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Data for: Modeling of spatial pattern and influencing factors of cultivated land quality based on spatial-temporal big data (PONE-D-21-21084R1)

Cite this dataset

Zhu, Yuxin (2022). Data for: Modeling of spatial pattern and influencing factors of cultivated land quality based on spatial-temporal big data (PONE-D-21-21084R1) [Dataset]. Dryad.


The quality of cultivated land determines the production capacity of cultivated land and the level of regional development, and also directly affects the food security and ecological safety of the country. This paper starts from the perspective of spatial pattern of cultivated land quality and uses spatial autocorrelation analysis to study the spatial aggregation characteristics and differences of cultivated land quality in Henan Province at the county level scale, and also uses bivariate spatial autocorrelation to analyze the influence of neighboring influences on the quality of cultivated land in the target area. The spatial autoregressive model was used to further analyze the driving factors affecting the quality of cultivated land, and the influence of cultivated land area index was coupled in the process of rating analysis, which was finally used as a basis to propose more precise measures for the protection of cultivated land zoning. The results show that: (1) The quality of cultivated land in Henan Province has a strong spatial correlation (global Moran's I≈0.710) and shows an obvious aggregation pattern in spatial distribution; positive correlation types (high-high and low-low) are concentrated in north-central and western mountainous areas of Henan Province, respectively; negative correlation types are discrete. The negative correlation types are distributed in a discrete manner. (2) The bivariate spatial autocorrelation results show that Slope (Moran's I≈-0.505), Irrigation guarantee rate (IGR, 0.354), Urbanization rate (-0.255), Total agricultural machinery power (TAMP, 0.331) and Pesticide use (0.214) are the main influencing factors. (3) According to the absolute values of the regression coefficients, it can be seen that the magnitude of the influence of different factors on the quality of cultivated land is: Slope (0.089) >IGR (0.025) > Urbanization rate (0.002) > TAMP (0.001) > Pesticide use (1.96e-006). (4) Based on the spatial pattern presented by the spatial autocorrelation results, we proposed corresponding protection zoning measures to provide more scientific reference decisions and technical support for the implementation of refined cultivated land management in Henan Province. 


The data I submitted included topographic slope, irrigation guarantee rate, gross product, population size, soil pH, pesticide use, and total agricultural machinery power for each county and district in Henan Province. It also contains layer data of administrative divisions. 

Usage notes

Because we signed a confidentiality agreement with the Natural Resources Bureau, the spatial data on cropland quality used in the study could not be shared. In the data source table below I provide the email address and contact information of the Natural Resources Bureau of Henan Province. If
other scholars need to use the data, they can apply to them for the right to use the data.

No. Data Description of Data Source Department of Data Source
1. Natural quality grade, utilization grade and economic grade of cultivated land, Spatial Data Database of the 2018 Cultivated Land Quality Grade Update Project in Henan Province Natural Resources Planning Bureau of Henan Province
2. Data on slope, IGR ,TAMP and other influencing factors in each county cultivated land quality update evaluation results and County Statistical Yearbook(2018)
URL: Agriculture Bureau
3. Town bound boundaries Industrial and tourism development planning Development and
Reform Commission and Resource and Environment Science and Data Center


National Natural Science Foundation of China, Award: 41771438

Open Fund Project of the Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Award: KLSPWSEP-A01

Key scientific and technological project of Henan Province, Award: 212102210105