Affiliation:
1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Abstract
How to recognize the land use change in urban villages during dynamic transformation in Haidian District, Beijing, has become a hot topic with the promotion of urban renewal. The GF-1 high-resolution remote sensing images of 2013, 2015, and 2020 were used in this study to reflect the land use change in urban villages before and after urban renewal by using a hierarchical machine learning recognition method based on scene-based and random forest classification. The overall scale of urban village blocks in Haidian was 10.46 km2, showing the distribution pattern along the traffic arteries in 2013. In 2015, it dropped to 10.11 km2. The scale of urban village blocks in 2020 decreased to 1.02 km2, 9.75% of that in 2013. Three kinds of urban village renewal logic are revealed by further taking Chuanying Village as an example: “urban village–blue–green space”, “urban village–real estate”, and “urban village–municipal facilities”.
Funder
National Natural Science Foundation of China
Subject
General Earth and Planetary Sciences
Cited by
3 articles.
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