Cargando…
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...
Autores principales: | , , , , , |
---|---|
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 |
_version_ | 1784683826564300800 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8993019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wanghua modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata AT zhuyuxin modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata AT wangjinghao modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata AT hanhubiao modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata AT niujiqiang modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata AT chenxueye modelingofspatialpatternandinfluencingfactorsofcultivatedlandqualityinhenanprovincebasedonspatialbigdata |