The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China

The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China

In light of the need for fine-grained, accurate, and timely urban land use information, a per-field classification approach was proposed in this paper to automatically map fine-grained urban land use in a study area within Haidian District, Beijing, China, in 2016. High-resolution remote sensing ima...

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Bibliographic Details
Main Authors: Yuan Zhang, Qiangzi Li, Huiping Huang, Wei Wu, Xin Du, Hongyan Wang
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Remote Sensing
Subjects:
urban land use classification
per-field classification
remote sensing
social sensing
random forests
Online Access:https://www.mdpi.com/2072-4292/9/9/865

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