{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T19:19:52Z","timestamp":1774898392929,"version":"3.50.1"},"reference-count":84,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T00:00:00Z","timestamp":1719532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Project of the Department of Ecology and Environment of Qinghai Province","award":["2021046279"],"award-info":[{"award-number":["2021046279"]}]},{"name":"Science and Technology Project of the Department of Ecology and Environment of Qinghai Province","award":["2022NSFSCO18"],"award-info":[{"award-number":["2022NSFSCO18"]}]},{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["2021046279"],"award-info":[{"award-number":["2021046279"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["2022NSFSCO18"],"award-info":[{"award-number":["2022NSFSCO18"]}],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The effective identification of reclaimed vegetation species is important for the subsequent management of ecological restoration projects in mining areas. Hyperspectral remote sensing has been used for identifying vegetation species. However, few studies have focused on mine-reclaimed vegetation. Even if there are studies in this field, the methods used by the researches are mainly traditional discriminant analyses. The environmental conditions of reclaimed mining areas lead to significant intraclass spectral differences in reclaimed vegetation, and there is uncertainty in the identification of reclaimed vegetation species using traditional classification models. In this study, in situ hyperspectral data were used to analyze the spectral variation in the reclaimed vegetation canopy in mine restoration areas and evaluate their potential in the identification of reclaimed vegetation species. We measured the canopy spectral reflectance of five vegetation species in the study area using the ASD FieldSpec 4. The spectral characteristics of vegetation canopy were analyzed by mathematically transforming the original spectra, including Savitzky\u2013Golay smoothing, first derivative, reciprocal logarithm, and continuum removal. In addition, we calculated indicators for identifying vegetation species using mathematically transformed hyperspectral data. The metrics were submitted to a feature selection procedure (recursive feature elimination) to optimize model performance and reduce its complexity. Different classification algorithms (regularized logistic regression, back propagation neural network, support vector machines with radial basis function kernel, and random forest) were constructed to explore optimal procedures for identifying reclaimed vegetation species based on the best feature metrics. The results showed that the separability between the spectra of reclaimed vegetation can be improved by applying different mathematical transformations to the spectra. The most important spectral metrics extracted by the recursive feature elimination (RFE) algorithm were related to the visible and near-infrared spectral regions, mainly in the vegetation pigments and water absorption bands. Among the four identification models, the random forest had the best recognition ability for reclaimed vegetation species, with an overall accuracy of 0.871. Our results provide a quantitative reference for the future exploration of reclaimed vegetation mapping using hyperspectral data.<\/jats:p>","DOI":"10.3390\/rs16132372","type":"journal-article","created":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T06:51:53Z","timestamp":1719557513000},"page":"2372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Analysis of Vegetation Canopy Spectral Features and Species Discrimination in Reclamation Mining Area Using In Situ Hyperspectral Data"],"prefix":"10.3390","volume":"16","author":[{"given":"Xu","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwei","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Environmental Studies, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7777-5429","authenticated-orcid":false,"given":"Xiaonan","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6100-0279","authenticated-orcid":false,"given":"Shuang","family":"Shuai","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Architecture, Wuhan Polytechnic University, Wuhan 430023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianhua","family":"Yang","sequence":"additional","affiliation":[{"name":"Sichuan Key Laboratory of Rare Earth Strategic Resources, Sichuan Geological Survey Institute, Chengdu 610081, China"},{"name":"Geo-Big Data Center, Sichuan Geological Survey Institute, Chengdu 610081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"146221","DOI":"10.1016\/j.scitotenv.2021.146221","article-title":"Grassland ecological restoration based on the relationship between vegetation and its below-ground habitat analysis in steppe coal mine area","volume":"778","author":"Feng","year":"2021","journal-title":"Sci. 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