Spatial-Contextual Information Utilization Framework for Land Cover Change Detection With Hyperspectral Remote Sensed Images

Land cover change detection (LCCD) using bitemporal remote sensing images is a crucial task for identifying the change areas on the Earth's surface. However, the utilization of hyperspectral remote sensing images (HRSIs) introduces challenges as the detection performance is affected by the spec...

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Vydáno v:	IEEE transactions on geoscience and remote sensing Ročník 61; s. 1 - 11
Hlavní autoři:	Lv, Zhiyong, Zhang, Ming, Sun, Weiwei, Benediktsson, Jon Atli, Lei, Tao, Falco, Nicola
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Adaptive contextual analysis Adaptive filters Change detection Deep learning Detection Earth surface Feature extraction Hyperspectral imaging hyperspectral remote sensing images (HRSIs) Information processing Iterative methods Land cover land cover change detection (LCCD) Redundancy Remote sensing Sun Training Vector analysis White noise
ISSN:	0196-2892, 1558-0644
On-line přístup:	Získat plný text
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