Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration
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Bowling Green State University / OhioLINK
2014
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1402857524 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-bgsu14028575242021-08-03T06:25:18Z Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration Ilangakoon, Nayani Thanuja Environmental Geology Geology Terrestrial LiDAR Leaf Area Index Vegetation Indices Bayesian linear regression Uncertainty Leaf area index (LAI) is an important indicator of ecosystem conditions and an important key biophysical variable to many ecosystem models. The LAI in this study was measured by Leica ScanStation C 10 Terrestrial Laser Scanner (TLS) and a hand-held Li-Cor LAI-2200 Plant Canopy Analyzer for understanding differences derived from the two sensors. A total of six different LAI estimates were generated using different methods for the comparisons. The results suggested that there was a reasonable agreement (i.e., the correlations r > 0.50) considering a total of 30 plots and limited land cover types sampled. The predicted LAI from spectral vegetation indices including WDVI, DVI, NDVI, SAVI, and PVI3 which were derived from Landsat TM imagery were used to identify statistical relationships and for the development of the Bayesian inference model. The Bayesian Linear Regression (BLR) approach was used to scale up LAI estimates and to produce continuous field surfaces for the Oak Openings Region in NW Ohio. The results from the BLR provided details about the parameter uncertainties but also insight about the potential that different LAIs can be used to predict foliage that has been adjusted by removing the wooden biomass with reasonable accuracy. For instance, the modeled residuals associated with the LAI estimates from TLS orthographic projection that consider only foliage had the lowest overall model uncertainty with lowest error and residual dispersion range among the six spatial LAI estimates. The deviation from the mean LAI prediction map derived from the six estimates hinted that sparse and open areas that relate to vegetation structure were associated with the highest error. However, although in many studies TLS has been shown to hold a great potential for quantifying vegetation structure, in this study the quantified relationship between LAI and the vegetation indices did not yield any statistical relationship that needs to be further explore. 2014-07-03 English text Bowling Green State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1402857524 http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1402857524 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
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English |
| sources |
NDLTD |
| topic |
Environmental Geology Geology Terrestrial LiDAR Leaf Area Index Vegetation Indices Bayesian linear regression Uncertainty |
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Environmental Geology Geology Terrestrial LiDAR Leaf Area Index Vegetation Indices Bayesian linear regression Uncertainty Ilangakoon, Nayani Thanuja Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| author |
Ilangakoon, Nayani Thanuja |
| author_facet |
Ilangakoon, Nayani Thanuja |
| author_sort |
Ilangakoon, Nayani Thanuja |
| title |
Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| title_short |
Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| title_full |
Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| title_fullStr |
Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| title_full_unstemmed |
Relationship between leaf area index (LAI) estimated by terrestrial LiDAR and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| title_sort |
relationship between leaf area index (lai) estimated by terrestrial lidar and remotely sensed vegetation indices as a proxy to forest carbon sequestration |
| publisher |
Bowling Green State University / OhioLINK |
| publishDate |
2014 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1402857524 |
| work_keys_str_mv |
AT ilangakoonnayanithanuja relationshipbetweenleafareaindexlaiestimatedbyterrestriallidarandremotelysensedvegetationindicesasaproxytoforestcarbonsequestration |
| _version_ |
1719436255564922880 |