Integration of innovative remote sensing techniques for optimum modelling of tropical forest primate habitat and carbon storage

Dr Cici Alexander led this postdoctoral research project at Bournemouth University together with Prof Ross Hill and Prof Amanda Korstjens as well as Professors Serge Wich and Eric Næsset.

The project completed in October 2017.

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Publications

Cici Alexander, Amanda H. Korstjens, Ross A. Hill (2017) Structural attributes of individual trees for identifying homogeneous patches in a tropical rainforest, International Journal of Applied Earth Observation and Geoinformation, 55:68-72, ISSN 0303-2434, http://dx.doi.org/10.1016/j.jag.2016.11.004.

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.

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Cici Alexander, Amanda H. Korstjens, Ross A. Hill, (2018) Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models. International Journal of Applied Earth Observation and Geoinformation. 65:105-113 DOI: 10.1016/j.jag.2017.10.009

Abstract: 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 < 0.001). The overestimations in tree height are up to 16.6 m on slopes greater than 50° in our study area in Sumatra. The errors in locations (DH) and tree heights (DV) are modelled for trees with conical and spherical tree crowns. For a spherical tree crown, DH can be modelled as R sin θ and DV as R (sec θ – 1). In this study, a model is developed for an idealised conical tree crown, DV = R (tan θ – tan ψ), where R is the crown radius, and θ and ψ are terrain and crown angles respectively. It is shown that errors occur only when terrain angle exceeds the crown angle, with the horizontal displacement equal to the crown radius. Errors in location are seen to be greater for spherical than conical trees on slopes where crown angles of conical trees are less than the terrain angle. The results are especially relevant for biomass and carbon stock estimations in tropical forests where there are trees with large crown radii on slopes. © 2017 The Author(s)