Abstract
Landscape patterns and ecological processes have been in long-term research focus in the field of landscape ecology, but how to measure their quantitative relations is still open. This work chooses the Hulunbeier grassland as the study area where ecosystem shows high vulnerability, frequent evolvement of landscape patterns and ecological processes. With remote sensing technology, the relationships between landscape patterns and ecological processes were analyzed quantitatively from multi-scale, multi-temporal and time series perspective. Firstly, the information about the current situation and change of landscape patterns and ecological processes are obtained from HJ-1 (Environmental and Disaster Small Satellite) and LANDSAT TM (Thermal Mapper) data. Secondly, SPOT NDVI (Normalized Difference Vegetation Index) data during 2000–2008 are used to analyze the dynamic changes of ecological processes, and to simulate its inter-annual variety at pixel scale. Finally, the dynamic change trends of ecological processes of grassland vegetation are described. The results indicate that the unchanged ecosystem types account for most of the study area, unused land in the central part expands continuously which results in the increase of desertification, and most ecosystem types in the eastern part are changed to grassland and woodland. Furthermore, the vegetation vulnerability is the highest in the grassland-dominated region, the second in grassland–farmland–woodland transition, and the smallest in the woodland-dominated region, where the stability is enhanced in turn. Due to the dynamic change of vegetation, it can be concluded that the study area underwent ecological processes of vegetation cover with a negative trend and a changed phenology.
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The study is funded by the National Natural Science Foundation of China (40801072 and 41101313). The authors are grateful to the fruitful comments by the editors and anonymous reviewers.
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Zhang, F., Li, Y., Liu, S. et al. Dynamic monitoring of landscape patterns and ecological processes using HJ-1 and SPOT satellite data over Hulunbeier grassland, China. J Earth Syst Sci 123, 319–328 (2014). https://doi.org/10.1007/s12040-014-0403-6
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DOI: https://doi.org/10.1007/s12040-014-0403-6