UZH-Logo

Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction


Morsdorf, F; Kötz, B; Meier, E; Itten, K I; Allgöwer, B (2006). Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction. Remote Sensing of Environment, 104(1):50-61.

Abstract

We evaluate the potential of deriving fractional cover (fCover) and leaf area index (LAI) from discrete return, small footprint airborne laser scanning (ALS) data. fCover was computed as the fraction of laser vegetation hits over the number of total laser echoes per unit area. Analogous to the concept of contact frequency, an effective LAI proxy was estimated by a fraction of first and last echo types inside the canopy. Validation was carried out using 83 hemispherical photographs georeferenced to centimeter accuracy by differential GPS, for which the respective gap fractions were computed over a range of zenith angles using the Gap Light Analyzer (GLA). LAI was computed by GLA from gap fraction estimations at zenith angles of 0–60°. For ALS data, different data trap sizes were used to compute fCover and LAI proxy, the range of radii was 2–25 m. For fCover, a data trap size of 2 m radius was used, whereas for LAI a radius of 15 m provided best results. fCover was estimated both from first and last echo data, with first echo data overestimating field fCover and last echo data underestimating field fCover. A multiple regression of fCover derived from both echo types with field fCover showed no increase of R2 compared to the regression of first echo data, and thus, we only used first echo data for fCover estimation. R2 for the fCover regression was 0.73, with an RMSE of 0.18. For the ALS LAI proxy, R2 was lower, at 0.69, while the RMSE was 0.01. For LAI larger radii (∼15 m ) provided best results for our canopy types, which is due to the importance of a larger range of zenith angles (0–60°) in LAI estimation from hemispherical photographs. Based on the regression results, maps of fCover and LAI were computed for our study area and compared qualitatively to equivalent maps based on imaging spectrometry, revealing similar spatial patterns and ranges of values.

We evaluate the potential of deriving fractional cover (fCover) and leaf area index (LAI) from discrete return, small footprint airborne laser scanning (ALS) data. fCover was computed as the fraction of laser vegetation hits over the number of total laser echoes per unit area. Analogous to the concept of contact frequency, an effective LAI proxy was estimated by a fraction of first and last echo types inside the canopy. Validation was carried out using 83 hemispherical photographs georeferenced to centimeter accuracy by differential GPS, for which the respective gap fractions were computed over a range of zenith angles using the Gap Light Analyzer (GLA). LAI was computed by GLA from gap fraction estimations at zenith angles of 0–60°. For ALS data, different data trap sizes were used to compute fCover and LAI proxy, the range of radii was 2–25 m. For fCover, a data trap size of 2 m radius was used, whereas for LAI a radius of 15 m provided best results. fCover was estimated both from first and last echo data, with first echo data overestimating field fCover and last echo data underestimating field fCover. A multiple regression of fCover derived from both echo types with field fCover showed no increase of R2 compared to the regression of first echo data, and thus, we only used first echo data for fCover estimation. R2 for the fCover regression was 0.73, with an RMSE of 0.18. For the ALS LAI proxy, R2 was lower, at 0.69, while the RMSE was 0.01. For LAI larger radii (∼15 m ) provided best results for our canopy types, which is due to the importance of a larger range of zenith angles (0–60°) in LAI estimation from hemispherical photographs. Based on the regression results, maps of fCover and LAI were computed for our study area and compared qualitatively to equivalent maps based on imaging spectrometry, revealing similar spatial patterns and ranges of values.

Citations

156 citations in Web of Science®
173 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

2 downloads since deposited on 18 Jul 2012
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2006
Deposited On:18 Jul 2012 14:38
Last Modified:05 Apr 2016 15:48
Publisher:Elsevier
ISSN:0034-4257
Publisher DOI:10.1016/j.rse.2006.04.019
Permanent URL: http://doi.org/10.5167/uzh-62113

Download

[img]
Content: Published Version
Language: English
Filetype: PDF - Registered users only
Size: 931kB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations