Built-Up Area Mapping for the Greater Bay Area in China from Spaceborne SAR Data Based on the PSDNet and Spatial Statistical Features

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 14; p. 3428
• Main Authors: Zhang, Wei, Lu, Shengtao, Xiang, Deliang, Su, Yi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2022
• Subjects: Algorithms; Amplitudes; Artificial neural networks; built-up area extraction; China; Cities; Classification; Computer networks; Data processing; Deep learning; Feature extraction; Land settlement; Mapping; pseudo-Siamese dense convolutional network; Remote sensing; spatial statistical features; Statistics; Sustainable development; Synthetic aperture radar; synthetic aperture radar (SAR); Teaching methods; the Greater Bay Area; Urban areas; Urban planning; Urbanization; Hong Kong China; Pearl River (China); China; Macao

Built-up areas (BAs) information acquisition is essential to urban planning and sustainable development in the Greater Bay Area in China. In this paper, a pseudo-Siamese dense convolutional network, namely PSDNet, is proposed to automatically extract BAs from the spaceborne synthetic aperture radar...