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Analysis of urban growth from 1960 to 2015 using historical DISP and Landsat time series data in Shanghai

  • Huan Mi
  • Gang QiaoEmail author
  • Weian Wang
  • Yang Hong
Original Paper
  • 59 Downloads

Abstract

Urbanization is one of the most important dimensions of contemporary global change. Urban growth affects life-supporting environment of human beings, as well as natural ecological system and biological composition. Thus, long time series urban land cover datasets with high spatial and temporal resolution are useful for understanding the dynamics of urban growth processes, providing great insights into urban planning and sustainable development in the future. For the first time, this study analyzes 55-year spatiotemporal patterns of urban changes in Shanghai, China, by integrating the historical Declassified Intelligence Satellite Photography (DISP) and Landsat time series data at 5-year intervals from 1960 to 2015. Here we applied different methods to detect urban land from DISP and Landsat images, respectively, and their accuracies were quantitatively analyzed and evaluated. The spatiotemporal patterns of urban growth were explored. The derived products showed that urban land cover increased at a rapid and accelerating pace with growth concentrated at the expanding fringes of existing urban clusters. Across the study region, the total urban area increased from 205.10 to 2259.97 km2, at an average annual rate of 37.4 km2/year, and the percentage of urban area increased from 3.33 to 31.96%, expanded by more than 10 times between 1960 and 2015. In addition, urban area increased over time in all directions; the relative proportions of the urban area in downtown and non-downtown changed dramatically over the study period, indicating that urban sprawl of the metropolis experienced major transitions under the effect of population increase, economic development, and policies.

Keywords

Urban growth Remote sensing DISP Landsat Shanghai 

Notes

Funding information

This research was supported by the National Key R&D Program of China (2017YFA0603102), the National Science Foundation of China (91547210), the National Key R&D Program of China (2017YFB0503502), the National Science Foundation of China (41771471, 41201425), and the Fundamental Research Funds for the Central Universities.

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Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  1. 1.College of Surveying and Geo-InformaticsTongji UniversityShanghaiChina
  2. 2.School of Civil Engineering and Environmental SciencesThe University of OklahomaNormanUSA

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