Title : Modeling Forest Stand Volume and Live Above ground Woody Biomass Using Landsat 5 TM Satellite Imagery Spectral and Textural Features
Even though, field-based forest surveying provides highly accurate measurements, it has limitations with regard to incurring high cost, being time consuming and having low spatial coverage and frequency. Taking this challenge into account, this study presents the utility of Landsat 5 TM satellite imagery spectral and textural features for the estimation of forest stand level stem volume and live aboveground woody biomass (AGB) for Eucalyptus globulus plantation forest. The research was conducted to improve accuracy and decrease uncertainties in the modern approach in general, and replace the classical approach in the study site in particular by developing a function that estimate both attributes (dependent variables) as a function of spectral and textural features. The modeling of the stem volume and AGB equations as a function of spectral and textural independent variables were developed using ordinary least square regression method. Based on Pearson correlation statistics test result among dependents and independents variables, Tasseled Cap brightness, GLCM Dissimilarity and GLC Variance were found as best explanatory variables for stem volume estimation. It was also found that Landsat 5 TM Band 5, GLCM Dissimilarity and GLCM Variance were found as best explanatory variables for AGB estimation. The modern approach estimated almost similar mean stem volume and aboveground biomass abundance with field measurement data. The overall findings presented in this study are encouraging and show that Landsat 5 TM imagery was successful in predicting both attributes with reasonable accuracy (Adjusted R2 is 0.50 and 0.51 for stem volume and AGB, respectively). Mean residual is 0 for both stem volume and AGB. Further research is recommended to document the performance of the Landsat 5 TM satellite data under different environmental conditions and topographical changes, as well as for other species.