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Chen, J; Quan, WT; Lu, K (2012). Remote Sensing of Eupatorium Adenophorum Spreng Based on HJ-A Satellite Data. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 40(1), 29-36.

In the southwest of China, one of the greatest threats to local ecosystem is the area expansion of an invasive species, i.e., Eupatorium adenophorum Spreng (EAS). In this study, the remote-sensing technology was used to detect and map the spatial distribution of EAS in Guizhou Province, China. A series of vegetation indices, including normalized difference vegetation index (NDVI), simple ratio index (SRI) and atmospherically resistant vegetation index (ARVI), were used to identify EAS from HJ-A Chninese satellite data. According to the analysis results of fieldworks from March 21 to 22, 2009, it was found that the vegetation index of {1.9589 a parts per thousand currency signaEuro parts per thousand SRI a parts per thousand currency signaEuro parts per thousand 4.1095}a (c){0.2359 a parts per thousand currency signaEuro parts per thousand ARVI a parts per thousand currency signaEuro parts per thousand 0.5193} was the optimal remote-sensing parameter for identifying EAS from HJ-A data. According to the spatial distribution of EAS estimated from HJ-A data, it was found that EAS was rather more in southwest of Guizhou Province than in northeast. EAS became sparse from southwest to northeast gradually, and the central Guizhou Province was the ecological corridor linking EAS in southwest to that in northeast. By comparison with validated data collected by the government of Guizhou Province, it was found that the uncertainty of remote-sensing method was 18.52%, 29.31%, 8.77% and 9.46% in grassland, forest, farmland and others respectively, and the mean uncertainty was 13.29%. Owing to the lower height of EAS than many plants in forest, the uncertainty of EAS was the greatest in forest than that in grassland, farmland and so on.



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