Frontiers of Earth Science

, Volume 6, Issue 4, pp 445–452

Spatial disparities of regional forest land change based on ESDA and GIS at the county level in Beijing-Tianjin-Hebei area

Research Article

DOI: 10.1007/s11707-012-0338-7

Cite this article as:
Xie, H., Kung, CC. & Zhao, Y. Front. Earth Sci. (2012) 6: 445. doi:10.1007/s11707-012-0338-7


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.


land use changeforest landspatial autocorrelationESDAGISBeijing-Tianjin-Hebei area

Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of Poyang Lake Eco-economicsJiangxi University of Finance and EconomicsNanchangChina
  2. 2.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina