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Open AccessArticle

Land Use Simulation of Guangzhou Based on Nighttime Light Data and Planning Policies

College of Tourism and Geographic Sciences, Yunnan Normal University, Kunming 650500, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Department of Geography and the Environment, University of North Texas, Denton, TX 76203, USA
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(10), 1675;
Received: 12 April 2020 / Revised: 21 May 2020 / Accepted: 21 May 2020 / Published: 23 May 2020
With the implementation processes of strategies such as Guangdong-Hong Kong-Macau Greater Bay Area’s coordinated development and “Belt and Road Initiative” initiative, the planning policies had produced a significant influence on land use distributions in Guangzhou. In this paper, we employ nighttime light (NTL) information as a proxy indicator of gross domestic product(GDP), and a future land use simulation model (FLUS) to simulate the land use patterns in Guangzhou from 2015 to 2018 and 2018 to 2035 by incorporating planning policies. The results show that: (1) the accuracy of simulation result from 2015 to 2018 based on National Polar-orbiting Partnership, Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) is higher than that based on GDP; (2) by incorporating planning policies into the model can better identify the potential spatial distribution of urban land and make the simulated results more consistent with the actual urban land development trajectory. This study demonstrates that NTL is a suitable and feasible proxy indicator of GDP for the land use simulations, providing a scientific basis for the development of urban planning and construction policy. View Full-Text
Keywords: nighttime light; planning policies; land use simulation; FLUS; Guangzhou nighttime light; planning policies; land use simulation; FLUS; Guangzhou
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MDPI and ACS Style

Lao, J.; Wang, C.; Wang, J.; Pan, F.; Xi, X.; Liang, L. Land Use Simulation of Guangzhou Based on Nighttime Light Data and Planning Policies. Remote Sens. 2020, 12, 1675.

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