{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T07:15:58Z","timestamp":1765178158737,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T00:00:00Z","timestamp":1692576000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"],"award-info":[{"award-number":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"]}]},{"name":"National Natural Science Foundation of China","award":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"],"award-info":[{"award-number":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"]}]},{"DOI":"10.13039\/501100018617","name":"Liaoning Revitalization Talents Program","doi-asserted-by":"publisher","award":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"],"award-info":[{"award-number":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"]}],"id":[{"id":"10.13039\/501100018617","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Science and Technology Department of Liaoning Province","award":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"],"award-info":[{"award-number":["2016YFC0801602","2020AAA0109200","41974028","52074064","XLYC2008020","2021-BS-054"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The accuracy and rapidity of total iron content (TFE) analysis can accelerate iron ore production. Although the conventional TFE detection methods are accurate, its detection speed presents difficulties in meeting production requirements. Therefore, this paper proposes a method of TFE detection based on reflectance spectroscopy (wavelength range: 340\u20132500 nm) and remote sensing. Firstly, spectral experiments were conducted on iron ore using the HR SVC-1024 spectrometer to obtain spectral data for each sample. Then, the spectra were smoothed and dimensionally reduced by using wavelet transform and principal component analysis. To improve the detection accuracy of TFE, a two hidden layer extreme learning machine with variable neuron nodes based on an improved sparrow search algorithm and batch normalization optimization (MSSA-BNVTELM) is proposed. According to the experimental results, MSSA-BNVTELM exhibited superior detection accuracy in comparison to other algorithms. In addition, this research established a remote sensing detection model using Sentinel-2 data and MSSA-BNVTEM to detect the distribution of TFE in the mining area. The distribution of TFE in the mine area was plotted based on the detection results. The results show that the remote sensing of the mine area can be useful for detection of the TFE distribution, providing assistance for the mining plan.<\/jats:p>","DOI":"10.3390\/rs15164100","type":"journal-article","created":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T01:46:56Z","timestamp":1692582416000},"page":"4100","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Rapid Detection of Iron Ore and Mining Areas Based on MSSA-BNVTELM, Visible\u2014Infrared Spectroscopy, and Remote Sensing"],"prefix":"10.3390","volume":"15","author":[{"given":"Mengyuan","family":"Xu","sequence":"first","affiliation":[{"name":"School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China"}]},{"given":"Yachun","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China"}]},{"given":"Mengqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Heze Vocational College, Heze 274000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0401-6654","authenticated-orcid":false,"given":"Dong","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University, Shenyang 110819, China"}]},{"given":"Hongfei","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University, Shenyang 110819, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,21]]},"reference":[{"key":"ref_1","first-page":"631","article-title":"Multi-Source and Multi-Target Iron Ore Blending Method in Open Pit Mine","volume":"67","author":"Yao","year":"2022","journal-title":"Arch. 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