A Study on Influencing Factors of Cultivated Land Based on Multivariate Regression and Spatial Statistics-A Case Study of Shizhu County, Chongqing City

HE Changhua; CHEN Dan; LI Tianguo; LI Hui; XU Xiaojun

doi:10.13961/j.cnki.stbctb.2017.02.031

您当前的位置：

首页 >

文章列表页 >

A Study on Influencing Factors of Cultivated Land Based on Multivariate Regression and Spatial Statistics-A Case Study of Shizhu County, Chongqing City

- A Study on Influencing Factors of Cultivated Land Based on Multivariate Regression and Spatial Statistics-A Case Study of Shizhu County, Chongqing City
- Bulletin of Soiland Water Conservation Vol. 37, Issue 2, Pages: 199-206(2017)
- 作者机构：
  
  1. 昆明理工大学环境科学与工程学院,云南,昆明,650500
  2. 重庆工商大学融智学院,重庆,400067
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2017.02.031
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
HE Changhua, CHEN Dan, LI Tianguo, et al. A Study on Influencing Factors of Cultivated Land Based on Multivariate Regression and Spatial Statistics-A Case Study of Shizhu County, Chongqing City[J]. Bulletin of Soiland Water Conservation, 2017, 37(2): 199-206.
DOI：

HE Changhua, CHEN Dan, LI Tianguo, et al. A Study on Influencing Factors of Cultivated Land Based on Multivariate Regression and Spatial Statistics-A Case Study of Shizhu County, Chongqing City[J]. Bulletin of Soiland Water Conservation, 2017, 37(2): 199-206. DOI： 10.13961/j.cnki.stbctb.2017.02.031.

摘要

[目的

]

通过空间自相关和多元回归分析，揭示耕地空间分布规律，为土地开发复垦及整理提供快速的评价方法。[方法

]

以耕地面积占比为空间变量，运用空间自相关及马塞克图分析耕地分布整体特征，通过距离、地形、NDWI和人口密度共9个因素对耕地空间分布进行多元回归分析，模拟耕地分布适宜性并进行了检验。[结果

]

空间自相关分析结果表明，距离和地形因素对耕地空间分布具有显著影响，空间自相关分析Moran's I值为0.701 5，研究区耕地分布主要为不显著、LL（低空间自相关）和HH（高空间自相关）类型，其中不显著类型占研究区总面积的65%以上；基于多远回归分析结果表明：回归模型具有较高拟合优度和可靠性（R

=0.846），模拟得到的耕地分布适宜性图与现有耕地分布基本吻合。[结论

]

研究区耕地空间分布总体上呈现较强的正相关关系，且受距离、地形因素影响明显；回归模型能够较好地揭示研究区耕地空间分布规律；研究区具有一定耕地补充潜力；将回归模型应用于土地开发复垦以及整理工作中，有利于提高补充耕地质量，减弱水土流失以及优化区域土地结构。

Abstract

[Objective] We aimed to reveal the regularity of spatial distribution of cultivated land by spatial autocorrelation analysis and multivariable regression

in order to provide a rapid evaluation method for land development

reclamation

and consolidation. [Methods] Coverage ratio by cultivated land was as response variable

and methods of spatial autocorrelation and mosaic plot were utilized to demonstrate its spatial pattern. Nine factors such as Euclidean distances

terrain

NDWI

population density

simulated cultivated land distribution suitability

etc. were used as independent variables

and multivariate regression of them with the response variable was conducted to test the distributional suitability of cultivated land. [Results] The Euclidean distances and terrain have significant impacts on the spatial distribution of cultivated land

and the Moran's I index is 0.701 5. In addition

the main types of local indicators of spatial association(LISA) distribution are not significant. L-L(low spatial autocorrelations) and H-H(high spatial autocorrelations) and insignificant types are three of the main types

especially the third type covered over 65% of study area. Multivariate regression behaved well in the distribution suitability simulation of cultivated land

it was remarkably coincided with the present distribution of cultivated land. The regression model was testified reliable and had goodness of fit (R2=0.846). [Conclusion] (1) The spatial distribution of cultivated land in the study area generally exhibits a strong positive correlation. And the distribution of cultivated land is affected by distance and terrain significantly. (2) The regression model can well reveal the spatial distribution of cultivated land in the study area

showing that the study area has a potential for cultivated land supplement. (3) We can improve the quality of additional cultivated land

reduce soil erosion

and optimize the land utilization structure if under the guidance of the regression model for land development

reclamation and consolidation.

关键词

Keywords

references

沈仁芳,陈美军,孔祥斌,等.耕地质量的概念和评价与管理对策[J].土壤学报,2012,49(6):1210-1217.

蔡海生,林建平,朱德海.基于耕地质量评价的鄱阳湖区耕地整理规划[J].农业工程学报,2007,23(5):75-80.

李子良,王树涛,张利,等.经济快速发展地区耕地生产能力空间格局[J].农业工程学报,2010,26(11):323-331.

韦仕川,熊昌盛,栾乔林,等.基于耕地质量指数局部空间自相关的耕地保护分区[J].农业工程学报,2014,30(18):249-256.

邵子南,王怀成,陈江龙,等.中国农村居民点整理研究进展与展望[J].中国农业资源与区划,2013,34(3):10-15.

Coelho J C, Portela J, Pinto P A. A social approach to land consolidation schemes:A Portuguese case study:The valenca Project[J]. Land Use Policy, 1996,13(2):129-147.

王军,严慎纯,白中科,等.土地整理的景观格局与生态效应研究综述[J].中国土地科学,2012,26(9):87-94.

Petr Sklenicka. Applying evaluation criteria for the land consolidation effect to three contrasting study areas in Czech Republic[J]. Land Use Policy, 2006,23(4):502-510.

张正峰,赵伟.土地整理的资源与经济效益评估方法[J].农业工程学报,2011,27(3):295-299.

赵登辉,郭川.对耕地定级与估价几个问题的思考[J].中国土地,1997,11(12):18-19.

奉婷,张凤荣,李灿,等.基于耕地质量综合评价的县域基本农田空间布局[J].农业工程学报,2014,30(1):200-210.

孙蕊,孙萍,吴金希,等.中国耕地占补平衡政策的成效与局限[J].中国人口·资源与环境,2014,24(3):41-46.

Overmars K P, Koning G H J D, Veldkamp A. Spatial autocorrelation in multi-scale land use models[J]. Ecological Modelling, 2003,164(2/3):257-270.

沈陈华.丹阳市农村居民点空间分布尺度特征及影响因素分析[J].农业工程学报,2012,28(22):261-268.

陈丹,周启刚,何昌华,等.基于MPI的典型西南山区耕地空间分布影响因素研究:以重庆石柱县为例[J].水土保持研究,2014,21(2):228-233.

杨沁汶,安祺,谢莹,等.基于GIS的重庆市石柱县土地利用现状分析[J].重庆工商大学学报:自然科学版,2012,29(12):87-94.

郭洪峰,许月卿,吴艳芳.基于地形梯度的土地利用格局与时空变化分析:以北京市平谷区为例[J].经济地理,2013,33(1):160-166.

Kabacoff R. R in Action:Data Analysis and Graphics with R[M]. Pearson Schweiz Ag:Manning Publications Co.,2015.

Hornik K, Zeileis A, Meyer D. The strucplot framework:Visualizing multi-way contingency tables with vcd[J]. Journal of Statistical Software, 2006,17(3):1-48.

Tobler W R. A computer movie simulating urban growth in the Detroit region[J]. Economic geography, 1970,46(2):234-240.

Verburg P H, Chen Y Q. Multiscale characterization of land-use patterns in China[J]. Ecosystems, 2000,3(4):369-385.

Anselin L, Syabri I, Kho Y. GeoDa:An introduction to spatial data analysis[J]. Geographical Analysis, 2006,38(1):5-22.

孟斌,王劲峰,张文忠,等.基于空间分析方法的中国区域差异研究[J].地理科学,2005,25(4):393-400.

Anselin L. Local indicators of spatial association:LISA[J]. Geographical Analysis, 1995,27(2):93-115.

Reshef D N, Reshef Y A, Finucane H K, et al. Detecting novel associations in large data sets[J]. Science, 2011,334(6062):1518-1524.

Zhang Yi, Jia Shili, Huang Haiyun, et al. A Novel algorithm for the precise calculation of the maximal information coefficient[J]. Scientific Reports, 2014, 4(4):6662.

项静恬,郭世琪.多元回归模型在实际应用中的几种推广[J].数理统计与管理,1994,13(4):48-53.

徐嘉兴,李钢,陈国良.基于Logistic回归模型的矿区土地利用演变驱动力分析[J].农业工程学报,2012,28(20):247-255.

Views

1464

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Spatio-temporal evolution of coupling coordination between urban resilience and land use efficiency in Guangdong Province from 2013 to 2022

Analyzing Regional Pattern of Cultivated Land Change on County Scale in Jiangxi Province

Effects of Landuse on Ecological Restoring Force in Qinling Mountainous Region

Spatio-temporal Variations of Soil Erosion and Its Spatial Autocorrelation Analysis in Source Area of Fenhe River

Research on Soil and Water Conservation Zonation Based on Method of Spatial Autocorrelation -A Case Study in Black Soil Region of Northeast China

Related Author

Peng Liyao

Xiao Zhi

ZHU Chuan-min

HUANG Ya-dan

WU Jia

PENG Qiong

YANG Hai-juan

WEN Xiao-jin

Related Institution

School of Natural Resources and Surveying, Nanning Normal University

College of Geosciences, Digital Land Key Laboratory of Jiangxi Province, East China Institute of Technology

Urban and Rural Planning and Design Institute of Shaanxi Province, Xian

College of Tourism and Environment Sciences, Shaanxi Normal University, Xian

College of Urban and Environmental Sciences, Northwest University, Xian

⁰