Spatial planning zoning based on land-type mapping: a case study in Changzhou City, Eastern China

Figures & data

Table 1. Sources and main uses of data used in this study

Data source	Description
1. Data for classification
1.1 Landform
Digital Line Graphic (2010) Acquired from Changzhou Bureau of Land and Resources	Vector layer (1:50,000) of geographic conditions such as elevation and contour supported by Chinese government. They were acquired by field measurement and were the basis to construct digital elevation model (DEM).
1.2 Soil
Soil Type (2010) Acquired from Geographic Information Monitoring Cloud Platform (http://www.dsac.cn)	Vector layer (1:100,000) of soil subtype in Changzhou based on field measurement.
1.3 Land use
Land-use Type (2015) Acquired from Changzhou Bureau of Land and Resources	Vector layer (1:50,000) generated by field data acquisition and remote sensing image interpretation supported by Chinese government.
1.4 Land-use Intensity
Farmland Quality (2013) Acquired from Changzhou Bureau of Land and Resources	Based on the standard farming system, the quality of farmland (vector layer, 1:50,000) was classified based on the natural conditions and the utilization intensity of land resource. The detail of evaluation system refers to Regulation for Gradation on Agriculture Land Quality (Ministry of Land and Resources of the People’s Republic of China (MLRPRC), 2012).
Point of Interest (2015) Acquired from Geographic Information Monitoring Cloud Platform (http://www.dsac.cn)	Vector layer includes spatial and attribute information such as latitude, longitude, and point name. This paper divided POI data into four sets included commercial set (16,460 points of shopping and service points), residential set (2582 points of estate), industrial set (23,066 points of factory), public management and service set (81 points of traffic stations, university campuses, government).
2. Data for verification
2.1 Landform
DEM (2010) Acquired from Geospatial Data Cloud (http://www.gscloud.cn/)	GDEM (Global Digital Elevation Model) layer (30 m × 30 m) generated by cooperation of METI (Ministry of Economy, Trade and Industry) and NASA (National Aeronautics and Space Administration). It is used to be compared with landform classification results.
2.2 Land-use Intensity
Open Street Map (OSM) (2015) (https://www.openstreetmap.org)	Vector layer with the attribute of functions of a street block (e.g. industrial areas, commercial areas, and residential areas). This data is the basis of urban functional areas verification.
Potential Crop Yield (2010) Resource and Environment Data Cloud Platform (http://www.resdc.cn/)	Based on DEM, soil, and other data of cultivated land distribution, GAEZ (Global Agro-Ecological Zones) model was applied to estimate the farmland production potential in China (L. Liu et al., 2015). This data (raster, 1000 m × 1000 m) is the basis of agricultural land quality classification verification.
2.3 Typical land-type points
Land Value Points (2015) (http://www.landvalue.com.cn/Tradept/Index)	Points (vector) in dataset include land transfer price, spatial location, and urban function (e.g. industry, resident, and commerce) information. Based on field measurement, other attributes such landform, soil and land use were collected to construct typical urban land-type points.
Grain Yield Survey (2013) Acquired from Changzhou Bureau of Land and Resources	Points (vector) in dataset include grain yield based on field measurement. Other attributes such landform, soil and land use were surveyed to construct typical agricultural land-type points.

Figure 1. Study area and spatial distribution of different types of data used in this research: (a) land use, (b) spatial location, (c) elevation, (d) soil type, (e) farmland quality, and (f) point of interest (POI). Note. PSO: paddy soil; BLPSO: bleached paddy soil; PPSO: percogenic paddy soil; DPSO: degleyed paddy soil; ML: medium loam; BRRSO: brown-red soil; RSO: red soil; ALLSO: alluvial soil; YCSO: yellow-cinnamon soil; CLPYCSO: clay pan yellow-cinnamon soil; FLAGUSO: fluvo-aquic soil; BSO: bog soil; YBOSO: yellow-brown soil; ACSKSO: acid skeletal soil; SKSO: skeletal soil; TF: terra fusca.

Figure 2. Technological flow of land-type classifications and spatial planning zoning.

Table 2. Terrain factors and their mathematical expressions

Factor	Description
Slope$R=S_h/S_l$	The maximum rate of change from a cell in the land surface to its neighbors (Sh is the vertical height, and Sl is the horizontal distance), which indicates the steepness of landform.
The rate of change in slopes	The gradient of slope, which is the basic representation of surface morphology.
Relief$RF=H_{max}-H_{min}$	The extreme difference from a cell in the land surface to its neighbors (Hmax is the highest elevation, and Hmin is the lowest). It is an important index to quantitatively describe landform.

Figure 3. Differences between land zoning based on land-types and spatial planning systems.

Table 3. Generalization rules of land suitability based on land-types

Land Zones	Land-types
	Landform	Soil	Land use
Ecology
Nature Conservation	Any landform	Any soil type	Forestry
		Any soil type	Unutilized land
		Yellow-brown Soil, Skeletal Soil, Acid Skeletal Soil, Alluvial Soil, Takyr, Terra Fusca	Grade 7 agricultural land
Water	-	-	River and lake
Agriculture
Grain Product	Slope <15°	Paddy Soil, Bleached Paddy Soil, Percogenic Paddy Soil, Degleyed Paddy Soil, Medium Loam	Grade 5, 6, and 7 agricultural land
		Brown-red Soil, Red Soil, Yellow-cinnamon Soil, Clay Pan Yellow-Cinnamon Soil, Bog Soil, Fluvo-aquic Soil	Grade 5 and 6 agricultural land
		Yellow-brown Soil, Skeletal Soil, Acid Skeletal Soil, Alluvial Soil, Takyr, Terra Fusca	Grade 5 agricultural land
Perennial Plantation	Slope >15°	Paddy Soil, Bleached Paddy Soil, Percogenic Paddy Soil, Degleyed Paddy Soil, Medium Loam	Grade 5,6, and 7 agricultural land
		Brown-red Soil, Red Soil, Yellow-cinnamon Soil, Clay Pan Yellow-Cinnamon Soil, Bog Soil, Fluvo-aquic Soil	Grade 5 and 6 agricultural land
		Yellow-brown Soil, Skeletal Soil, Acid Skeletal Soil, Alluvial Soil, Takyr, Terra Fusca	Grade 5 agricultural land
	Any landform	Brown-red Soil, Red Soil, Yellow-cinnamon Soil, Clay Pan Yellow-Cinnamon Soil, Bog Soil, Fluvo-aquic Soil	Grade 7 agricultural land
		Yellow-brown Soil, Skeletal Soil, Acid Skeletal Soil, Alluvial Soil, Takyr, Terra Fusca	Grade 6 agricultural land
Built-up
Urban-Town	Any landform	Impervious	Mixed-function area, Public management & service area, Commercial area, Residential area, Industrial area
Rural-Town	Any landform	Impervious	Rural built-up lands

Figure 4. Land-type map of Changzhou City (detailed information of legend is showed in the Appendix).

Figure 5. Proportions of land-types in Changzhou City. (a) Proportion of Level 2 land-types. (b) Proportion of land-use types. (c) Agricultural land quality of different soil types. (d) Proportion of urban functional areas in different buffer areas.

Figure 6. Spatial planning zoning map of Changzhou City.

Figure 7. Accuracy of land-types. (a) Accuracy of landform classification. (b) Accuracy of agricultural land quality. (c) Accuracy of urban functional areas. (d) Accuracy assessment based on typical land-type points.

Ministry of Land and Resources of the People’s Republic of China (MLRPRC). (2012). GB/T28407-2012. In Regulation for gradation on agriculture land quality (pp. 1–27). Standards Press of China. (in Chinese).

 Google Scholar

Liu, L., Xu, X., & Chen, X. (2015). Assessing the impact of urban expansion on potential crop yield in China during 1990–2010. Food Security, 7(1), 33–43. https://doi.org/https://doi.org/10.1007/s12571-014-0411-z

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