{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T15:02:26Z","timestamp":1771340546847,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T00:00:00Z","timestamp":1681776000000},"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":["41771542"],"award-info":[{"award-number":["41771542"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["4202065"],"award-info":[{"award-number":["4202065"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"General Program of Beijing Natural Science Foundation","award":["41771542"],"award-info":[{"award-number":["41771542"]}]},{"name":"General Program of Beijing Natural Science Foundation","award":["4202065"],"award-info":[{"award-number":["4202065"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Particle size distribution is an important characteristic of reclaimed soil in arid and semi-arid mining areas in western China, which is important in the ecological environment protection and control of the Yellow River Basin. Large-scale coal resource mining disturbances have caused serious damage to the fragile ecological environment. The timely and accurate dynamic monitoring of mining area topsoil information has practical significance for ecological restoration and management evaluation. Investigating Wuhai City in the Inner Mongolia Autonomous Region of China, this study uses Landsat8 OLI multispectral images and measured soil sample particle size data to analyze soil spectral characteristics and establish a particle size content prediction model to retrieve the particle size distribution in the study area. The experimental results and analysis demonstrate that: (1) the 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum Vector version) atmospheric correction model is more accurate than the FLAASH (Fast Line-of-sight Atmospheric Analysis of Hypercubes) model in arid and semi-arid areas with undulating terrain; (2) 0\u201340 cm is the optimum soil thickness for modeling and predicting particle size content in this study; and (3) the multi-band prediction model is more precise than the single-band prediction model. The multi-band model\u2019s sequence of advantages and disadvantages is SVM (Support Vector Machine) &gt; MLR (Multiple Linear Regression) &gt; PLSR (Partial Least Squares Regression). Among them, the 6SV-SVM model has the highest precision, and the prediction precision R2 of the 3 particle sizes\u2019 contents is above 0.95, which can effectively predict the soil particle-size distribution and provide effective data to support topsoil quality change monitoring in the mine land reclamation area.<\/jats:p>","DOI":"10.3390\/rs15082137","type":"journal-article","created":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T01:09:22Z","timestamp":1681866562000},"page":"2137","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Multispectral Remote Sensing Monitoring of Soil Particle-Size Distribution in Arid and Semi-Arid Mining Areas in the Middle and Upper Reaches of the Yellow River Basin: A Case Study of Wuhai City, Inner Mongolia Autonomous Region"],"prefix":"10.3390","volume":"15","author":[{"given":"Quanzhi","family":"Li","sequence":"first","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6225-6787","authenticated-orcid":false,"given":"Zhenqi","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"},{"name":"School of Environment Science & Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deyun","family":"Song","sequence":"additional","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yusheng","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Geosciences & Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105681","DOI":"10.1016\/j.still.2023.105681","article-title":"Integration of Sentinel-1\/2 and topographic attributes to predict the spatial distribution of soil texture fractions in some agricultural soils of western Iran","volume":"229","author":"Azizi","year":"2023","journal-title":"Soil Tillage Res."},{"key":"ref_2","first-page":"1355","article-title":"Technological difficulties and future directions of ecological reconstruction in open pit coal mine of the arid and semi-arid areas of Western China","volume":"46","author":"Bi","year":"2021","journal-title":"J. China Coal Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jclepro.2022.132602","article-title":"Spatio-temporal evolution and optimization analysis of ecosystem service value-A case study of coal resource-based city group in Shandong, China","volume":"363","author":"Han","year":"2022","journal-title":"J. Clean Prod."},{"key":"ref_4","first-page":"2","article-title":"Main problems in ecological restoration of mines and their solutions","volume":"47","author":"Hu","year":"2021","journal-title":"China Coal"},{"key":"ref_5","first-page":"438","article-title":"Principle and technology of coordinated control of eco-environment of mining areas and river sediments in Yellow River watershed","volume":"47","author":"Hu","year":"2022","journal-title":"J. China Coal Soc."},{"key":"ref_6","first-page":"1","article-title":"Speech at the symposium on ecological protection and high-quality development in the Yellow River basin","volume":"39","author":"Xi","year":"2019","journal-title":"Water Conserv. Constr. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"104190","DOI":"10.1016\/j.catena.2019.104190","article-title":"Predicting particle-size distribution using thermal infrared spectroscopy from reclaimed mine land in the semi-arid grassland of North China","volume":"183","author":"Bao","year":"2019","journal-title":"Catena"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.ecolind.2019.04.015","article-title":"Evaluation of reclamation success in an open-pit coal mine using integrated soil physical, chemical and biological quality indicators","volume":"103","author":"Carmona","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1029\/JB089iB07p06329","article-title":"Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications","volume":"89","author":"Clark","year":"1984","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2411","DOI":"10.1080\/01431160600554363","article-title":"Development of topsoil grain size index for monitoring desertification in arid land using remote sensing","volume":"27","author":"Xiao","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"S38","DOI":"10.1016\/j.rse.2008.09.019","article-title":"Using Imaging Spectroscopy to study soil properties","volume":"113","author":"Chabrillat","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Fongaro, C.T., Dematt\u00ea, J.A.M., Rizzo, R., Lucas Safanelli, J., Mendes, W.D., Dotto, A.C., Vicente, L.E., Franceschini, M.H.D., and Ustin, S.L. (2018). Improvement of Clay and Sand Quantification Based on a Novel Approach with a Focus on Multispectral Satellite Images. Remote Sens., 10.","DOI":"10.3390\/rs10101555"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.isprsjprs.2022.09.013","article-title":"Towards spatially continuous mapping of soil organic carbon in croplands using multitemporal Sentinel-2 remote sensing","volume":"193","author":"Shi","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"112914","DOI":"10.1016\/j.rse.2022.112914","article-title":"Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing","volume":"271","author":"Wang","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"640","DOI":"10.2136\/sssaj2002.6400a","article-title":"Mid-infrared and near-infrared diffuse reflectance spectroscopy for soil carbon measurement","volume":"66","author":"McCarty","year":"2002","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"186","DOI":"10.2136\/sssaj2007.0028","article-title":"Mapping soil organic carbon concentration for multiple fields with image similarity analysis","volume":"72","author":"Chen","year":"2008","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1111\/j.1365-2389.2010.01301.x","article-title":"Soil properties prediction of western Mediterranean islands with similar climatic environments by means of mid-infrared diffuse reflectance spectroscopy","volume":"61","author":"Pucci","year":"2010","journal-title":"Eur. J. Soil Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.isprsjprs.2022.01.018","article-title":"Airborne imaging spectroscopy for assessing land-use effect on soil quality in drylands","volume":"186","author":"Levi","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"113182","DOI":"10.1016\/j.rse.2022.113182","article-title":"Universal quadratic soil spectral reflectance line and its deviation patterns\u2019 relationships with chemical and textural properties: A global data base analysis","volume":"280","author":"Shoshany","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1574","DOI":"10.1007\/s12517-022-10847-3","article-title":"Spatial prediction of soil particle size distribution in arid agricultural lands in central Iran","volume":"15","author":"Zolfaghari","year":"2022","journal-title":"Arab. J. Geosci."},{"key":"ref_21","first-page":"485","article-title":"Improving Soil Texture Digital Mapping Using Landsat 8 Satellite Imageries in Calcareous Soils of Southern Iran","volume":"25","author":"Shirazi","year":"2023","journal-title":"J. Agric. Sci. Technol."},{"key":"ref_22","first-page":"886","article-title":"Retrieval of Soil Organic Carbon in Cinnamon Mining Belt Subsidence Area Based on OLI and 6SV","volume":"39","author":"Zhao","year":"2019","journal-title":"Spectrosc. Spect. Anal."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.geoderma.2006.03.026","article-title":"Mid- and near-infrared spectroscopic assessment of soil compositional parameters and structural indices in two Ferralsols","volume":"136","author":"Madari","year":"2006","journal-title":"Geoderma"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1080\/00380768.2013.802643","article-title":"Spatial estimation of surface soil texture using remote sensing data","volume":"59","author":"Liao","year":"2013","journal-title":"Soil Sci. Plant Nutr."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"99","DOI":"10.5433\/1679-0359.2019v40n1p99","article-title":"VIS-NIR spectral reflectance for discretization of soils with high sand content","volume":"40","author":"Pereira","year":"2019","journal-title":"Semin. Ci\u00eancias Agr\u00e1rias"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1002\/ldr.3250","article-title":"Soil organic matter and texture estimation from visible\u2013near infrared\u2013shortwave infrared spectra in areas of land cover changes using correlated component regression","volume":"30","author":"Vlassova","year":"2019","journal-title":"Land Degrad. Dev."},{"key":"ref_27","unstructured":"Cooley, T., Anderson, G.P., Felde, G.W., Hoke, M.L., Ratkowski, A.J., Chetwynd, J.H., Gardner, J.A., Adler-Golden, S.M., Matthew, M.W., and Berk, A. (2002, January 24\u201328). FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toronto, ON, Canada."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.rse.2017.03.013","article-title":"Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances","volume":"194","author":"Houborg","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Pereira, P., Brevik, E.C., Mu\u00f1oz-Rojas, M., and Miller, B.A. (2017). Soil Mapping and Process Modeling for Sustainable Land Use Management, Elsevier.","DOI":"10.1016\/B978-0-12-805200-6.00002-5"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.chemolab.2009.04.005","article-title":"The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis","volume":"97","author":"Janik","year":"2009","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.geoderma.2009.12.025","article-title":"Using data mining to model and interpret soil diffuse reflectance spectra","volume":"158","author":"Rossel","year":"2010","journal-title":"Geoderma"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2015.09.0131","article-title":"Modeling Soil Processes: Review, Key Challenges, and New Perspectives","volume":"15","author":"Vereecken","year":"2016","journal-title":"Vadose Zone J."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhang, F., Hu, Z.Q., Fu, Y.K., Yang, K., Wu, Q.Y., and Feng, Z.W. (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_34","doi-asserted-by":"crossref","unstructured":"Zheng, G., Ryu, D., Jiao, C., Xie, X., Cui, X., and Shang, G. (2019). Visible and Near-Infrared Reflectance Spectroscopy Analysis of a Coastal Soil Chronosequence. Remote Sens., 11.","DOI":"10.3390\/rs11202336"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"105684","DOI":"10.1016\/j.still.2023.105684","article-title":"Predicting key soil properties from Vis-NIR spectra by applying dual-wavelength indices transformations and stacking machine learning approaches","volume":"229","author":"Tavakoli","year":"2023","journal-title":"Soil Tillage Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"39","DOI":"10.21046\/2070-7401-2021-18-2-39-50","article-title":"Design of satellite sensing data classification algorithm based on machine learning using the example of granulometric composition of soils in agricultural landscapes of Western Siberia","volume":"18","author":"Chursin","year":"2021","journal-title":"Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosm."},{"key":"ref_37","unstructured":"Zhang, Y., and Zhang, L. (2012). Machine Learning Theory and Algorithms, Science Press."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.geoderma.2007.12.009","article-title":"Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils","volume":"144","author":"Stevens","year":"2008","journal-title":"Geoderma"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0273-1177(95)00658-2","article-title":"Ground surface features of the Taklimakan Desert","volume":"17","author":"Ishiyama","year":"1996","journal-title":"Adv. Space Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1016\/j.rse.2007.06.014","article-title":"Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements","volume":"112","author":"Lagacherie","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"116103","DOI":"10.1016\/j.geoderma.2022.116103","article-title":"Soil moisture effects on predictive VNIR and MIR modeling of soil organic carbon and clay content","volume":"427","author":"Seidel","year":"2022","journal-title":"Geoderma"},{"key":"ref_42","first-page":"25","article-title":"Study on some characteristics of evaporation of sand dune and evapotranspiration of grassland in Mu Us desert","volume":"3","author":"Li","year":"2000","journal-title":"J. Hydraul. Eng."},{"key":"ref_43","unstructured":"Zhang, L. (2018). Research on Reservoir Water Depth Inversion and Water Area Extraction Based on Multi-Band Remote Sensing. [Master\u2019s Thesis, Inner Mongolia Agricultural University]."},{"key":"ref_44","unstructured":"Xiong, Y., and Li, Q.K. (1986). China Soil, Science Press. [2nd ed.]."},{"key":"ref_45","unstructured":"(2022, May 05). USGS, Available online: https:\/\/earthexplorer.usgs.gov\/."},{"key":"ref_46","unstructured":"Li, M., Han, D., and Wang, X. (2006). Spectral Analysis Techniques and Their Applications, Science Press."},{"key":"ref_47","first-page":"309","article-title":"Monitoring vegetation systems in the Great Plains with ERTS","volume":"351","author":"Rouse","year":"1974","journal-title":"NASA Spec. Publ."},{"key":"ref_48","first-page":"675","article-title":"Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An overview","volume":"35","author":"Tanre","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary analysis of the performance of the Landsat 8\/OLI land surface reflectance product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_50","unstructured":"(2022, November 05). CSDN. Available online: https:\/\/blog.csdn.net\/gordon3000\/article\/details\/102911626."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"120","DOI":"10.2136\/sssaj1986.03615995005000010023x","article-title":"Simultaneous Determination of Moisture, Organic Carbon, and Total Nitrogen by Near Infrared Reflectance Spectrophotometry","volume":"50","author":"Dalal","year":"1986","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_52","unstructured":"Wold, S. (1983). Lecture Notes in Mathematics, Springer."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Hapke, B. (1993). Theory of Reflectance and Emittance Spectroscopy, Cambridge University Press.","DOI":"10.1017\/CBO9780511524998"},{"key":"ref_54","first-page":"3","article-title":"Spectroscopy of rocks and minerals and principles of spectroscopy","volume":"3","author":"Clark","year":"1999","journal-title":"Man. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2137\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:18:28Z","timestamp":1760123908000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2137"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,18]]},"references-count":54,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082137"],"URL":"https:\/\/doi.org\/10.3390\/rs15082137","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,18]]}}}