IGSNRR OpenIR
comparisonofspatialautoregressivemodelsonmultiscalelanduse
Chen Xiwei1; Dai Erfu2
2011
Source Publication农业工程学报
ISSN1002-6819
Volume27Issue:6Pages:324
AbstractAs a case study on the Huadu district of Guangzhou city,this paper compared classical linear regression model,spatial lag model (SLM)and spatial error model (SEM)through the Lagrange Multiplier (LM)and goodness-of-fit (GOF)tests,in terms of their explanatory power and applicability on land use at different scales.The results showed:1)The residuals of the classical linear regression models were proved its positive autocorrelation,which were weaker than those of the original land use data,this indicated that classical linear regression model could partially explain the spatial layout but could not capture all spatial dependency in the land use data;2)With higher GOF,the SLMs and SEMs could better diminish the spatial autocorrelation than the linear regression model;3)Land use at different scales required different optimal autoregressive models,i.e.the specific model had the character of scale dependency.
Language英语
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/127633
Collection中国科学院地理科学与资源研究所
Affiliation1.Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences
2.中国科学院地理科学与资源研究所
Recommended Citation
GB/T 7714
Chen Xiwei,Dai Erfu. comparisonofspatialautoregressivemodelsonmultiscalelanduse[J]. 农业工程学报,2011,27(6):324.
APA Chen Xiwei,&Dai Erfu.(2011).comparisonofspatialautoregressivemodelsonmultiscalelanduse.农业工程学报,27(6),324.
MLA Chen Xiwei,et al."comparisonofspatialautoregressivemodelsonmultiscalelanduse".农业工程学报 27.6(2011):324.
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