In this study, we test whether and in what way tree species diversity in three savanna woodland sites is related to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery-derived indices. We test the use of standard deviation of near-infrared (stdev NIR) radiance and tree canopy cover estimated through the soil-adjusted vegetation index (SAVI) in estimating diversity. We use linear regression analysis to test the existence as well as determine the nature of the relationship between tree species diversity estimated from fieldwork data and stdev NIR radiance and SAVI. Our results show that tree species diversity has a significant (p < 0.05) hump-shaped response to variations in stdev NIR radiance and SAVI. Furthermore, results show that the combination of stdev NIR and SAVI explains between 60% and 64% of the variations in tree species diversity, an improvement of between 30% and 54% explained by the indices individually. We conclude that ASTER remotely sensed data can successfully be used to estimate tree species diversity in savanna woodlands.
机构:
Faculty of Forest Sciences and Technology, University of GeziraFaculty of Forest Sciences and Technology, University of Gezira
Ahmed M M HASOBA
Ahmed A H SIDDIG
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机构:
Faculty of Forestry, University of Khartoum
Department of Environmental Conservation, University of Massachusetts AmherstFaculty of Forest Sciences and Technology, University of Gezira
Ahmed A H SIDDIG
Yousif E YAGOUB
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Faculty of Forestry, University of KhartoumFaculty of Forest Sciences and Technology, University of Gezira