Land use/cover classification in an arid desert-oasis mosaic landscape of China using remote sensed imagery: Performance assessment of four machine learning algorithms

• Published in: Global ecology and conservation Vol. 22; p. e00971
• Main Authors: Ge, Genbatu, Shi, Zhongjie, Zhu, Yuanjun, Yang, Xiaohui, Hao, Yuguang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2020; Elsevier
• Subjects: Arid area; arid lands; China; climate; Desert-oasis mosaic landscape; ecosystems; image analysis; land cover; land use; Land use/cover change; Landsat; landscapes; Machine learning algorithms; neural networks; oases; remote sensing; support vector machines; China; Arid area; Desert-oasis mosaic landscape; Machine learning algorithms; Land use/cover change

The importance of land use and cover change (LUCC) has gradually attracted more attention due to its influence on the climate and ecosystem. Consequently, the necessity of accurate LUCC mapping has become increasingly apparent. Over the past decades, although a large number of machine learning algor...