Investigation on the possibility of beech forest type mapping using Landsat ETM+ data (case study: Khyrood forest)

In order to investigate the possibility of beech forest type (Fagetum) mapping using Landsat ETM+, its data from Chelir district (780 ha) in Khyrood forest, Caspian forests, Iran were analyzed. Geometric registration was applied using 14 ground control points based on digital topographic maps at 1:25000 scale. The RMS error obtained was less than half of an ETM+ pixel. In order to estimate the accuracy of the classified satellite images, a ground truth map covering 42% of the total area, was qualitatively prepared as strips after field inspection. Image classification was performed using original and synthetic bands (rationing, principal component analysis, tasseled cap transformation and fusion) for following four beech forest types: pure beech, dominant beech, mixed beech and non-beech types. Classification was performed using maximum likelihood, minimum distance to mean and KNN classifiers. The highest overall accuracy (35%) was obtained using KNN classifier. The main reason for low overall accuracy can be related to the kind of related classes and also spectral similarity between pure and dominant beech classes. Therefore, these two classes were merged and classification was done again. The highest overall accuracy, considering three classes increased the classification accuracy up to 51%. The results showed that the spectral data of ETM+ do not have a high potential for beech forest type mapping in heterogeneous and uneven-aged Hyrcanian forests, Because the type of considering classes in such a classification is based on one specie (here beech) whereas the abundance of spectral reflectance of other species is neglected.