation Model and remote sensing images. The river network is extracted from the Digital Elevation Model and the remote sensing image is normalized. After fusion, threshold comparison is performed, and the threshold of the river network location is used as the basis for connecting the broken water bodies, it is compared and verified with the normalized thresholds to achieve accurate identification and complete extraction of water bodies. Taking the water bodies in Xinyang City as an example, the overall accuracy of the confusion matrix was the highest, with an overall accuracy of 93.0% compared with the traditional index method. Combined with water bodies in Zhengzhou City for model validation, it has high applicability. Whether the water body is large or small, the extraction results are complete, with no voids or broken, and the accuracy is high.<\/jats:p>","DOI":"10.1038\/s41598-024-51346-7","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T11:02:36Z","timestamp":1704711756000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["A method for extracting small water bodies based on DEM and remote sensing images"],"prefix":"10.1038","volume":"14","author":[{"given":"Qingzhen","family":"Sun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinguang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,8]]},"reference":[{"key":"51346_CR1","first-page":"1461","volume":"66","author":"PS Frazier","year":"2000","unstructured":"Frazier, P. 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