Analyzing spatiotemporal changes in land use and land cover could provide basic information for appropriate decision-making and thereby plays an essential role in promoting the sustainable use of land resources, especially in ecologically fragile regions. In this paper, a case study was taken in Zhenlai County, which is a part of the farming-pastoral ecotone of Northern China. This study integrated methods of bitemporal change detection and temporal trajectory analysis to trace the paths of land cover change for every location in the study area from 1954 to 2005, using published land cover data based on topographic and environmental background maps and also remotely sensed images including Landsat MSS (Multispectral Scanner) and TM (Thematic Mapper). Meanwhile, the Lorenz curve and Gini coefficient derived from economic models were also used to study the land use structure changes to gain a better understanding of human impact on this fragile ecosystem. Results of bitemporal change detection showed that the most common land cover transition in the study area was an expansion of arable land at the expense of grassland and wetland. Plenty of grassland was converted to other unused land, indicating serious environmental degradation in Zhenlai County during the past decades. Trajectory analysis of land use and land cover change demonstrated that settlement, arable land, and water bodies were relatively stable in terms of coverage and spatial distribution, while grassland, wetland, and forest land had weak stability. Natural forces were still dominating the environmental processes of the study area, while human-induced changes also played an important role in environmental change. In addition, different types of land use displayed different concentration trends and had large changes during the study period. Arable land was the most decentralized, whereas forest land was the most concentrated. The above results not only revealed notable spatiotemporal features of land use and land cover change in the time series, but also confirmed the applicability and effectiveness of the methodology in our research, which combined bitemporal change detection, temporal trajectory analysis, and a Lorenz curve/Gini coefficient in analyzing spatiotemporal changes in land use and land cover.
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