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High-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images.
- Source :
-
Science bulletin [Sci Bull (Beijing)] 2020 Jun 30; Vol. 65 (12), pp. 1039-1048. Date of Electronic Publication: 2020 Mar 06. - Publication Year :
- 2020
-
Abstract
- Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution (2 m) urban land-cover map (Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer's accuracies and user's accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level. Compared with the existing medium-resolution land-cover/use datasets (at a 30-m resolution), Hi-ULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.<br />Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.<br /> (Copyright © 2020 Science China Press. Published by Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 2095-9281
- Volume :
- 65
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Science bulletin
- Publication Type :
- Academic Journal
- Accession number :
- 36659019
- Full Text :
- https://doi.org/10.1016/j.scib.2020.03.003