Deep Feature Enhancement Method for Land Cover With Irregula…

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  • DOI 10.1109/tgrs.2023.3241331
  • OpenAlex ID W4318767606
  • Type Article
  • Language EN
  • Published 01 Jan 2023
  • Volume 61
  • Pages 1–20
  • Source IEEE Transactions on Geoscience and Remo…
  • Publisher Institute of Electrical and Electro…
  • FWCI 4.19
  • Countries 1
  • Institutions 1
  • Added 02 Feb 2023
  • Updated 29 Oct 2026
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Deep Feature Enhancement Method for Land Cover With Irregular and Sparse Spatial Distribution Features: A Case Study on Open-Pit Mining

Article 2023 EN

Land cover classification in mining areas (LCMA) is essential for the environmental assessment of mines and plays a crucial role in their sustainable development. The shapes of mine land occupation elements are irregular, and the overall proportion of their area is relatively small. Therefore, their features may be easily lost during feature extraction, which limits the interpretation accuracy in…

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4.19

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6 authors
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1 Gaodian Zhou China University of Geoscience… (CN)
2 Jiahui Xu China University of Geoscience… (CN)
3 Weitao Chen China University of Geoscience… (CN)
4 Xianju Li China University of Geoscience… (CN)
5 Jun Li China University of Geoscience… (CN)
6 Lizhe Wang China University of Geoscience… (CN)
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