首页|Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

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Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes,ecology and the environment.At the pixel level,logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change,and thereby to evaluate land use suitability.However,these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors.Consequently,a multinomial logistic regression method was introduced to address this flaw,and thereby,judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province,China.A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98％,which was 8.47％ higher than that obtained using logistic regression.Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression.In conclusion,multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes.The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes,ecology,and environment.

multinomial logistic regressionland use changelogistic regressionland use suitabilityland use allocation

Yingzhi LIN、Xiangzheng DENG、Xing LI、Enjun MA

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School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China

Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China

National Basic Research of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

2010CB9509007122500541071343

2014

10.1007/s11707-014-0426-y

地球科学前沿
高等教育出版社

地球科学前沿

CSCDSCI
影响因子：0.585
ISSN：2095-0195
年,卷(期)：2014.8(4)
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