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Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data.
Wang, Hua; Zhu, Yuxin; Wang, Jinghao; Han, Hubiao; Niu, Jiqiang; Chen, Xueye.
Afiliación
  • Wang H; School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
  • Zhu Y; School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
  • Wang J; School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
  • Han H; School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
  • Niu J; Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang Normal University, Xinyang, China.
  • Chen X; Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen, China.
PLoS One ; 17(4): e0265613, 2022.
Article en En | MEDLINE | ID: mdl-35395011
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Plaguicidas / Macrodatos Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Plaguicidas / Macrodatos Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: China