ICESat/GLAS Canopy Height Sensitivity Inferred from Airborne Lidar
Mahoney, Craig ; Hopkinson, Chris ; Held, Alex ; Kljun, Natascha LU
and van Gorsel, Eva
(2016)
In Photogrammetric Engineering & Remote Sensing
82(5).
p.351-363
- Abstract
- Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted... (More)
- Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted when GLAS acquired data during summertime from high energy, laser three transmissions. As GLAS data can be used in global biomass assessments, there is a need to understand and quantify the influence of these data inconsistencies on canopy height estimates. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/f9c4ad54-bf13-4e52-9c4e-d6b9b11d9ca7
- author
- Mahoney, Craig
; Hopkinson, Chris
; Held, Alex
; Kljun, Natascha
LU
and van Gorsel, Eva
- publishing date
- 2016-05-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Photogrammetric Engineering & Remote Sensing
- volume
- 82
- issue
- 5
- pages
- 13 pages
- publisher
- American Society for Photogrammetry and Remote Sensing
- external identifiers
-
- scopus:84969939773
- ISSN
- 0099-1112
- DOI
- 10.14358/PERS.82.5.351
- language
- English
- LU publication?
- no
- id
- f9c4ad54-bf13-4e52-9c4e-d6b9b11d9ca7
- date added to LUP
- 2018-06-12 13:05:56
- date last changed
- 2022-04-25 07:51:50
@article{f9c4ad54-bf13-4e52-9c4e-d6b9b11d9ca7,
abstract = {{Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted when GLAS acquired data during summertime from high energy, laser three transmissions. As GLAS data can be used in global biomass assessments, there is a need to understand and quantify the influence of these data inconsistencies on canopy height estimates.}},
author = {{Mahoney, Craig and Hopkinson, Chris and Held, Alex and Kljun, Natascha and van Gorsel, Eva}},
issn = {{0099-1112}},
language = {{eng}},
month = {{05}},
number = {{5}},
pages = {{351--363}},
publisher = {{American Society for Photogrammetry and Remote Sensing}},
series = {{Photogrammetric Engineering & Remote Sensing}},
title = {{ICESat/GLAS Canopy Height Sensitivity Inferred from Airborne Lidar}},
url = {{http://dx.doi.org/10.14358/PERS.82.5.351}},
doi = {{10.14358/PERS.82.5.351}},
volume = {{82}},
year = {{2016}},
}