Enhancing land use and land cover classification with deep learning-based satellite imagery segmentation

Semantic segmentation of satellite imagery plays a vital role in applications such as sustainable development, agriculture, forestry, urban planning, and climate change monitoring. Despite its importance, optimizing deep learning models for this task remains challenging. This study evaluates several...

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Autori principali: Tsion Fekadu Deressu, Amanuel Kumsa Bojer, Taye Girma Debelee, Worku Gachena Negera, Saralees Nadarajah, Kena Wendimu Gebissa
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2025-11-01
Serie:International Journal of Applied Earth Observations and Geoinformation
Soggetti:
Satellite image
Semantic segmentation
Deep learning
Land Use Land cover(LULC)
Remote sensing
DeeplabV3+
Accesso online:http://www.sciencedirect.com/science/article/pii/S1569843225004868
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