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Assessing factors influencing vegetation coverage calculation with remote sensing imagery

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Influencing factor analysis is required for assessing the performance of vegetation fractional coverage (VFC) models with remote sensing imagery. This paper analyses influences of the radiometric correction level (RL), vegetation index (VI) and polynomial exponential power (EP) choice on VI-VFC relationship models. A SPOT 5 HRG image of Nanjing, China was chosen, and three RLs (digital number, top of atmosphere reflectance and post atmospheric correction reflectance) were used to derive six VIs, such as normalized difference vegetation index (NDVI) and ratio vegetation index (RVI). Fifty-four models describing the VI-VFC relationship were established, and the influences of the RL, VI and EP choice on the VI-VFC models were analysed based on a statistical analysis of determination coefficients (R 2) of these models. The results showed that model robustness was jointly influenced by the three factors, so these three factors should be synthetically taken into account in VI-VFC modelling. It is recommended to establish different models between the VFC and various VIs derived from different RLs, and then to select the better ones.
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Document Type: Research Article

Affiliations: 1: College of Geography Science, Nanjing Normal University, Nanjing 210097, China 2: State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China,Graduate University of Chinese Academy of Sciences, Beijing 100039, China 3: Department of Earth Sciences, Indiana University-Purdue University, Indianapolis, IN46202, USA 4: State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China

Publication date: 2009-01-01

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