{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T14:06:08Z","timestamp":1782482768434,"version":"3.54.5"},"reference-count":50,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801380"],"award-info":[{"award-number":["41801380"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"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>Widespread ground fissures caused by coal mining subsidence are a main cause of ecological destruction in coal mining areas, and the rapid monitoring of ground fissures is essential for ecological restoration. Traditional fissure monitoring technologies are time consuming and laborious. Therefore, we developed a method to automatically extract ground fissures from high-resolution UAV images. First, a multiscale Hessian-based enhancement filter was utilized to enhance the ground fissures in grayscale images. Then, a simple single-thresholding operation was applied to segment the enhanced image to generate a binary ground fissure map. Finally, incomplete path opening was performed to eliminate the noises in the fissure extraction results. We selected the N1212 working face of the Ningtiaota Coal Mine in Shenmu County, China, as the study area. The results indicated that the ranges of correctness, completeness, and the kappa coefficient of the extracted results were 66.23\u201379.00%, 69.03\u201373.22%, and 67.91\u201375.88%, respectively. Image resolution is the key factor for successful fissure detection; the method proposed in this paper can extract ground fissures with a width greater than one pixel (2.64 cm), and the detection ratio for fissures with a width greater than two pixels was over 87%. Our research has solved the problem of the rapid monitoring of ground fissures to a certain extent and can act as a valuable tool for ecological restoration in mining areas.<\/jats:p>","DOI":"10.3390\/rs14051071","type":"journal-article","created":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T22:35:00Z","timestamp":1645569300000},"page":"1071","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Automated Extraction of Ground Fissures Due to Coal Mining Subsidence Based on UAV Photogrammetry"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5262-6054","authenticated-orcid":false,"given":"Kun","family":"Yang","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":"Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusheng","family":"Liang","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"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9488-6652","authenticated-orcid":false,"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":"Dongzhu","family":"Yuan","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":"Jiaxin","family":"Guo","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"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7342-8513","authenticated-orcid":false,"given":"Gensheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221008, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Li","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"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,22]]},"reference":[{"key":"ref_1","unstructured":"IEA (2021). Key World Energy Statistics 2021, IEA."},{"key":"ref_2","first-page":"11","article-title":"Distribution characteristic and development rules of ground fissures due to coal mining in windy and sandy region","volume":"39","author":"Hu","year":"2014","journal-title":"J. China Coal Soc."},{"key":"ref_3","first-page":"597","article-title":"Effect of cracks on soil characteristics and crop growth in subsided coal mining areas","volume":"23","author":"Xu","year":"2015","journal-title":"Chin. J. Eco-Agric."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kong, J.L., Xian, T., Yang, J., Chen, L., and Yang, X.T. (2016, January 12\u201319). Monitoring soil moisture in a coal mining area with multi-phase Landsat images. Proceedings of the ISPRS\u2014International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Prague, Czech Republic.","DOI":"10.5194\/isprsarchives-XLI-B7-537-2016"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.scitotenv.2018.10.249","article-title":"Arbuscular mycorrhizal fungi alleviate root damage stress induced by simulated coal mining subsidence ground fissures","volume":"652","author":"Bi","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"107800","DOI":"10.1016\/j.ecolind.2021.107800","article-title":"Arbuscular mycorrhizal fungi alter root and foliar responses to fissure-induced root damage stress","volume":"127","author":"Zhang","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"114634","DOI":"10.1016\/j.geoderma.2020.114634","article-title":"Revealing soil erosion characteristics using deposited sediment sources in a complex small catchment in the wind-water erosion crisscross region of the Chinese Loess Plateau","volume":"379","author":"Zhang","year":"2020","journal-title":"Geoderma"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"105830","DOI":"10.1016\/j.catena.2021.105830","article-title":"Slow surface subsidence and its impact on shallow loess landslides in a coal mining area","volume":"209","author":"Yang","year":"2022","journal-title":"Catena"},{"key":"ref_9","first-page":"1442","article-title":"Characteristics of ground fissure development in high intensity mining area of shallow seam in Yushenfu coal field","volume":"40","author":"Fan","year":"2015","journal-title":"J. China Coal Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s12665-017-6452-9","article-title":"Analysis of developmental features and causes of the ground cracks induced by oversized working face mining in an aeolian sand area","volume":"76","author":"Li","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1007\/s10064-017-1108-2","article-title":"Formation and development mechanism of ground crack caused by coal mining: Effects of overlying key strata","volume":"78","author":"Zhou","year":"2019","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6297","DOI":"10.1007\/s10064-019-01532-z","article-title":"Effects of mining speed on the developmental features of mining-induced ground fissures","volume":"78","author":"Liu","year":"2019","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Fu, Y., Shang, J., Hu, Z., Li, P., Yang, K., Chen, C., Guo, J., and Yuan, D. (2021). Ground fracture development and surface fracture evolution in N00 method shallowly buried thick coal seam mining in an arid windy and sandy area: A case study of the Ningtiaota Mine (China). Energies, 14.","DOI":"10.3390\/en14227712"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2835","DOI":"10.1007\/s00603-018-1726-4","article-title":"Ground subsidence and surface cracks evolution from shallow-buried close-distance multi-seam mining: A case study in Bulianta Coal Mine","volume":"52","author":"Yang","year":"2019","journal-title":"Rock Mech. Rock Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.geomorph.2012.12.010","article-title":"Image-based mapping of surface fissures for the investigation of landslide dynamics","volume":"186","author":"Stumpf","year":"2013","journal-title":"Geomorphology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"108048","DOI":"10.1016\/j.measurement.2020.108048","article-title":"Streamlined bridge inspection system utilizing unmanned aerial vehicles (UAVs) and machine learning","volume":"164","author":"Perry","year":"2020","journal-title":"Measurement"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"042011","DOI":"10.1088\/1742-6596\/1168\/4\/042011","article-title":"Study on pavement defect detection based on image processing utilizing UAV","volume":"1168","author":"Zhang","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zollini, S., Alicandro, M., Dominici, D., Quaresima, R., and Giallonardo, M. (2020). UAV photogrammetry for concrete bridge inspection using object-based image analysis (OBIA). Remote Sens., 12.","DOI":"10.3390\/rs12193180"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Al-Rawabdeh, A., He, F.N., Moussa, A., El-Sheimy, N., and Habib, A. (2016). Using an unmanned aerial vehicle-based digital imaging system to derive a 3D point cloud for landslide scarp recognition. Remote Sens., 8.","DOI":"10.3390\/rs8020095"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bhowmick, S., Nagarajaiah, S., and Veeraraghavan, A. (2020). Vision and Deep Learning-Based Algorithms to Detect and Quantify Cracks on Concrete Surfaces from UAV Videos. Sensors, 20.","DOI":"10.3390\/s20216299"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, F., Hu, Z., Fu, Y., Yang, K., Wu, Q., and Feng, Z. (2020). A new identification method for surface cracks from UAV images based on machine learning in coal mining areas. Remote Sens., 12.","DOI":"10.3390\/rs12101571"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Jia, H., Wei, B., Liu, G., Zhang, R., Yu, B., and Wu, S. (2021). A semi-automatic method for extracting small ground fissures from loess areas using unmanned aerial vehicle images. Remote Sens., 13.","DOI":"10.3390\/rs13091784"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.isprsjprs.2021.08.005","article-title":"Identification of mining induced ground fissures using UAV and infrared thermal imager: Temperature variation and fissure evolution","volume":"180","author":"Zhao","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_25","first-page":"810","article-title":"Research advances in formation mechanism of ground crack due to coal mining subsidence in China","volume":"43","author":"Chen","year":"2018","journal-title":"J. China Coal Soc."},{"key":"ref_26","first-page":"43","article-title":"Analysis of mining damage in huge thick collapsible loess of western China","volume":"37","author":"Yu","year":"2008","journal-title":"J. China Univ. Min. Technol."},{"key":"ref_27","first-page":"59","article-title":"Analysis of effect of fissures caused by underground mining on ground movement and deformation","volume":"27","author":"Kang","year":"2008","journal-title":"Chin. J. Rock Mech. Eng."},{"key":"ref_28","first-page":"380","article-title":"Analysis of forming mechanism of collapsing ground fissure caused by mining","volume":"30","author":"Liu","year":"2013","journal-title":"J. Min. Saf. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"111666","DOI":"10.1016\/j.rse.2020.111666","article-title":"Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS","volume":"239","author":"Meinen","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge-detection","volume":"8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_31","first-page":"187","article-title":"Theory of edge detection","volume":"207","author":"Marr","year":"1980","journal-title":"Proc. R. Soc. Lond. Ser. B Biol. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"101623","DOI":"10.1016\/j.media.2019.101623","article-title":"Tensor-cut: A tensor-based graph-cut blood vessel segmentation method and its application to renal artery segmentation","volume":"60","author":"Wang","year":"2020","journal-title":"Med. Image Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2076","DOI":"10.1016\/j.patcog.2011.02.014","article-title":"A detailed investigation into low-level feature detection in spectrogram images","volume":"44","author":"Lampert","year":"2011","journal-title":"Pattern Recognit."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1007\/BFb0056195","article-title":"Multiscale vessel enhancement filtering","volume":"1496","author":"Frangi","year":"1998","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/S1361-8415(98)80009-1","article-title":"Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images","volume":"2","author":"Sato","year":"1998","journal-title":"Med. Image Anal."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s10851-005-4885-3","article-title":"Path openings and closings","volume":"22","author":"Heijmans","year":"2005","journal-title":"J. Math. Imaging Vis."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/j.imavis.2006.07.021","article-title":"Efficient complete and incomplete path openings and closings","volume":"25","author":"Talbot","year":"2007","journal-title":"Image Vis. Comput."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"105752","DOI":"10.1016\/j.cmpb.2020.105752","article-title":"Frangi based multi-scale level sets for retinal vascular segmentation","volume":"197","author":"Yang","year":"2020","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"107170","DOI":"10.1016\/j.measurement.2019.107170","article-title":"Structure-aware-based crack defect detection for multicrystalline solar cells","volume":"151","author":"Chen","year":"2020","journal-title":"Measurement"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Ghanta, S., Shamsabadi, S.S., Dy, J., Wang, M., and Birken, R. (2015, January 9\u201312). A Hessian-based methodology for automatic surface crack detection and classification from pavement images. Proceedings of the Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure, San Diego, CA, USA.","DOI":"10.1117\/12.2084370"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2327","DOI":"10.1109\/JSTARS.2013.2242846","article-title":"Airborne vehicle detection in dense urban areas using HoG features and disparity maps","volume":"6","author":"Tuermer","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2953","DOI":"10.1080\/01431160500057764","article-title":"Quality assessment for geo-spatial objects derived from remotely sensed data","volume":"26","author":"Zhan","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.ijrmms.2018.01.014","article-title":"Dynamic structural evolution of overlying strata during shallow coal seam longwall mining","volume":"103","author":"Wang","year":"2018","journal-title":"Int. J. Rock Mech. Min. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhao, Y., Abbott, A.L., Wynne, R.H., Hu, Z., Zou, Y., and Tian, S. (2019). Automated mapping of typical cropland strips in the North China Plain using small unmanned aircraft systems (sUAS) photogrammetry. Remote Sens., 11.","DOI":"10.3390\/rs11202343"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"112281","DOI":"10.1016\/j.rse.2020.112281","article-title":"Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery","volume":"255","author":"Wang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_46","first-page":"1","article-title":"Supraglacial rivers on the northwest Greenland Ice Sheet, Devon Ice Cap, and Barnes Ice Cap mapped using Sentinel-2 imagery","volume":"78","author":"Yang","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.ijmst.2015.05.006","article-title":"Mechanism of formation of sliding ground fissure in loess hilly areas caused by underground mining","volume":"25","author":"Liu","year":"2015","journal-title":"Int. J. Min. Sci. Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.enggeo.2016.12.021","article-title":"Numerical analysis of a large landslide induced by coal mining subsidence","volume":"217","author":"Nazem","year":"2017","journal-title":"Eng. Geol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1111\/mice.12297","article-title":"Automated pixel-level pavement crack detection on 3D asphalt surfaces using a deep-learning network","volume":"32","author":"Zhang","year":"2017","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1111\/mice.12440","article-title":"Encoder\u2013decoder network for pixel-level road crack detection in black-box images","volume":"34","author":"Bang","year":"2019","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1071\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:25:00Z","timestamp":1760135100000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1071"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,22]]},"references-count":50,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14051071"],"URL":"https:\/\/doi.org\/10.3390\/rs14051071","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,22]]}}}