American Journal of Applied Sciences

Individual Species Crown Mapping in Taman Rimba Ilmu, University Malaya Using Airborne Hyperspectral Imaging

Kamaruzaman Jusoff

DOI : 10.3844/ajassp.2010.493.499

American Journal of Applied Sciences

Volume 7, Issue 4

Pages 493-499

Abstract

Problem statement: Accurate, current and cost-effective individual standing tree data are required by forest management communities for use in forest inventory over large areas. Currently, most of the forest mapping process is done directly on the ground using many technique such as the bearing-distance and also the other technique that use the computer software as a support, such as Tree MapperTM. Instead of ground data collection and where there are difficulties in reaching the individual trees, hyper spectral remote sensing technology is the best option to map the tree positions. Approach: A novel approach to generating an individual tree crown mapping estimated for a lowland dipterocarp forest of Taman Rimba Ilmu, University Malaya, Kuala Lumpur using an airborne hyperspatial (1 m2 ground resolution) imager was presented. Results: A total of 297 individual tree crowns comprising of 83 Xylopia sp., 79 Ixonanthes sp., 56 Hevea sp., 15 Streblus elongates, 14 Pellacalyx sp., 12 Endospermum diadenum, 11 Macaranga gigantea, 10 Cratoxylum sp., 10 Cannarium sp. and 7 Ixonanthes icosandra were identified and delineated as individual polygons in a study area plot of 2 ha. Conclusion/Recommendations: It was found out that individual tree crowns in University Malaya can be detected and counted with reasonable field measured to image derived mapping accuracy of 98.65%. This study implied that acceptable individual tree crown classification maps and algometric equations relating diameter at breast height (dbh) or crown area to biomass can be used to generate timber volume estimates with established crown-diameter-volume correlations.

Copyright

© 2010 Kamaruzaman Jusoff. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.