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Frontiers of Earth Science

Front Earth Sci    2012, Vol. 6 Issue (4) : 445-452     DOI: 10.1007/s11707-012-0338-7
Spatial disparities of regional forest land change based on ESDA and GIS at the county level in Beijing-Tianjin-Hebei area
Hualin XIE1(), Chih-Chun KUNG1, Yuluan ZHAO2
1. Institute of Poyang Lake Eco-economics, Jiangxi University of Finance and Economics, Nanchang 330013, China; 2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Forest land is the essential and important natural resource that provides strong support for human survival and development. Research on forest land changes at the county level about its characteristics, rules, and spatial patterns is, therefore, important for regional resource protection and the sustainable development of the social economy. In this study we selected the GIS and Geoda software package to explore the spatial disparities of forest land changes at the Beijing-Tianjin-Hebei area county level, based on the global and local spatial autocorrelation analyses of exploratory spatial data. The results show that: 1) during 1985–2000, the global spatial autocorrelation of forest land change is significant in the study area. The global Moran’s I value is 0.3122 for the entire time period and indicates significant positive spatial correlation (p<0.05). Moran’s I value of forest land change decreases from 0.3084 at the time stage I to 0.3024 at the time stage II; 2) the spatial clustering characteristics of forest land changes appear on the whole in Beijing-Tianjin-Hebei area. Moran’s I value decreases from the time stage I to time stage II, which means that trend of spatial clustering of forest land change is weakened in the Beijing-Tianjin-Hebei area; 3) the grid map of the local Moran’s I for each county reflects local spatial homogeneity of forest land change, which means that spatial clustering about regions of high value and low value is especially significant. The regions with “High-High” correlation are mainly located in the north hilly area. However, the regions with “Low-Low” correlation were distributed in the middle of the study area. Therefore, protection strategies and concrete measures should be put in place for each regional cluster in the study area.

Keywords land use change      forest land, spatial autocorrelation, ESDA, GIS, Beijing-Tianjin-Hebei area     
Corresponding Authors: XIE Hualin,   
Issue Date: 05 December 2012
 Cite this article:   
Hualin XIE,Chih-Chun KUNG,Yuluan ZHAO. Spatial disparities of regional forest land change based on ESDA and GIS at the county level in Beijing-Tianjin-Hebei area[J]. Front Earth Sci, 2012, 6(4): 445-452.
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Hualin XIE
Chih-Chun KUNG
Yuluan ZHAO
Fig.1  Study area
Fig.2  Land use of study area in 1985, 1995 and 2000
Land use type198519952000
Arable land11220751.9910160347.0110217547.31
Forest land4456720.655974527.655978427.68
Grass land3568916.542770412.822770412.83
Construction land147046.81177128.20170857.91
Other land9640.4528601.3227271.26
Tab.1  Land use changes in the Beijing-Tianjin-Hebei area from 1985 to 2000
Time stageYearMoran’s IE(I)ZscoreThreshold value(p&lt;0.05)
Time stage I1985-19950.3084-0.00537.381.96
Time stage II1995-20000.3024-0.00537.161.96
Time stage III1985-20000.3122-0.00537.331.96
Tab.2  Global Moran’s value and its statistic test for forest land changes at county level in Beijing-Tianjin-Hebei area from 1985 to 2000
Time stageMinimumMaximumMeanMoran’s Ii(+)Moran’s Ii(-)Range
Time stage I-2.511211.96670.508884.12715.87314.4779
Time stage II-3.728812.38710.397870.37129.62916.1159
Time stage III-2.458811.95690.514684.12715.87314.4157
Tab.3  Related parameters for local Moran’s of forest change at county level from 1985 to 2000 in Beijing-Tianjin-Hebei Area
Fig.3  Spatial differentiation about Local Moran’s for index of forest land changes at county level in the Beijing-Tianjin-Hebei area
Fig.4  Moran scatter plot of forest land changes at county level in the Beijing-Tianjin-Hebei area during 1985-2000
Time stageRatioH-HH-LL-LL-H
Std-Iclc&gt;0Std-Iclc&lt;0Lag-Iclc&gt;0Lag-Iclc&lt;0Comparison ratioRatioComparison ratioRatioComparison ratioRatioComparison ratioRatio
I21.1678.8431.7568.25S+L+17.98S+L-3.7S- L-64.55S-L+13.76
II50.7949.2144.4455.56S+L+32.27S+L-19.05S- L-36.51S-L+12.17
III21.6978.3132.2867.72S+L+17.98S+L-3.7S- L64.55S-L+13.76
Tab.4  Related parameters and disparities type of standardized variable for forest land changes at county level in Beijing-Tianjin-Hebei area/%
Fig.5  LISA clustering of forest land changes at county lever in Beijing-Tianjin-Hebei area
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