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Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry

  • In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa Barbara, California, USA. We implemented two different modeling approaches. First, we directly estimated effective LAI (LAIe) using scan angle- and clump-corrected lidar laser penetration metrics (LPM). Second, we adapted existing allometric equations to estimate crown structural metrics including tree height and crown base height using lidar. The latter approach allowed for LAI estimates at the individual tree-crown scale. The LPM method, at both high and decimated point densities, resulted in good linear agreement with estimates from ground-based hemispherical photography (r(2) = 0.82, y = 0.99x) using a model that assumed a spherical leaf angle distribution. Within individual tree crown segments, the lidar estimates of crown structure closely paralleled field measurements (e.g., r(2) =In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa Barbara, California, USA. We implemented two different modeling approaches. First, we directly estimated effective LAI (LAIe) using scan angle- and clump-corrected lidar laser penetration metrics (LPM). Second, we adapted existing allometric equations to estimate crown structural metrics including tree height and crown base height using lidar. The latter approach allowed for LAI estimates at the individual tree-crown scale. The LPM method, at both high and decimated point densities, resulted in good linear agreement with estimates from ground-based hemispherical photography (r(2) = 0.82, y = 0.99x) using a model that assumed a spherical leaf angle distribution. Within individual tree crown segments, the lidar estimates of crown structure closely paralleled field measurements (e.g., r(2) = 0.87 for crown length). LAI estimates based on the lidar crown measurements corresponded well with estimates from field measurements (r(2) = 0.84, y = 0.97x + 0.10). Consistency of the LPM and allometric lidar methods was also strong at 71 validation plots (r(2) = 0.88) and at 450 additional sample locations across the entire study area (r(2) = 0.72). This level of correspondence exceeded that of the canopy hemispherical photography and allometric, ground-based estimates (r(2) = 0.53). The first-order alignment of these two disparate methods may indicate that the error bounds for mapping LAI in cities are small enough to pursue large scale, spatially explicit estimation. (C) 2015 Elsevier Inc All rights reserved.show moreshow less

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Metadaten
Author details:Michael Alonzo, Bodo BookhagenORCiDGND, Joseph P. McFadden, Alex Sun, Dar A. Roberts
DOI:https://doi.org/10.1016/j.rse.2015.02.025
ISSN:0034-4257
ISSN:1879-0704
Title of parent work (English):Remote sensing of environment : an interdisciplinary journal
Publisher:Elsevier
Place of publishing:New York
Publication type:Article
Language:English
Year of first publication:2015
Publication year:2015
Release date:2017/03/27
Tag:Airborne lidar; Allometry; Hemispherical photography; Leaf area index; Urban ecosystem analysis; Vegetation structure
Volume:162
Number of pages:13
First page:141
Last Page:153
Funding institution:Naval Postgraduate School [N00244-11-1-0028]; National Science Foundation [BCS-0948914]; Garden Club of America Fellowship in Urban Forestry
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer review:Referiert
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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