Estimating Above-Ground Biomass from Land Surface Temperature and Evapotranspiration Data at the Temperate Forests of Durango, Mexico

The study of above-ground biomass (AGB) is important for monitoring the dynamics carbon cycle in forest ecosystems. emergence remote sensing has made it possible to analyze vegetation using land surface temperature (LST), Vegetation Temperature Condition Index (VTCI) and evapotranspiration (ET) information. However, relatively few studies have evaluated ability these variables estimate AGB temperate forests. aim present was evaluate relationship LST, VTCI ET with forests Durango, Mexico, regarding each season year develop a estimation model as predictors VCTI ET, together topographic, reflectance Gray-Level Co-Occurrence Matrix (GLCM) texture variables. A semi-parametric generated linear non-linear responses predictive generalized (GAM). results show that best were longitude, latitude, spring elevation VTCI, NDVI (Normalized Difference Index), slope GLCM mean (R2 = 0.61; RMSE 28.33 Mgha−1). developed GAM an independent dataset 0.58; 31.21 Mgha−1), suggesting potential this modeling approach predict analyzed