YIC-IR  > 海岸带信息集成与战略规划研究中心
Effects of Time-Duration on the Performance of the Spatial-Markov Model for Land use Change Forecasting
Hou, Xi-Yong; Wu, Li; Lu, Xiao; Di, Xiang-Hong; Hou, XY (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res YIC, 17 ChunHui Rd, Laishan Dist 264003, Yantai, Peoples R China. xyhou@yic.ac.cn
2015-06-01
Source PublicationJOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
ISSN0255-660X
Volume43Issue:2Pages:287-295
Contribution Rank[Hou, Xi-Yong; Lu, Xiao] Chinese Acad Sci, Yantai Inst Coastal Zone Res YIC, Laishan Dist 264003, Yantai, Peoples R China; [Wu, Li] Henan Inst Engn, Coll Civil Engn, Zhengzhou 451191, Henan, Peoples R China; [Di, Xiang-Hong] Dezhou Univ, Coll Resources Environm & Planning, Dezhou 253023, Shandong, Peoples R China
AbstractMarkov chain is one of the most widely used methods for land use change forecasting, however, it's a non-spatial model and few papers have discussed the effects of time-duration on its performance. In this paper, we first present the primary methodologies of the Spatial-Markov model, which endows the ordinary Markov chain with spatial dimension using spatial analysis techniques, and then explore the effects of forecasting time-duration on the model's performance. By taking Shandong province, China as a case study area, land use maps in 1990, 1995, 2000, 2005 and 2010 were created using on Landsat images and then the Spatial-Markov model was developed at 1 km spatial scale. In detail, we repeatedly run the model by choosing different initial time points and the same time step (five year interval) to simulate the spatial-temporal dynamics of land use change from 1990 to 2010. The forecasting results of a single run included a stack of ratio scale images and a derived nominal scale image, chi(2) test and Kappa coefficient were adopted to evaluate their accuracy respectively. It turned out that the Spatial-Markov model could achieve very good performance for short period forecasting. For the case study, it was quite qualified for the prediction of three time steps (up to 15 years) or more within which the results had much high reliability, however, time-duration of forecasting had much significant impact on the model's performance, the longer the forecasting duration, the lower the model's accuracy.; Markov chain is one of the most widely used methods for land use change forecasting, however, it's a non-spatial model and few papers have discussed the effects of time-duration on its performance. In this paper, we first present the primary methodologies of the Spatial-Markov model, which endows the ordinary Markov chain with spatial dimension using spatial analysis techniques, and then explore the effects of forecasting time-duration on the model's performance. By taking Shandong province, China as a case study area, land use maps in 1990, 1995, 2000, 2005 and 2010 were created using on Landsat images and then the Spatial-Markov model was developed at 1 km spatial scale. In detail, we repeatedly run the model by choosing different initial time points and the same time step (five year interval) to simulate the spatial-temporal dynamics of land use change from 1990 to 2010. The forecasting results of a single run included a stack of ratio scale images and a derived nominal scale image, chi(2) test and Kappa coefficient were adopted to evaluate their accuracy respectively. It turned out that the Spatial-Markov model could achieve very good performance for short period forecasting. For the case study, it was quite qualified for the prediction of three time steps (up to 15 years) or more within which the results had much high reliability, however, time-duration of forecasting had much significant impact on the model's performance, the longer the forecasting duration, the lower the model's accuracy.
KeywordLand Use Change Markov Chain Spatial-markov Time Duration Ratio Scale Nominal Scale
Department海岸带信息集成与综合管理实验室
Subject AreaEnvironmental Sciences ; Remote Sensing
DOI10.1007/s12524-014-0400-x
Funding OrganizationEnvironmental Sciences & Ecology ; Remote Sensing
Indexed BySCI
WOS KeywordUSE/LAND COVER CHANGE ; REMOTE-SENSING DATA ; URBAN EXPANSION ; CHINA ; DYNAMICS ; GROWTH ; REGION ; AREA ; GIS
SubtypeArticle
Language英语
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing
WOS IDWOS:000354894500008
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.yic.ac.cn/handle/133337/8586
Collection海岸带信息集成与战略规划研究中心
Corresponding AuthorHou, XY (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res YIC, 17 ChunHui Rd, Laishan Dist 264003, Yantai, Peoples R China. xyhou@yic.ac.cn
Recommended Citation
GB/T 7714
Hou, Xi-Yong,Wu, Li,Lu, Xiao,et al. Effects of Time-Duration on the Performance of the Spatial-Markov Model for Land use Change Forecasting[J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,2015,43(2):287-295.
APA Hou, Xi-Yong,Wu, Li,Lu, Xiao,Di, Xiang-Hong,&Hou, XY .(2015).Effects of Time-Duration on the Performance of the Spatial-Markov Model for Land use Change Forecasting.JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,43(2),287-295.
MLA Hou, Xi-Yong,et al."Effects of Time-Duration on the Performance of the Spatial-Markov Model for Land use Change Forecasting".JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 43.2(2015):287-295.
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