“双评价”视角下基于FLUS模型的武汉大都市区土地利用模拟和城镇开发边界划定研究

doi:10.12082/dqxxkx.2020.200137

Abstract

Abstract:

The delimitation of urban growth boundaries is of great significance for ensuring the rational use of resources and promoting the orderly development of cities and towns. Most existing studies mainly focus on the technical exploration of planning practice, while ignoring the quantitative assessment of the ecological environment to some extent. In addition, few studies have been carried out at the metropolitan area scale. This study takes Wuhan Metropolitan Area as the study case, and proposes to combine multiple factors to build a "dual environment evaluation" system. The FLUS model is used for land growth simulation and delineation of urban growth boundaries. Furthermore, the results are analyzed using the landscape metrics. The results show that: (1) the FLUS simulated urban area expansion demonstrates an applicable accuracy. The simulation results reveal that the urban built-up areas keep expanding, so it is necessary to delimit the development boundary to restrict urban development; (2) The delineated urban growth boundaries can prevent from urban construction occupying areas with high ecological or agricultural value, and improve the urban spatial layout of the Wuhan Metropolitan Area based on the optimization of spatial forms with strong applicability; (3)The evaluation of urban expansion driving factors shows that compared to a single factor library, the "dual environment evaluation" factor library has a higher accuracy, can optimize the landscape pattern, promote the development of construction land, and fill the gaps in the built-up area better, which is corresponded with regional development requirements; and (4) The evaluation of expansion analysis shows that the results are consistent with the expected development pattern of Wuhan Metropolitan Area, and government departments might pay attention to the potential value of the expansion in the airport region, the Yangluo region, the Optics Valley-Future City region, and the Zhifang region. The above shows the effectiveness of the FLUS model in the Wuhan metropolitan area, which also provides great reference for planning management and construction land optimization.

Key words: Land use simulation, Urban Growth Boundaries, Dual environment evaluation, FLUS model, Wuhan Metropolitan area, Evaluation of landscape pattern index, Space control, Regional collaborative development

ZHAO Xuan, PENG Jiandong, FAN Zhiyu, YANG Chen, YANG Hong. Land Use Simulation and Urban Growth Boundaries Delineation in Wuhan Metropolitan Area based on FLUS Model and "Dual Environment Evaluation"[J].Journal of Geo-information Science, 2020, 22(11): 2212-2226.DOI:10.12082/dqxxkx.2020.200137

Figures/Tables 21

Fig. 1

Tab.1

The meaning and calculation formula of landscape index"

景观指数	指数含义	计算公式公式编号
斑块面积指数CA	表示斑块类型的总面积	$CA = ∑ i = 1 n a i$ （3）式中: $a i$ 是斑块 $i$ 的面积
最大斑块指数LPI	表示最大斑块面积所占比例	$LPI = max a i A × 100$ （4）式中: $a i$ 为斑块 $i$ 的面积, $A$ 为景观总面积
斑块数量指数NP	表示斑块总数量	$NP = ∑ n j$ （5）式中: $n i$ 是第 $j$ 类斑块的个数
平均周长面积比指数PARA_MN	表示形状复杂度,值越小,形状越简单规整	$PARA_MN = ∑ i = 1 n p i a i$ （6）式中: $p i$ 为斑块 $i$ 的周长, $a i$ 为斑块 $i$ 的面积
平均最邻近指数ENN_MN	表示空间分布特征,值越小,分布越集中	$ENN_MN = ∑ i = 1 n h i n i$ （7）式中: $h i$ 是斑块 $i$ 到最邻近斑块直线距离
景观分裂度指数SPLIT	表示被割裂程度,值越小,破碎度越低	$SPLIT = A 2 ∑ i = 1 n a i 2$ （8）式中: $a i$ 是斑块 $i$ 的面积, $A$ 为景观总面积

Tab.1

Fig. 2

Fig. 3

Tab.2

Information of driving factors for land use simulation in Wuhan metropolitan area"

	数据名称		数据说明	年份	数据来源
资源环境承载力评价因子库	水资源	年平均降水量	1 km×1 km栅格数据	2015	a
		水资源供给	具体见生态系统服务价值空间分布数据^[30]
		水文调节	具体见生态系统服务价值空间分布数据^[30]
		距河流水系的距离	30 m×30 m栅格数据
	土地资源	土壤质地	计算粉砂土、黏土、砂土含量空间分布	1995	a
	植被资源	年度植被指数	NDVI数据	2015	b
	粮食资源	净初级生产力	NPP数据	2010	a
		食物生产能力	具体见生态系统服务价值空间分布数据^[30]	2015
		原料生产能力	具体见生态系统服务价值空间分布数据^[30]	2015
	大气资源	大气污染指数	PM2.5空间插值栅格数据	2018	c
		年平均气温	1 km×1 km栅格数据	2010	a
		气体调节	具体见生态系统服务价值空间分布数据^[30]	2015	a
		气候调节	具体见生态系统服务价值空间分布数据^[30]	2015	a
	水土流失	土壤侵蚀	1 km×1 km侵蚀强度	2015	a
	城市化	距武汉大都市区中心距离距县区中心的距离距矿产资源的距离	30 m×30 m栅格数据	2015 2015 2018	a
	生物多样性	生物多样性	具体见生态系统服务价值空间分布数据^[30]	2015	a
城市空间适宜性评价因子库	地形条件	地形（DEM）、坡度	坡度据地形数据计算	2015	d
	交通优势	距机场的距离	30 m×30 m栅格数据	2019	e
		距高速公路的距离
		距国道的距离
		距省道的距离
		距城市主干路的距离
		距火车轻轨站的距离
		距铁路的距离
	经济发展	GDP	1 km×1 km人均GDP	2015	a
	人口聚集	人口密度	1 km×1 km人口分布	2015	a
	设施适宜度	距行政机关的距离	30 m×30 m栅格数据	2019	e
		距知名企业的距离
		距购物中心的距离
		距高等院校的距离
		距三甲医院的距离
		距公园广场的距离
		距产业园区的距离
		距风景名胜的距离
	地质灾害	距地质灾害点距离	30 m×30 m栅格数据	2015	a
	生态发展	净化环境能力	具体见生态系统服务价值空间分布数据^[30]	2015	a
	生态发展	美学景观	具体见生态系统服务价值空间分布数据^[30]	2015	a

Tab.2

Fig. 4

Fig. 5

Fig. 6

Tab.3

Tab.4

Tab.5

Fig. 7

Fig. 8

Tab. 6

Tab. 7

Tab. 8

Tab. 9

Fig. 9

Fig. 10

Fig. 11

Fig. 12

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年份	耕地	林地	草地	水域	城镇建设用地	对外交通用地	农村居民点用地	未利用土地
2005	11 080.70	2551.20	356.70	4188.20	1191.21	94.77	907.28	185.90
2015	10 636.95	2524.71	351.96	4195.49	1625.56	109.03	930.20	182.08
2025	10 211.33	2498.37	347.24	4200.36	2049.50	118.59	952.25	178.33
2035	9803.07	2472.20	342.54	4202.94	2462.42	124.67	973.48	174.66

用地类型	耕地	林地	草地	水域	城镇建设用地	对外交通用地	农村居民点用地	未利用土地
耕地	1	0	0	1	1	1	1	0
林地	0	1	0	0	1	1	0	0
草地	1	1	1	0	1	1	0	0
水域	1	0	0	1	1	1	0	0
城镇建设用地	0	0	0	0	1	0	0	0
对外交通用地	0	0	0	0	1	1	0	0
农村居民点用地	0	0	0	0	1	1	1	0
未利用土地	1	0	0	1	1	1	0	1

描绘方案	CA/ha	LPI/%	NP/个	PARA_MN	ENN_MN/m	SPLIT
DEE- UGB	253 320	30.66	792	105.26	1098.5	1716.9	0.9465
BASIC- UGB	253 626	29.85	769	109.40	1128.7	1645.9	0.9435
RECC- UGB	254 121	30.57	789	106.22	1108.2	1728.8	0.9422
USS- UGB	254 230	30.37	768	106.65	1125.9	1704.9	0.9456
2015-UGB	161 111	12.20	1169	118.29	882.2	2252.8	0.7352

描绘方案	飞地式扩张											总计/个
描绘方案	数量/个	比例/%		数量/个		比例/%		数量/个		比例/%		总计/个
DEE-UGB	89		4.16		1404		65.70		644		30.14	2137
BASIC- UGB	81		2.45		2322		70.32		899		27.23	3302
RECC- UGB	102		3.99		1747		68.27		710		27.75	2559
USS- UGB	70		2.18		2227		69.33		915		28.49	3212

时间	N	NNE	NE	NEE	E	SEE	SE	SSE	S	SSW	SW	SWW	W	NWW	NW	NNW
2015-2025	1.1	0.3	1.6	1.1	3.0	4.2	0.9	0.9	2.4	1.2	1.4	1.6	1.4	1.0	1.5	1.2
2025-2035	1.3	0.4	1.7	1.1	2.1	2.9	0.7	0.7	2.4	1.2	1.1	1.2	1.6	1.2	1.4	1.1
2015-2035	2.5	0.7	3.3	2.2	5.1	7.1	1.6	1.6	4.7	2.4	2.5	2.7	3.0	2.2	2.9	2.3

Land Use Simulation and Urban Growth Boundaries Delineation in Wuhan Metropolitan Area based on FLUS Model and "Dual Environment Evaluation"

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