Hill, R.A., 2007. Going Undercover: Mapping Woodland Understorey from Leaf-On and Leaf-Off LiDAR Data. In: Proceedings of the ISPRS Workshop: Laser Scanning 2007 and SilviLaser 2007, September 12-14, 2007, Espoo, Finland, pp. 184-189.
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Official URL: http://www.commission3.isprs.org/laser07/ls2007.pd...
An understorey model is created for an area of broadleaf, deciduous woodland in eastern England using airborne LiDAR data from winter 2003 (leaf-off conditions) and summer 2005 (leaf-on). The woodland is ancient, semi-natural broadleaf and has a heterogeneous structure, with a mostly closed canopy overstorey and a patchy understorey layer beneath. In places, particularly in the centre of the study area, the top canopy is not mature, but is open and scrubby. The trees of the top canopy (i.e. dominants) together with trees and shrubs that occur in open areas (i.e. sub-dominants) can be sampled directly in leaf-on first return airborne LiDAR data, whereas trees and shrubs that occur hidden as understorey (i.e. suppressed) require a more sophisticated approach to map using airborne LiDAR data. This study makes use of the fact that in temperate deciduous woodland the understorey layer typically leafs out two weeks before the overstorey. Capturing winter (leaf-off) airborne LiDAR data during this time slot maximises the ability to map the understorey layer. Thus, leaf-on first return data were used to define the top canopy for overstorey trees and leaf-off last return data were used to model the understorey layer beneath. Field data from five stands were used to identify crown depth in relation to tree height for the six species of dominant trees in the study area. Thresholds were identified per tree species for crown depth as a percentage of canopy height, and the understorey layer was modelled where leaf-off last return data occurred below the relevant threshold. A minimum height of 1 m was applied to define woody understorey. Critical to this process were a Digital Terrain Model (extracted from the leaf-off last return LiDAR data) to normalise the first and last return LiDAR data to canopy height, and a digital tree species map (derived from the classification of time series airborne multi-spectral data) to guide the application of canopy depth thresholds per species.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Geography and Environmental Studies|
Technology > Agriculture
|Group:||School of Applied Sciences > Centre for Conservation, Ecology and Environmental Change|
|Deposited By:||INVALID USER|
|Deposited On:||16 Dec 2008 20:09|
|Last Modified:||07 Mar 2013 14:57|
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