Literature DB >> 23774750

An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

Yueqing Xu1, Paul McNamara, Yanfang Wu, Yue Dong.   

Abstract

Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Keywords:  Arable land; Dynamic change; Econometric model; Pinggu district of Beijing

Mesh:

Substances:

Year:  2013        PMID: 23774750     DOI: 10.1016/j.jenvman.2013.05.020

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

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Authors:  Chao Liu; Yueqing Xu; Piling Sun; An Huang; Weiran Zheng
Journal:  Environ Monit Assess       Date:  2017-09-14       Impact factor: 2.513

2.  Genome-wide analysis of the cotton G-coupled receptor proteins (GPCR) and functional analysis of GTOM1, a novel cotton GPCR gene under drought and cold stress.

Authors:  Pu Lu; Richard Odongo Magwanga; Joy Nyangasi Kirungu; Qi Dong; Xiaoyan Cai; Zhongli Zhou; Xingxing Wang; Yanchao Xu; Yuqing Hou; Renhai Peng; Kunbo Wang; Fang Liu
Journal:  BMC Genomics       Date:  2019-08-14       Impact factor: 3.969

  2 in total

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