Abstract
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.
Highlights
As an essential geospatial feature, land use changes play an important role in many fields, such as global ecological environmental change, urban planning, and sustainable development [1]
The abovementioned problems in the currently and commonly used land use simulation methods were the reasons of initiating this study, which aims to compensate for GDP’s deficiencies by using nighttime light (NTL) as a proxy indicator of GDP, and the future land use simulation model (FLUS) model was used to address the influence of planning policies on land use distributions
Further analysis shows that the range of urban land in the simulation results is larger than that in actual land use patterns, and is distributed in small patches; this is because the land use change simulation is based on the cell grid, and the NPP/VIIRS
Summary
As an essential geospatial feature, land use changes play an important role in many fields, such as global ecological environmental change, urban planning, and sustainable development [1]. (2) land use spatial patterns are affected by abovementioned driving factors, and affected by planning policies, which cannot be stereotyped and constantly changes with the urban development over time [16]. The abovementioned problems in the currently and commonly used land use simulation methods were the reasons of initiating this study, which aims to compensate for GDP’s deficiencies by using NTL as a proxy indicator of GDP, and the FLUS model was used to address the influence of planning policies on land use distributions. NTL has been widely utilized for economic research [18], analyzing population/population density patterns [19], monitoring urban expansion [20], assessing ecological environment [21], building environment [22], energy consumption [23], and other fields, it has not been applied to the field of future land use simulation. The NPP/VIIRS and Luojia No 1 are selected to simulate the land use scenarios of Guangzhou during the period from 2015–2018 and 2018–2035, respectively
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