{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T14:06:05Z","timestamp":1782482765090,"version":"3.54.5"},"reference-count":30,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T00:00:00Z","timestamp":1618531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Research and Demonstration of Key Technology for Water Resources Protection and Utilization and Ecological Reconstruction in Coal Mining area of Northern Shaanxi","award":["2018SMHKJ-A-J-03"],"award-info":[{"award-number":["2018SMHKJ-A-J-03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In order to effectively control the damage caused by surface cracks to a geological environment, we need to find a convenient, efficient, and accurate method to obtain crack information. The existing crack extraction methods based on unmanned air vehicle (UAV) images inevitably have some erroneous pixels because of the complexity of background information. At the same time, there are few researches on crack feature information. In view of this, this article proposes a surface crack extraction method based on machine learning of UAV images, the data preprocessing steps, and the content and calculation methods for crack feature information: length, width, direction, location, fractal dimension, number, crack rate, and dispersion rate. The results show that the method in this article can effectively avoid the interference by vegetation and soil crust. By introducing the concept of dispersion rate, the method combining crack rate and dispersion rate can describe the distribution characteristics of regional cracks more clearly. Compared to field survey data, the calculation result of the crack feature information in this article is close to the true value, which proves that this is a reliable method for obtaining quantitative crack feature information.<\/jats:p>","DOI":"10.3390\/rs13081534","type":"journal-article","created":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T06:35:53Z","timestamp":1618814153000},"page":"1534","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["The Surface Crack Extraction Method Based on Machine Learning of Image and Quantitative Feature Information Acquisition Method"],"prefix":"10.3390","volume":"13","author":[{"given":"Fan","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6225-6787","authenticated-orcid":false,"given":"Zhenqi","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaokun","family":"Fu","sequence":"additional","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zewei","family":"Feng","sequence":"additional","affiliation":[{"name":"Shenmu Hanjiawan Coal Mining Company Ltd., Shannxi Coal and Chemical Industry Group, Yulin 719000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingbo","family":"Bai","sequence":"additional","affiliation":[{"name":"Shenmu Hanjiawan Coal Mining Company Ltd., Shannxi Coal and Chemical Industry Group, Yulin 719000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.jseaes.2016.01.003","article-title":"Holocene intracontinental deformation of the northern north china plain: Evidence of tectonic ground fissures","volume":"119","author":"Xu","year":"2016","journal-title":"J. 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