LEAP paper by Cici Alexander online
LEAP Paper led by Cici Alexander is now online.
This paper is the write-up of the poster she presented at the Remote Sensing and Photogrammetry Society (RSPSoc) Annual Conference at the University of Nottingham from 6th to 8th September. RSPSoc is the UK's leading Society for remote sensing and photogrammetry.
Highlights
• We develop a method to delineate patches in a tropical forest using LiDAR data.
• Trees identified from a Canopy Height Model are clustered using k-medoids.
• Patches based on Thiessen polygons reduce edge effects associated with grid cells.
• The method has relevance in landscape ecology for estimating habitat fragmentation.
• Patch-based models could improve carbon stock estimations in tropical forests.
Abstract
Mapping and monitoring tropical rainforests and quantifying their carbon stocks are important, both for devising strategies for their conservation and mitigating the effects of climate change. Airborne Laser Scanning (ALS) has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. This study identifies forest patches using ALS-based structural attributes in a tropical rainforest in Sumatra, Indonesia. A method to group trees with similar attributes into forest patches based on Thiessen polygons and k-medoids clustering is developed, combining the advantages of both raster and individual tree–based methods. The structural composition of the patches could be an indicator of habitat type and quality. The patches could also be a basis for developing allometric models for more accurate estimation of carbon stock than is currently possible with generalised models.
