Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models

• Published in: International journal of applied earth observation and geoinformation 2018-03, Vol.65, p.105-113
• Main Authors: Alexander, Cici, Korstjens, Amanda H., Hill, Ross A.
• Format: Article
• Language: English
• Subjects: Airborne laser scanning; algorithms; biomass; canopy height; carbon sinks; crown characteristics; forest management; Forestry; habitats; Indonesia; ITC; landscapes; lidar; microrelief; REDD; remote sensing; topographic slope; tree crown; Tree delineation; tree height; trees; tropical forests
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2017.10.009

•Errors in tree locations and heights from a LiDAR CHM increase with terrain slope.•Conical tree heights are overestimated if terrain slope is larger than crown slope.•Errors in location are greater for spherical than conical trees on gentle slopes.•This is relevant for tropical forest biomass estimations on slopes based on a CHM. Tree or canopy height is an important attribute for carbon stock estimation, forest management and habitat quality assessment. Airborne Laser Scanning (ALS) based on Light Detection and Ranging (LiDAR) has advantages over other remote sensing techniques for describing the structure of forests. However, sloped terrain can be challenging for accurate estimation of tree locations and heights based on a Canopy Height Model (CHM) generated from ALS data; a CHM is a height-normalised Digital Surface Model (DSM) obtained by subtracting a Digital Terrain Model (DTM) from a DSM. On sloped terrain, points at the same elevation on a tree crown appear to increase in height in the downhill direction, based on the ground elevations at these points. A point will be incorrectly identified as the treetop by individual tree crown (ITC) recognition algorithms if its height is greater than that of the actual treetop in the CHM, which will be recorded as the tree height. In this study, the influence of terrain slope and crown characteristics on the detection of treetops and estimation of tree heights is assessed using ALS data in a tropical forest with complex terrain (i.e. micro-topography) and tree crown characteristics. Locations and heights of 11,442 trees based on a DSM are compared with those based on a CHM. The horizontal (DH) and vertical displacements (DV) increase with terrain slope (r = 0.47 and r = 0.54 respectively, p