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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Hlavní autoři:	Tsion Fekadu Deressu, Amanuel Kumsa Bojer, Taye Girma Debelee, Worku Gachena Negera, Saralees Nadarajah, Kena Wendimu Gebissa
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2025-11-01
Edice:	International Journal of Applied Earth Observations and Geoinformation
Témata:	Satellite image Semantic segmentation Deep learning Land Use Land cover(LULC) Remote sensing DeeplabV3+
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S1569843225004868
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