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Title: Forest height inventory from airborne Synthetic Aperture Radar
Author: Wallington, Edward David
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2006
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This study assesses the capabilities of commercially available airborne short wavelength Synthetic Aperture Radar (SAR) Interferometry (InSAR) for retrieving individual tree and forest and stand height. In this study, tree height is estimated by subtracting a ground surface elevation model (a UK Ordinance Survey DEM, OSDEM) from a Digital Surface Model, DSM (from commercial Intermap Technologies) and the results are then compared to field measurements of tree and stand heights. Subsequently, the use of two airborne InSAR data sets is assessed for top height retrieval as an operational product, as well as a precursor and supplement to satellite data. Firstly, X-band data from Intermap are used to retrieve homogenous plantation top height over four UK study sites using the difference between the DSM and OSDEM with mean underestimations of 33.48% (6.99m mean difference). Secondly, X-band data are also used to retrieve tree total height over two heterogeneous woodland areas of Belize and the UK. Relationships between radar retrieved height and forest parameters such as stocking density and tree height and radar dependent properties such as slope and edge effects are presented as possible explanation for variations across the collected data. Supporting work using a simple coherent interferometric scattering model is also used to characterise and explain the effects on tree height retrieval due to variations in slope, number density, stand height and forest edges. The results indicate that top height retrieval over homogenous forest stands is feasible with similar accuracies to those found with other remote sensing techniques and ground survey. Individual tree location assessment does not appear to be a suitable technique for assessing height retrieval in heterogeneous environments, and further investigations are required to determine a more suitable approach. This new data set therefore potentially allows a rapid and timely management tool for use in cost-effective sustainable forest management and related applications.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available