Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

摘要: Accurate estimation of aboveground biomass and carbon stock has gained importance in the context United Nations Framework Convention on Climate Change (UNFCCC) Kyoto Protocol. In order to develop improved forest stratum–specific models for humid rainforest northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A inventory was conducted stratum-specific allometric equations dry biomass. On basis, calculated by applying a conversion factor. After data preprocessing, vegetation indices, principal components, were calculated. The strength their relationships with plot using Pearson’s correlation. Biomass developed performing stepwise multiple linear regression. correlation coefficients revealed that (a) correlated more than spectral parameters, (b) correlations stronger degraded non-degraded forest. For forest, Correlation, Angular Second Moment, Contrast, red band, contributed best model, which explained 84% variability field (relative RMSE = 6.8%). index EVI Variance, Mean, newly introduced coastal blue both NIR bands, 81% 11.8%). These results indicate tropical biomass/carbon, based very high resolution data, can be developing models, including textural information addition information.