South China Geographical Journal >
Three-Dimensional Urban Expansion Simulation of Shenzhen City under the Future SSP Scenarios Based on 3D-FLUS Model
Received date: 2023-05-21
Revised date: 2023-05-29
Online published: 2023-09-25
With the acceleration of urbanization, urban expansion gradually tends to develop medium and high-rise buildings in the vertical direction from low-density development in the horizontal direction. It is very important to establish a dynamic three-dimensional model for simulating urban expansion to correctly explore the evolution process of urban three-dimensional space. However, the current model research on 3D urban expansion is very limited, and some of the existing 3D model studies still use the 2D land use area as the demand constraint condition, which is inconsistent with the actual 3D expansion simulation idea. Based on the above background, this paper takes Shenzhen as the research object, and proposes a 3D urban expansion simulation model mining the transformation rules that combine horizontal expansion and vertical growth,which is based on the two-dimensional FLUS model and the building mass in different shared socioeconomic paths (SSPs) scenarios as the constrained demand. It solves the problem of separation of horizontal and vertical simulation processes in previous studies. The research shows that in the simulation of urban land in the horizontal direction, the FoM index is 0.34, the Kappa coefficient is 0.887 9, and the overall accuracy is 95.14%. The relative error of each building volume in the vertical direction is less than or equal to 10%, and the fitting error is low. Moreover, the 3D-FLUS model predicts the three-dimensional urban expansion results of Shenzhen under different SSP scenarios in the future, which is of great significance for future urban planning.
DING Dan , LIU Xiaoping , XU Xiaocong . Three-Dimensional Urban Expansion Simulation of Shenzhen City under the Future SSP Scenarios Based on 3D-FLUS Model[J]. South China Geographical Journal, 2023 , 1(2) : 39 -50 . DOI: 10.20125/j.2097-2245.202302004
表1 空间驱动因素数据列表Tab.1 List of spatial driving factors |
数据类别 | 数据名称 | 年份 | 分辨率 | 数据来源 |
---|---|---|---|---|
基础地理数据 | 行政区划和边界 | 2019 | 全国地理信息资源目录服务系统 (https://www.webmap.cn) | |
市中心、区县中心 | ||||
公路、铁路 | ||||
水系、海洋 | ||||
铁路站点、地铁站点 | ||||
公园和绿地 | 2020 | OpenStreetMap (https://www.openstreetmap.org/) | ||
数字高程模型(DEM) | 2000—2013 | 30 m | ASTER GDEM V3 (https://search.earthdata.nasa.gov/) | |
坡度 | 30 m | 由DEM计算得到 | ||
感兴趣点 (POIs) | 商场 | 2018 | 高德地图 (https://www.amap.com) | |
医院 | ||||
娱乐设施 | ||||
超市 | ||||
餐饮 | ||||
公园 | ||||
公交站点 | ||||
工厂 | ||||
开放街道地图 (OSM) | 高速公路 | 2020 | OpenStreetMap (https://openstreetmap.org) | |
铁路 | ||||
国道 | ||||
省道 | ||||
城市路网 | ||||
社会经济 | 人口密度 | 2019 | 100 m | Worldpop (https://www.worldpop.org/) |
夜间灯光强度 | 2019 | 15″ (450 m) | NOAA/NGDC-EOG (https://www.ngdc.noaa.gov/eog/) | |
房价 | 2017 | 5 m | Yao et al |
表2 非建设用地像建设用地转换的转换成本表Tab.2 Conversion cost table for conversion of non-construction land to construction land |
用地类型 | 未利用 | 草地 | 园地 | 林地 | 坑塘沟渠 | 设施农用 | 耕地 |
---|---|---|---|---|---|---|---|
转换成本 | 0.647 3 | 0.758 1 | 0.955 0 | 0.969 9 | 0.934 1 | 0.895 7 | 0.839 9 |
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