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Open AccessArticle

Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features

1
College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China
2
Institute of National Development and Security Studies, Jilin University, Changchun 130026, China
3
Key Laboratory of Lunar and Deep-Space Exploration, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
4
Institute of Integrated Information for Mineral Resources Prediction, Jilin University, Changchun 130061, China
5
College of Physics, Jilin University, Changchun 130026, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(1), 153; https://doi.org/10.3390/rs13010153
Received: 2 December 2020 / Revised: 31 December 2020 / Accepted: 3 January 2021 / Published: 5 January 2021
(This article belongs to the Special Issue Optical Remote Sensing Applications in Urban Areas)
As the capital city of China, Beijing has experienced unprecedented economic and population growth and dramatic impervious surface changes during the last few decades. An application of the classification method combining the spectral and textural features based on Random Forest was conducted to monitor the spatial and temporal changes of Beijing’s impervious surfaces. This classification strategy achieved excellent performance in the impervious surface extraction in complex urban areas, as the Kappa coefficient reached 0.850. Based on this strategy, the impervious surfaces inside Beijing’s sixth ring road in 1997, 2002, 2007, 2013, and 2017 were extracted. As the development of Beijing has a special regional feature, the changes of impervious surfaces within the sixth ring road were assessed. The findings are as follows: (1) the textural features can significantly improve the classification accuracy of land cover in urban areas, especially for the impervious surface with high albedo. (2) Impervious surfaces within the sixth ring road expanded dramatically from 1997 to 2017, had three expanding periods: 1997–2002, 2002–2007, and 2013–2017, and only shrank in 2007–2013. There are different possible major driving factors for each period. (3) The region between the fifth and sixth ring roads in Beijing underwent the most significant changes in the two decades. (4) The inner three regions are relatively highly urbanized areas compared to the outer two regions. Urbanization processes in the interior regions tend to be completed compared to the exterior regions. View Full-Text
Keywords: impervious surface; spatiotemporal change; textural feature; Random Forest; Beijing; urbanization process impervious surface; spatiotemporal change; textural feature; Random Forest; Beijing; urbanization process
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MDPI and ACS Style

Dong, X.; Meng, Z.; Wang, Y.; Zhang, Y.; Sun, H.; Wang, Q. Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features. Remote Sens. 2021, 13, 153. https://doi.org/10.3390/rs13010153

AMA Style

Dong X, Meng Z, Wang Y, Zhang Y, Sun H, Wang Q. Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features. Remote Sensing. 2021; 13(1):153. https://doi.org/10.3390/rs13010153

Chicago/Turabian Style

Dong, Xuegang; Meng, Zhiguo; Wang, Yongzhi; Zhang, Yuanzhi; Sun, Haoteng; Wang, Qingshuai. 2021. "Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features" Remote Sens. 13, no. 1: 153. https://doi.org/10.3390/rs13010153

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