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

被引:13
|
作者
Wang, Hua [1 ]
Zhu, Yuxin [1 ]
Wang, Jinghao [1 ]
Han, Hubiao [1 ]
Niu, Jiqiang [2 ]
Chen, Xueye [3 ]
机构
[1] Zhengzhou Univ Light Ind, Sch Comp & Commun Engn, Zhengzhou, Peoples R China
[2] Xinyang Normal Univ, Key Lab Synergist Prevent Water & Soil Environm P, Xinyang, Peoples R China
[3] Minist Nat Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen, Peoples R China
来源
PLOS ONE | 2022年 / 17卷 / 04期
基金
中国国家自然科学基金;
关键词
COVER CHANGE; SOUTH; CHINA;
D O I
10.1371/journal.pone.0265613
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 approximate to 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 approximate to-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.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Spatial Differentiation Pattern and Influencing Factors of Cultivated Land Quality in Jinzhong City
    Liu, Huifang
    Bi, Rutian
    Guo, Yonglong
    Wang, Jin
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2021, 52 (12): : 216 - 224
  • [2] Spatiotemporal variation, influencing factors and spatial spillover of cultivated land multifunction in Zhejiang Province
    Chen, Sha
    Yang, Runjia
    Li, Guan
    [J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2022, 38 (16): : 21 - 32
  • [3] Exploring the spatial distribution and influencing factors of soil PH value of cultivated land in Sichuan Province
    Li Wang
    Wenying Xiong
    Hang Chen
    Fei Meng
    Yongzhong Tan
    [J]. Environmental Earth Sciences, 2024, 83
  • [4] Exploring the spatial distribution and influencing factors of soil PH value of cultivated land in Sichuan Province
    Wang, Li
    Xiong, Wenying
    Chen, Hang
    Meng, Fei
    Tan, Yongzhong
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2024, 83 (01)
  • [5] Spatial distribution and influencing factors of rural tourism: A case study of Henan Province
    Du, Jiusheng
    Zhao, Beibei
    Feng, Yunchao
    [J]. HELIYON, 2024, 10 (07)
  • [6] Spatial Differentiation Characteristics and Influencing Factors of Cultivated Land Planting Structure in Typical Counties of Heilongjiang Province
    Zhang, Hongmei
    Song, Ge
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2021, 52 (05): : 239 - 248
  • [7] Temporal and Spatial Differentiation in Urban Resilience and Its Influencing Factors in Henan Province
    Liu, Lu
    Luo, Yun
    Pei, Jingjing
    Wang, Huiquan
    Li, Jixia
    Li, Ying
    [J]. SUSTAINABILITY, 2021, 13 (22)
  • [8] Spatial Zoning of Cultivated Land in Shandong Province Based on the Trinity of Quantity, Quality and Ecology
    Wang, Nan
    Zu, Jian
    Li, Mu
    Zhang, Jinyi
    Hao, Jinmin
    [J]. SUSTAINABILITY, 2020, 12 (05) : 1 - 20
  • [9] Prime Cropland Assignment Based on Cultivated Land Quality Evaluation and Spatial Cluster Pattern
    Dong, Guanglong
    Zhao, Xuan
    Liu, Jinhua
    Zheng, Xinqi
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2020, 51 (02): : 133 - 142
  • [10] Spatial Pattern Characteristics and Influencing Factors of Green Use Efficiency of Urban Construction Land in Jilin Province
    Yu, Huisheng
    Song, Ge
    Li, Tong
    Liu, Yanjun
    [J]. COMPLEXITY, 2020, 2020