Structural attributes of single trees for identifying homogeneous patches in a tropical rainforest
Start date: 5 September 2016
Tropical rainforests are relatively poorly understood, despite supporting a large proportion of the Earth’s plant and animal species, storing much of the terrestrial carbon pool and playing an important role in regulating the Earth’s climate by being a large sink for carbon dioxide. Human activities such as logging and clearing of forests for agriculture, and agroforestry, continue to alter their extent and composition, leading to fragmentation of habitats., pointing This points to the need for mapping these resources and monitoring changes for devising strategies for conservation. Satellite images have been used for mapping forest types since they cover large areas more efficiently than traditional forest inventory. Airborne laser scanning (ALS), based on the technique of Light Detection and Ranging (LiDAR), has advantages over other remote sensing techniques especially in the case of forests. ALS is considered to be the best suited for generating terrain models in forests due to its ability to collect data from or near the forest floor, which is a requisite for generating forest canopy height models. The aim of this study is to identify forest patches based on structural composition using airborne laser scanner data in a tropical rainforest in Sumatra, Indonesia. The objectives are to estimate the locations and attributes of single trees based on a canopy height model, and to group the single trees based on their structural attributes into forest patches. The structural composition of the patches may be an indication of habitat type and quality for the different species in these forests, which are increasingly under threat from anthropogenic and natural disturbances.