Dataset Information
Enhancing the classification of spectrally similar land use/land cover classes using transfer learning in arid regions.
Ontology highlight
ABSTRACT:
SUBMITTER: Farag NH
PROVIDER: S-EPMC12949008 | biostudies-literature | 2026 Feb
REPOSITORIES: biostudies-literature
Publications
Enhancing the classification of spectrally similar land use/land cover classes using transfer learning in arid regions.
Scientific reports 20260226 1
Accurate mapping of Land Use/ Land Cover (LULC) in arid and semi-arid areas is essential for managing urban planning, monitoring environmental risks, and preserving the ecosystem balance. Conventional classification techniques provide inaccurate mapping of LULC in such areas due to the spectral similarity behavior of built-up and bareland classes. To address this challenge, semantic segmentation techniques have been recently employed to enhance classification accuracy. Meanwhile, in the case of ...[more]