Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m^–3 voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R² = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels.

Three-dimensional point data acquired by Terrestrial Lidar Scanning (TLS) is used as ground observation in comparisons with fire severity indices computed from Landsat satellite multi-temporal images through Google Earth Engine (GEE). Forest fires are measured by the extent and severity of fire. Current methods of assessing fire severity are limited to on-site visual inspection or the use of satellite and aerial images to quantify severity over larger areas. On the ground, assessment of fire severity is influenced by the observers’ knowledge of the local ecosystem and ability to accurately assess several forest structure measurements. The objective of this study is to introduce TLS to validate spectral burned ratios obtained from Landsat images. The spectral change was obtained by an image compositing technique through GEE. The 32 plots were collected using TLS in Wood Buffalo National Park, Canada. TLS-generated 3D points were converted to voxels and the counted voxels were compared in four height strata. There was a negative linear relationship between spectral indices and counted voxels in the height strata between 1 to 5 m to produce R² value of 0.45 and 0.47 for unburned plots and a non-linear relationship in the height strata between 0 to 0.5m for burned plots to produce R² value of 0.56 and 0.59. Shrub or stand development was related with the spectral indices at unburned plots, and vegetation recovery in the ground surface was related at burned plots. As TLS systems become more cost efficient and portable, techniques used in this study will be useful to produce objective assessments of structure measurements for fire refugia and ecological response after a fire. TLS is especially useful for the quick ground assessments which are needed for forest fire applications.

Forest fires spread via production and combustion of pyrolysis gases in the understory. The goal of the present paper is to understand the spatial location, distribution, and fraction (relative to the overstory) of understory plants, in this case, sparkleberry shrub, namely its degree of understory consumption upon burn, and to search for correlations between the degree of shrub consumption to the composition of emitted pyrolysis gases. Data were collected in situ at seven small experimental prescribed burns at Ft. Jackson, an army base in South Carolina, USA. Using airborne laser scanning (ALS) to map overstory tree crowns and terrestrial laser scanning (TLS) to characterize understory shrub fuel density, both pre- and postburn estimates of sparkleberry coverage were obtained. Sparkleberry clump polygons were manually digitized from a UAV-derived orthoimage of the understory and intersected with the TLS point cloud-derived rasters of pre- and postburn shrub fuel bulk density; these were compared in relation to overstory crown cover as well as to ground truth. Shrub fuel consumption was estimated from the digitized images; sparkleberry clump distributions were generally found to not correlate well to the overstory tree crowns, suggesting it is shade-tolerant. Moreover, no relationship was found between the magnitude of the fuel consumption and the chemical composition of pyrolysis gases, even though mixing ratios of 25 individual gases were measured.

本研究は森林内の樹木や下層植生などの有形物ではなく，有形物以外の空間である「空隙」が微気象へ与える影響を評価した。森林内空間を3次元的に計測する手法として地上レーザー，森林内の気温・湿度を計測する手法として気象センサーを使用した。有形物と空隙のボクセル数の比較より，森林内の空隙は高さによって分布が異なることがわかった。また，空隙のボクセル数と気象データの相関解析より，森林内空隙は最低気温に大きく影響を及ぼすことがわかった。林冠の有無が微気象に影響を与えることは従来指摘されてきたが，本研究はその関係を森林内空隙の空間分布から解析できた。

Estuaries are complex ecosystems, being difficult to determine the way management actions affect them. This study quantitatively evaluated the spread of invasive submerged and floating aquatic macrophyte vegetation in Franks Tract of the Sacramento-San Joaquin Delta in response to two types of management actions, drought salinity barriers in years 2015, 2021 and 2022, and herbicide treatments in years 2004-2022. A Random Forest algorithm applied to airborne hyperspectral and satellite multispectral images generated maps of macrophyte cover in 2004-2022. Two methods assessed the effects of the management actions. The first one compared macrophyte cover trends between Franks Tract and reference sites across the Delta. The second one predicted macrophyte cover within Franks Tract using multiple environmental variables with a Long Short-Term Memory model. According to the comparison with Big Break reference site, submerged/floating macrophyte cover was +40.9 %/+8.6 % (2015), +57.8 %/+12.7 % (2021) and +75.7 %/+34.3 % (2022) with the barrier than predicted without it. Other reference sites rendered the same tendences in 2015 but mixed results for the other years. It is questionable if these sites behave as true references. Instead, the submerged/floating macrophyte cover was +8.0 %/+0.4 % (2015), +10.3 %/-20.6 % (2021) and -22.7 %/-9.3 % (2022) with the barrier than the Long Short-Term Memory model predicted without it. Additionally, the submerged/floating macrophyte cover with the herbicide treatments was -75.8 %/-72.4 % than modeled without it throughout 2004-2022. These models would improve quantitative assessments of management effects on macrophytes with a longer time series of data that includes more periods with and without drought barriers and herbicide use.

森林の自然更新や多様性の維持には下層植生が重要である。特にササが繁茂すると森林更新が妨げられ，管理作業も困難になる。広域かつ効率的にササの有無を把握する手法の開発が求められている。本研究では，ドローンレーザーによる点群データから生成した樹冠高モデル（DCHM）を用い，ササの有無を推定した。DCHM画像に主成分分析を適用し，ランダムフォレストによりモデルを構築し，高い精度で判別できた。結果より，第1主成分は平均的な樹高と関係し，それ以外の主成分は上層木の空間パターンと関係していた。DCHMを活用することで，下層に存在するササの分布を推定できた。