| Technology and Methodology |
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A Comparative Study of Different Vegetation Indices for Estimating Vegetation Coverage Based on the Dimidiate Pixel Model |
| XU Shuang1,2, SHEN Run-ping1, YANG Xiao-yue1,2 |
1. Key Laboratory of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. College of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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Abstract ASD Field Spec Pro FRTM spectroradiometer was used to measure the spectral response of the vegetable and grass at different vegetation coverage levels. The data were applied to calculate six vegetation indices, i.e., NDVI (normalized difference vegetation index), DVI (difference vegetation index), RVI (ratio vegetation index), MVI (modified vegetation index), MSAVI (modified soil adjusted vegetation index) and GEMI (global environment monitoring index). Then the best combination of spectral bands was analyzed. Furthermore, the performance of different vegetation indices was investigated when they were used to estimate the vegetation coverage by using the dimidiate pixel model. The results show that, for the green vegetable, the best combinations of bands in the spectral region from 620 to 740 nm and from 780 to 900 nm have the best correlation with the vegetation index, whereas for the grass, the best combinations of bands are from 620 to 750 nm and from 760 to 900 nm, with the correlation coefficients of the two cases being all larger than 0.8. The bands of Landsat7 and HJ-1A CCD1 simulated according to the spectral response function were employed to calculate the six vegetation indices. The average overall accuracy for estimating the vegetation fraction by DVI and MSAVI is 83.7% and 79.5% respectively, indicating that they are superior to the other four vegetation indices as the input of vegetation index for the dimidiate pixel model.
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| Keywords
passive microwave remote sensing
land surface emissivity
retrieving approach
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Issue Date: 13 November 2012
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2012,
Vol. 24
