Wide-Area Land Cover Mapping With Sentinel-1 Imagery Using Deep Learning Semantic Segmentation Models

Land cover (LC) mapping is essential for monitoring the environment and understanding the effects of human activities on it. Recent studies demonstrated successful applications of specific deep learning models to small-scale LC mapping tasks (e.g., wetland mapping). However, it is not readily clear...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.10357-10374
Hauptverfasser:	Scepanovic, Sanja, Antropov, Oleg, Laurila, Pekka, Rauste, Yrjo, Ignatenko, Vladimir, Praks, Jaan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Biological system modeling C band Coders CORINE Deep learning Encoders-Decoders Environmental monitoring Feature extraction Image acquisition image classification Image processing Image segmentation Imagery Imaging radar Land cover land cover (LC) mapping Mapping Optical imaging Radar data Radar imaging Radar polarimetry Remote sensing SAR (radar) Satellite imagery Satellites Semantic segmentation Semantics sentinel-1 data Spaceborne remote sensing Statistical analysis Synthetic aperture radar synthetic aperture radar (SAR)
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