Burned forest characterization at single-tree level with airborne laser scanning for assessing wildlife habitat

Casas, A.; Garcı́a, Mariano; Siegel, Rodney B.; Koltunov, Alexander; Ramı́rez, C.; Ustin, Susan L.

doi:10.1016/j.rse.2015.12.044

Cited by 54 publications

(55 citation statements)

References 67 publications

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“…However, urban environments often have a broad mix of tree species and trees of different heights and crown shapes, which makes the ITC analysis more challenging [76]. Another application is for habitat analysis, where detailed information about the trees can provide information that is not otherwise available for large areas about the height distribution or layering, tree species composition, and site condition [77] or standing dead trees and burnt forest [78].…”

Section: Habitat Analysis and Urban Mappingmentioning

confidence: 99%

Individual Tree Crown Methods for 3D Data from Remote Sensing

Lindberg

Holmgren

2017

Curr Forestry Rep

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Purpose of Review The rapid development of remote sensing technology has made dense 3D data available from airborne laser scanning and recently also photogrammetric point clouds. This paper reviews methods for extraction of individual trees from 3D data and their applications in forestry and ecology. Recent Findings Methods for analysis of 3D data at tree level have been developed since the turn of the century. The first algorithms were based on 2D surface models of the upper contours of tree crowns. These methods are robust and provide information about the trees in the top-most canopy. There are also methods that use the complete 3D data. However, development of these 3D methods is still needed to include use of geometric properties. To detect a large fraction of the tallest trees, a surface model method generally gives the best results, but detection of smaller trees below the top-most canopy requires methods utilizing the whole point cloud. Several new sensors are now available with capability to describe the upper part of the canopy, which can be used to frequently update vegetation maps. Highly sensitive laser photo detectors have become available for civilian applications, which will enable acquisition of high-resolution 3D laser data for large areas to much lower costs. Summary Methods for ITC delineation from 3D data provide information about a large fraction of the trees, but there is still a challenge to make optimal use of the information from the whole point cloud. Newly developed sensors might make ITC methods cheaper and feasible for large areas.

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Section: Habitat Analysis and Urban Mappingmentioning

confidence: 99%

Individual Tree Crown Methods for 3D Data from Remote Sensing

Lindberg

Holmgren

2017

Curr Forestry Rep

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“…The fire burned through a mosaic of vegetation types that vary with elevation, which included low-elevation grasslands, chaparral and foothill-oak woodland savanna habitat, mixed conifer-broadleaf forests dominated by pines in the lower montane zone, and mixed conifer forests in higher elevation areas dominated by firs. A more detailed description of the study site can be found in Casas et al [26]. …”

Section: Study Areamentioning

confidence: 99%

Extrapolating Forest Canopy Fuel Properties in the California Rim Fire by Combining Airborne LiDAR and Landsat OLI Data

et al. 2017

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Accurate, spatially explicit information about forest canopy fuel properties is essential for ecosystem management strategies for reducing the severity of forest fires. Airborne LiDAR technology has demonstrated its ability to accurately map canopy fuels. However, its geographical and temporal coverage is limited, thus making it difficult to characterize fuel properties over large regions before catastrophic events occur. This study presents a two-step methodology for integrating post-fire airborne LiDAR and pre-fire Landsat OLI (Operational Land Imager) data to estimate important pre-fire canopy fuel properties for crown fire spread, namely canopy fuel load (CFL), canopy cover (CC), and canopy bulk density (CBD). This study focused on a fire prone area affected by the large 2013 Rim fire in the Sierra Nevada Mountains, California, USA. First, LiDAR data was used to estimate CFL, CC, and CBD across an unburned 2 km buffer with similar structural characteristics to the burned area. Second, the LiDAR-based canopy fuel properties were extrapolated over the whole area using Landsat OLI data, which yielded an R 2 of 0.8, 0.79, and 0.64 and RMSE of 3.76 Mg· ha −1 , 0.09, and 0.02 kg·m −3 for CFL, CC, and CBD, respectively. The uncertainty of the estimates was estimated for each pixel using a bootstrapping approach, and the 95% confidence intervals are reported. The proposed methodology provides a detailed spatial estimation of forest canopy fuel properties along with their uncertainty that can be readily integrated into fire behavior and fire effects models. The methodology could be also integrated into the LANDFIRE program to improve the information on canopy fuels.

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“…This finding corresponds to results documented by Lefsky et al [30], who found a strong relationship for ALS-based TD estimates considering a DBH > 100 cm (R 2 = 0.85). Casas et al [88] report a TD estimation accuracy of 87% for trees with a DBH > 30 cm. The dependency of the TD estimation accuracy on DBH indicates a sensitivity issue of the applied ALS-LM approach, while mainly small trees cannot be differentiated and reliably identified.…”

Section: Reliability Of Tree Density Retrievalmentioning

confidence: 99%

Tree Density and Forest Productivity in a Heterogeneous Alpine Environment: Insights from Airborne Laser Scanning and Imaging Spectroscopy

Fatehi

Damm

Leiterer

et al. 2017

Forests

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Abstract:We outline an approach combining airborne laser scanning (ALS) and imaging spectroscopy (IS) to quantify and assess patterns of tree density (TD) and forest productivity (FP) in a protected heterogeneous alpine forest in the Swiss National Park (SNP). We use ALS data and a local maxima (LM) approach to predict TD, as well as IS data (Airborne Prism Experiment-APEX) and an empirical model to estimate FP. We investigate the dependency of TD and FP on site related factors, in particular on surface exposition and elevation. Based on reference data (i.e., 1598 trees measured in 35 field plots), we observed an underestimation of ALS-based TD estimates of 40%. Our results suggest a limited sensitivity of the ALS approach to small trees as well as a dependency of TD estimates on canopy heterogeneity, structure, and species composition. We found a weak to moderate relationship between surface elevation and TD (R 2 = 0.18-0.69) and a less pronounced trend with FP (R 2 = 0.0-0.56), suggesting that both variables depend on gradients of resource availability. Further to the limitations faced in the sensitivity of the applied approaches, we conclude that the combined application of ALS and IS data was convenient for estimating tree density and mapping FP in north-facing forested areas, however, the accuracy was lower in south-facing forested areas covered with multi-stemmed trees.

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Burned forest characterization at single-tree level with airborne laser scanning for assessing wildlife habitat

Cited by 54 publications

References 67 publications

Individual Tree Crown Methods for 3D Data from Remote Sensing

Individual Tree Crown Methods for 3D Data from Remote Sensing

Extrapolating Forest Canopy Fuel Properties in the California Rim Fire by Combining Airborne LiDAR and Landsat OLI Data

Tree Density and Forest Productivity in a Heterogeneous Alpine Environment: Insights from Airborne Laser Scanning and Imaging Spectroscopy

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