Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.752318
Title: Improved estimates of vegetation and terrain parameters from waveform LiDAR
Author: Mahoney, Craig
ISNI:       0000 0004 7425 461X
Awarding Body: Swansea University
Current Institution: Swansea University
Date of Award: 2014
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Abstract:
Light Detection And Ranging (LiDAR) technologies have evolved rapidly over the last decade, contributing to our knowledge of the Earth's surface evolution from local to global scales. A relatively young form of LiDAR is continuous waveform, which has not yet been fully exploited. The current research investigates and develops new methods, highlighting the potential and possible pitfalls of working with continuous waveform LiDAR. The first piece of research investigates the effects of shadowing in LiDAR waveforms in physically observed, large footprint LiDAR waveforms, based on previous works noting shadowing effects in radiative transfer models, and in a controlled environment experiment. For this investigation airborne LiDAR derived digital elevation models were employed in conjunction with spatially corresponding waveform returns to identify possible shadowing effects. It was found that shadows occur more frequently over more severely sloped terrain, affecting the accuracy of waveform derived vegetation parameters. The implications of shadows in waveform data are also discussed. The second piece of research develops and tests two methods, the Slope Screening Model and Independent Slope Model, such to determine ground slope information from LiDAR waveforms. Both methods were validated against discrete return airborne LiDAR data, and British Ordnance Survey data, such to identify winch method is most suited to retrieving slope. The third piece of research utilises the favoured method for slope prediction from the second research topic to correct vegetation height estimates for slope. Two methods (Lox' and modified) are investigated and tested, and validated against airborne LiDAR equivalent results at the regional scale, and against normalised difference vegetation index at the near global scale. Both correction methods produced statistically significant differences in mean global vegetation heights with regards to a control dataset.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.752318  DOI: Not available
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