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Biophysical parameter retrieval from satellite laser altimetry. / Jacqueline Rosette

Swansea University Author: Jacqueline Rosette

Abstract

Quantifying and monitoring vegetation distribution and change are fundamental to carbon accounting and requirements of national forest inventories. This research explores the potential of the Geoscience Laser Altimeter System (GLAS), launched in 2003 by NASA as the first global Earth surface satelli...

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Published: 2009
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
URI: https://cronfa.swan.ac.uk/Record/cronfa42348
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last_indexed 2018-08-03T10:09:55Z
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spelling 2018-08-02T16:24:28.9165885 v2 42348 2018-08-02 Biophysical parameter retrieval from satellite laser altimetry. 7a4e92d81ff93cb67e35a001341e651e NULL Jacqueline Rosette Jacqueline Rosette true true 2018-08-02 Quantifying and monitoring vegetation distribution and change are fundamental to carbon accounting and requirements of national forest inventories. This research explores the potential of the Geoscience Laser Altimeter System (GLAS), launched in 2003 by NASA as the first global Earth surface satellite LiDAR mission. The project study site is the Forest of Dean, Gloucestershire, UK, a highly mixed, temperate forest with varied topography. Methods are developed to distinguish the regions within waveforms returned from vegetation and ground. When compared with field measurements, estimation of canopy height gives a correlation of R2=0.92; RMSE=2.81m. Waveform indices are determined and evaluated with respect to their potential to estimate biophysical parameters. Heights of cumulative energy percentiles within the waveform prove to be significant estimators. When compared to calculations from independent yield models, results show correlations with stand- level top height (R2=0.76; RMSE 3.9m) and stemwood volume (mixed composition stands dominated by broadleaves: R2=0.47, RMSE=75.6m3/ha; conifers: R2=0.66, RMSE=82.5m3/ha). Uncertainty analysis is undertaken of both waveform and yield model estimates. Canopy cover is estimated for the area beneath GLAS waveforms, corrected for differences in reflectance for ground and canopy surfaces. These are assessed against airborne LiDAR estimates, validated using hemispherical photography. The method produces results with R2=0.63; RMSE=11% for stands with greatest coverage by broadleaves and R2=0.41; RMSE 16% for conifer-dominated stands. Small footprint airborne LiDAR (AL) is widely accepted to offer valuable data regarding forest parameters. An evaluation of AL and GLAS results demonstrate that the broad GLAS footprint dimensions allow similar estimation of stand-level parameters (e.g. AL/yield model Top Height: R2=0.73, RMSE=4.5m). Direct comparison of GLAS with AL shows ground surface identification with mean difference of 0.32m and that elevation profiles correspond well (98th percentiles R2=0.76, RMSE=3.4m). Finally, prospects for use of LiDAR in carbon accounting, assimilation within models and for forestry applications are discussed. E-Thesis Remote sensing. 31 12 2009 2009-12-31 COLLEGE NANME Geography COLLEGE CODE Swansea University Doctoral Ph.D 2018-08-02T16:24:28.9165885 2018-08-02T16:24:28.9165885 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Geography Jacqueline Rosette NULL 1 0042348-02082018162447.pdf 10798056.pdf 2018-08-02T16:24:47.4030000 Output 14609754 application/pdf E-Thesis true 2018-08-02T16:24:47.4030000 false
title Biophysical parameter retrieval from satellite laser altimetry.
spellingShingle Biophysical parameter retrieval from satellite laser altimetry.
Jacqueline Rosette
title_short Biophysical parameter retrieval from satellite laser altimetry.
title_full Biophysical parameter retrieval from satellite laser altimetry.
title_fullStr Biophysical parameter retrieval from satellite laser altimetry.
title_full_unstemmed Biophysical parameter retrieval from satellite laser altimetry.
title_sort Biophysical parameter retrieval from satellite laser altimetry.
author_id_str_mv 7a4e92d81ff93cb67e35a001341e651e
author_id_fullname_str_mv 7a4e92d81ff93cb67e35a001341e651e_***_Jacqueline Rosette
author Jacqueline Rosette
author2 Jacqueline Rosette
format E-Thesis
publishDate 2009
institution Swansea University
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Geography{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Geography
document_store_str 1
active_str 0
description Quantifying and monitoring vegetation distribution and change are fundamental to carbon accounting and requirements of national forest inventories. This research explores the potential of the Geoscience Laser Altimeter System (GLAS), launched in 2003 by NASA as the first global Earth surface satellite LiDAR mission. The project study site is the Forest of Dean, Gloucestershire, UK, a highly mixed, temperate forest with varied topography. Methods are developed to distinguish the regions within waveforms returned from vegetation and ground. When compared with field measurements, estimation of canopy height gives a correlation of R2=0.92; RMSE=2.81m. Waveform indices are determined and evaluated with respect to their potential to estimate biophysical parameters. Heights of cumulative energy percentiles within the waveform prove to be significant estimators. When compared to calculations from independent yield models, results show correlations with stand- level top height (R2=0.76; RMSE 3.9m) and stemwood volume (mixed composition stands dominated by broadleaves: R2=0.47, RMSE=75.6m3/ha; conifers: R2=0.66, RMSE=82.5m3/ha). Uncertainty analysis is undertaken of both waveform and yield model estimates. Canopy cover is estimated for the area beneath GLAS waveforms, corrected for differences in reflectance for ground and canopy surfaces. These are assessed against airborne LiDAR estimates, validated using hemispherical photography. The method produces results with R2=0.63; RMSE=11% for stands with greatest coverage by broadleaves and R2=0.41; RMSE 16% for conifer-dominated stands. Small footprint airborne LiDAR (AL) is widely accepted to offer valuable data regarding forest parameters. An evaluation of AL and GLAS results demonstrate that the broad GLAS footprint dimensions allow similar estimation of stand-level parameters (e.g. AL/yield model Top Height: R2=0.73, RMSE=4.5m). Direct comparison of GLAS with AL shows ground surface identification with mean difference of 0.32m and that elevation profiles correspond well (98th percentiles R2=0.76, RMSE=3.4m). Finally, prospects for use of LiDAR in carbon accounting, assimilation within models and for forestry applications are discussed.
published_date 2009-12-31T03:52:47Z
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score 11.012678

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