Improving Tropical Forest Mapping using Combination of Optical and Microwave Data of ALOS

Abstract

[ABSTRACT]Optical remote sensing usually has not enough multi-temporal high resolution images to describe phenology of objects for forest mapping in local scale. This paper presents a possibility to improve accuracy of tropical forest mapping by combination of optical and microwave images. Study area is located in the southern part of Vietnam. The first, ALOS/AVNIR-2 images were used to create the forest map, then ALOS/PALSAR single-polarized and dual-polarized images were used to improve the accuracy of the classification result by a combination model. ALOS/PRISM images were also used to make Pan-sharpen images for collecting training data and validation data. Discrimination of Planted Forest and Natural Forest is one of the most important purposes of this study. The overall accuracy of ALOS/AVNIR-2 classification result is 77.0%, while after combining with ALOS/PALSAR, it is increased up to 88.2%. The accuracy is higher than 90% for main forest classes