Relating tree height variations to peat dome slope in Central Kalimantan, Indonesia using small-footprint airborne LiDAR data; SilviLaser, 9-2010
Figure: LiDAR-DTM profiles for Mawas area in (a) km228.8 and (b) km238 and (c) Sabangau area in Cenrl Kalimantan. We selected for the cross-section a profile parallel to the visible logging transects. Transects were acquired with different lengths and have different scales in elevation and in x-direction.
Silvilaser conference 2010, 14th - 17th September, Freiburg, Germany
by Hans-Dieter Viktor Boehm *†, Veraldo Liesenberg ‡ and Juergen Frank †
† Kalteng Consultants [www.kalteng.org], Kirchstockacher Weg 2, D-085635, Hoehenkirchen, Germany. * Corresponding author. Email: email@example.com - ‡ Faculty of Geosciences, Geotechnique and Mining, TU Bergakademie Freiberg, Bernhard-von-Cotta-Str. 2, D-09599, Freiberg, Germany
We investigated how measures derived from small footprint airborne Light Detection and Ranging (LiDAR) data can be used to evaluate the relationships between tree height (represented by the digital surface model, DSM) and peat swamp dome slope (digital terrain model, DTM). In August 2007 we mapped by helicopter different peat swamp forest (PSF) environments with Riegl LiDAR Technology LMS-Q560 in the Mawas area of the Ex-Mega Rice Project (EMRP) and in the Sabangau National Park (Central Kalimantan, Indonesia). In each LiDAR transect we used sample plots of 100x100m along the flown acquisition with a distance of 200m from each other. In each sample plot we calculated the peat dome slope and the tree height and we evaluate linear regression between both parameters. Our results showed that: a) the tree height increases by approximately 5m if the peat dome slope increases from 0.5 to 1.5m pro mille (m/km) from Sabangau River to the peat dome; and b) there is a relationship between both variables (r2≥0.60) that may be related with the permeability, interflow, water storage capability and nutrient availability in the domes. In a near future we intend to conduct regression analysis considering the field-measured stem volumes against together with LiDAR-derived tree height and Ortho-photos in the frame of the REDD knowledge.