Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/28631
Title: Characterising disturbance in tropical peat swamp forest using satellite imaging radar
Authors: Waldram, Matthew Scott
Supervisors: Page, Susan
Tansey, Kevin
Award date: 1-Jan-2014
Presented at: University of Leicester
Abstract: Satellite radar imaging is a promising technique for biomass mapping and the monitoring of deforestation in tropical forests and reducing the uncertainty in the quantification of forest biomass in tropical regions. The present paradigm in radar imaging is the fitting of empirical relationships between the radar signal and biomass for diverse forest ecosystems, especially in the humid tropics. Therefore, there is a great need to generate knowledge about how to monitor and characterise the biomass of intact and disturbed tropical forest biomass. This research presents the analysis of data from four years of L-band radar imagery from ALOS PALSAR within a carbon dense, tropical peat swamp forest ecosystem in Central Kalimantan (Indonesia). The results showed that the temporal behaviour of the radar signal varied across a gradient of forest biomass, being highly variable at low biomass levels. Critically a large amount of signal change was unrelated to biomass change. Changes in the radar signal were related in a complex non-linear manner to changes in the peatland water table. This allowed, for the first time, the estimation of water table depth at high spatial resolutions from radar images. It was found that the radar signal related to loss of primary forest biomass after fire were in the opposite direction to that expected according to fitted radarbiomass equations. Burnt areas showed highly variable temporal radar with variability linked to rainfall indicating a possible interaction between the water table and remaining (dead) aboveground biomass. The implications of these results are that, at least in tropical peatlands, estimates of biomass based on single date radar images are likely to be highly misleading; multitemporal radar data sets are required to both interpret disturbance histories and to produce accurate classifications of above ground biomass.
Links: http://hdl.handle.net/2381/28631
Type: Thesis
Level: Doctoral
Qualification: PhD
Rights: Copyright © the author. All rights reserved.
Appears in Collections:Theses, Dept. of Geography
Leicester Theses

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