Research of Spatial Pattern for Cultivated Land Quality in Henan Province Based on Spatial Autocorrelation

Wang, Hua; Zhu, Yuxin; Wang, Mengyu; Wang, Yifan; Chen, Xueye

doi:10.1007/978-3-030-78609-0_37

Cited by 1 publication

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“…(where Q represents the sample area, A denotes the study area, and n stands for the number of study area points), and to the proportional relationship between the study area and the scale selection by previous authors [23,24]. On this basis, 500 m×500 m was set as the basic study scale and GIS software was applied to convert the land use data into the five raster scales as required for the study: 1 km, 5 km, 10 km, 20 km, and 30 km.…”

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confidence: 99%

Comparative Spatial Distribution Simulation of Plateau Mountain Cultivated Land Based on Spatial Multi-Scale Model, Yunnan Central Urban Agglomeration Area, China

Chen¹

2023

Pol. J. Environ. Stud.

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Land use is highly dependent on scale and heterogeneous, serving as an important tool to examine land use change by comparing spatial multi-scale cultivated land models through an appropriate simulation model. In the present study, such indicators as the goodness of fit, the spatial auto-correlation of residuals, the number of factors and spatial scale are adopted to compare the variability and accuracy of four spatial multi-scale models: OLS (Ordinary Least Squares), SL (Spatial Lag), SE (Spatial Error) and GWR (Geographically Weighted Regression). According to the global characteristics, there is a positive autocorrelation between the distribution of cropland and the driving factors at multiple spatial scales and they are relatively sensitive to the sampling scale. According to the local characteristics, the smaller the spatial scale, the more accurate the spatial location of regional cropland aggregation. The order of merit of models characterizing the local spatial pattern and distribution pattern of cultivated land at the scale of plateau urban clusters is as follows: GWR, spatial error model, spatial lag model, and OLS. The GWR performs better in characterizing local spatial features, simulation accuracy and driving factor coefficients. Besides, the CLUE-S simulation model improved by GWR Logistic is more accurate in characterizing the spatial pattern of local land use and its distribution pattern at the scale of urban clusters in the plateau region.

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Section: Author Copy • Author Copy • Author Copy • Author Copy • Auth...mentioning

confidence: 99%

Comparative Spatial Distribution Simulation of Plateau Mountain Cultivated Land Based on Spatial Multi-Scale Model, Yunnan Central Urban Agglomeration Area, China

Chen¹

2023

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

Research of Spatial Pattern for Cultivated Land Quality in Henan Province Based on Spatial Autocorrelation

Cited by 1 publication

References 2 publications

Comparative Spatial Distribution Simulation of Plateau Mountain Cultivated Land Based on Spatial Multi-Scale Model, Yunnan Central Urban Agglomeration Area, China

Comparative Spatial Distribution Simulation of Plateau Mountain Cultivated Land Based on Spatial Multi-Scale Model, Yunnan Central Urban Agglomeration Area, China

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