Vegetation classification of East China with multi-temporal NOAA-AVHRR data |
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Authors: | Li Junxiang Liangjun Da Yujie Wang and Yongchang Song |
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Institution: | (1) Department of Environmental Science, East China Normal University, Shanghai, 200062, China |
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Abstract: | East China lies in the subtropical monsoon climatic zone and is dominated by subtropical evergreen broad-leaved forests, a
unique vegetation type mainly distributed in East Asia with the largest distribution in China. It is important to be able
to monitor and estimate forest biomass and production, regional carbon storage, and global climate change impacts on these
important vegetation types. In this paper, we used coarse resolution remote sensing data to identify the vegetation types
in East China and developed a map of the spatial distribution of vegetation types in this region. Nineteen maximum normalized
difference vegetation index (NDVI) composite images (acquisition time span of 7 months from February to August), which were
derived from 10 days National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer
(AVHRR) channel 1 and channel 2 observations, an unsupervised classification method, and the ISODATA algorithm were employed
to identify the vegetation types. To reduce the dimensions of the dataset resulted in a total of 28 spectral clusters of land-cover
of which two clusters were urban/bare soil and water, the images were processed using principal component analysis (PCA).
The 26 remaining spectral clusters were merged into six vegetation types using the Chinese vegetation taxonomy system: evergreen
broad-leaved forest, coniferous forest, bamboo forest, shrub-grass, aquatic vegetation, and agricultural vegetation. The spatial
distribution and areal extent for the coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation
were calculated and compared with the Vegetation Atlas of China at a 1:1,000,000 scale. The spatial accuracy and the area
accuracy for coniferous forests, shrub-grass, evergreen broad-leaved forests, and agricultural vegetation were 79.2%, 91.3%,
68.2% and 95.9% and 92.1%, 95.9%, 63.8% and 90.5%, respectively. The spatial accuracy and area accuracy of the bamboo forest
were 28.7% and 96.5%, respectively; the spatial accuracy of aquatic vegetation was 69.6%, but there was a significant difference
in its area accuracy because image acquisition did not cover the full year. Our study demonstrated the feasibility of using
NOAA-AVHRR to identify the different vegetation types in the subtropical evergreen broad-leaved forest zone in East China.
The spatial location of the six identified vegetation types agreed with the actual geographical distribution of the vegetation
types in East China.
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Translated from Acta Phytoecologica Sinica, 2005, 29(3): 436–443 译自: 植物生态学报, 2005, 29(3): 436–443] |
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Keywords: | vegetation classification remote sensing NDVI principal component analysis East China |
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