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The Utility of Spectral Indices from Landsat ETM+ for Measuring the Structure and Composition of Tropical Dry Forests 1
Author(s) -
Feeley Kenneth J.,
Gillespie Thomas W.,
Terborgh John W.
Publication year - 2005
Publication title -
biotropica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.813
H-Index - 96
eISSN - 1744-7429
pISSN - 0006-3606
DOI - 10.1111/j.1744-7429.2005.00069.x
Subject(s) - normalized difference vegetation index , tropical and subtropical dry broadleaf forests , canopy , basal area , environmental science , deciduous , tropics , vegetation (pathology) , tree canopy , tropical savanna climate , forestry , leaf area index , geography , remote sensing , ecology , agroforestry , ecosystem , biology , medicine , pathology
There is a growing emphasis on developing methods for quantifying the structure and composition of tropical forests that can be applied over large landscapes, especially for tropical dry forests that are severely fragmented and have a high conservation priority. This study investigates the relationships between various measures of forest structure (annual woody increment, canopy closure, stand density, stand basal area) and composition (tree species diversity, tree community composition) measured in semi‐deciduous tropical dry forests on islands in Lago Guri, Venezuela and three spectral indices derived from Landsat ETM+: Normalized Difference Vegetation Index (NDVI), Infrared Index (IRI), and Mid‐Infrared Index (MIRI). Even though there were significant autocorrelations among spectral indices, there were significant differences in the relationships between spectral indices and forest attributes. IRI was not significantly correlated with any of the structural variables while MIRI was correlated with canopy closure and NDVI values were correlated with canopy closure as well as annual woody increment. NDVI and MIRI were both related to relative tree diversity and all three indices were associated with aspects of tree species composition. Based on the results of this study, it appears that spectral indices, and in particular NDVI, may be useful indicators of forest attributes in tropical dry forest habitats. Further research needs to be undertaken to identify if the results of this study can be applied to other tropical dry forests at a global spatial scale.