Modeling of Canopy Cover Estimation Using Landsat 8 Satellite OLI Data in the Zagros Forests

Canopy cover is an important forest structure parameter with many applications in ecology, hydrology and forest management. This study aimed at investigating the capability of Landsat 8 satellite OLI data for modeling and estimation of forest canopy in a part of the Zagros forests. First the images were evaluated in terms of geometrical and radiometric errors. Required processing such as Vegetation Indices, Principle Component Analysis (PCA), and Tasseled Cap transformation were performed on the images of the study area. To measure aboveground canopy cover using hemispherical photography method, 60 sample plots were designed with a square dimension of 45 × 45 m. The spectral values of the corresponding sample plots were extracted using a polygon map of sample plots. Forest canopy cover was modeled using stepwise multiple linear regression and the accuracy of the model was evaluated via the k-fold cross validation technique. The results of multiple linear regression between canopy cover with main and computational bands showed that the model obtained from SR vegetation index and band 8 with R2 = 0.662 and RMSE (%) = 15.24 was the best model. Overall, this study demonstrated that the estimation of forest canopy cover is cost-effective and requires low computation power using Landsat 8 satellite.