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Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data

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...

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Autores principales: Wang, Hua, Zhu, Yuxin, Wang, Jinghao, Han, Hubiao, Niu, Jiqiang, Chen, Xueye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8993019/
https://www.ncbi.nlm.nih.gov/pubmed/35395011
http://dx.doi.org/10.1371/journal.pone.0265613
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author Wang, Hua
Zhu, Yuxin
Wang, Jinghao
Han, Hubiao
Niu, Jiqiang
Chen, Xueye
author_facet Wang, Hua
Zhu, Yuxin
Wang, Jinghao
Han, Hubiao
Niu, Jiqiang
Chen, Xueye
author_sort Wang, Hua
collection PubMed
description 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.
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spelling pubmed-89930192022-04-09 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 PLoS One Research Article 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. Public Library of Science 2022-04-08 /pmc/articles/PMC8993019/ /pubmed/35395011 http://dx.doi.org/10.1371/journal.pone.0265613 Text en © 2022 Wang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Hua
Zhu, Yuxin
Wang, Jinghao
Han, Hubiao
Niu, Jiqiang
Chen, Xueye
Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title_full Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title_fullStr Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title_full_unstemmed Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title_short Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data
title_sort modeling of spatial pattern and influencing factors of cultivated land quality in henan province based on spatial big data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8993019/
https://www.ncbi.nlm.nih.gov/pubmed/35395011
http://dx.doi.org/10.1371/journal.pone.0265613
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