LiDAR Data Fusion to Improve Forest Attribute Estimates: A Review

Current Forestry Reports, Год журнала: 2024, Номер 10(4), С. 281 - 297

Опубликована: Июнь 21, 2024

Abstract Purpose of the Review Many LiDAR remote sensing studies over past decade promised data fusion as a potential avenue to increase accuracy, spatial-temporal resolution, and information extraction in final products. Here, we performed structured literature review analyze relevant on these topics published last main motivations applications for fusion, methods used. We discuss findings with panel experts report important lessons, challenges, future directions. Recent Findings other datasets, including multispectral, hyperspectral, radar, is found be useful variety literature, both at individual tree level area level, tree/crown segmentation, aboveground biomass assessments, canopy height, species identification, structural parameters, fuel load assessments etc. In most cases, gains are achieved improving accuracy (e.g. better classifications), resolution height). However, questions remain regarding whether marginal improvements reported range worth extra investment, specifically from an operational point view. also provide clear definition “data fusion” inform scientific community combination, integration. Summary This provides positive outlook come, while raising about trade-off between benefits versus time effort needed collecting combining multiple datasets.

Язык: Английский

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Individual tree branch and leaf metrics extraction in dense plantation scenario through the fusion of drone and terrestrial LiDAR

Computers and Electronics in Agriculture, Год журнала: 2025, Номер 232, С. 110070 - 110070

Опубликована: Фев. 17, 2025

Язык: Английский

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Branch architecture quantification of large-scale coniferous forest plots using UAV-LiDAR data

Remote Sensing of Environment, Год журнала: 2024, Номер 306, С. 114121 - 114121

Опубликована: Апрель 2, 2024

Язык: Английский

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Lidar-derived estimates of forest structure in response to fire frequency

Fire Ecology, Год журнала: 2024, Номер 20(1)

Опубликована: Май 6, 2024

Abstract Background Longleaf pine ( Pinus palustris ) ecosystems are recognized as biodiversity hotspots, and their sustainability is tightly coupled to a complex nexus of feedbacks between fire, composition, structure. While previous research has demonstrated that frequent fire often associated with higher levels biodiversity, relationships frequency forest structure more nuanced because can be difficult measure characterize. We expanded on this body by using lidar characterize vegetation in response at long-term prescribed-fire experiment. asked (1) how does prescribed affect (2) do structural metrics vary the strength frequency. Results Our results indicated varied significantly frequency, reducing complexity. Metrics characterized central tendency and/or variance canopy-related properties were weakly moderately correlated while captured vertical dispersion or variability throughout strata strongly Of all evaluated, understory complexity index had strongest correlation explained 88% variation treatments. Conclusions The findings presented study highlight usefulness technology for characterizing cannot fully single metric. Instead, range diverse required refine scientific understanding support longleaf sustainability. Furthermore, there need further broaden assessments beyond overstory incorporate components, particularly within realm science land management.

Язык: Английский

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CaR3DMIC: A novel method for evaluating UAV-derived 3D forest models by tree features

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 208, С. 279 - 295

Опубликована: Янв. 28, 2024

Язык: Английский

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Individual Tree-Scale Aboveground Biomass Estimation of Woody Vegetation in a Semi-Arid Savanna Using 3D Data

Remote Sensing, Год журнала: 2024, Номер 16(2), С. 399 - 399

Опубликована: Янв. 19, 2024

Allometric equations are the most common way of assessing Aboveground biomass (AGB) but few exist for savanna ecosystems. The need accurate estimation AGB has triggered an increase in amount research towards 3D quantification tree architecture through Terrestrial Laser Scanning (TLS). Quantitative Structure Models (QSMs) trees have been described as way. However, accuracy using QSMs yet to be established savanna. We implemented a non-destructive method based on TLS and QSMs. Leaf-off multi scan point clouds were acquired 2015 Kruger National Park, South Africa Riegl VZ1000. data covered 80.8 ha with average density 315.3 points/m2. Individual segmentation was applied comparative shortest-path algorithm, resulting 1000 trees. As 31 failed reconstructed, we reconstructed optimized 969 computed volume converted wood 0.9. TLS-derived compared from three allometric equations. best modelling results had RMSE 348.75 kg (mean = 416.4 kg) Concordance Correlation Coefficient (CCC) 0.91. Optimized model repetition gave robust estimates given by low coefficient variation (CoV 19.9% 27.5%). limitations can addressed application high-density data. Our study shows that vegetation modelled clouds. this key understanding ecology, its complex dynamic nature.

Язык: Английский

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Drone LiDAR Occlusion Analysis and Simulation from Retrieved Pathways to Improve Ground Mapping of Forested Environments

Drones, Год журнала: 2025, Номер 9(2), С. 135 - 135

Опубликована: Фев. 12, 2025

Drone-mounted LiDAR systems have revolutionized forest mapping, but data quality is often compromised by occlusions caused vegetation and terrain features. This study presents a novel framework for analyzing predicting occlusion patterns in forested environments, combining the geometric reconstruction of flight paths with statistical modeling ground visibility. Using field collected at Unzen Volcano, Japan, we first developed an algorithm to retrieve drone from timestamped pointclouds, enabling post-processing optimization, even when original are unavailable. We then created mathematical model quantify shadow effects obstacles implemented Monte Carlo simulations optimize parameters different stand characteristics. The results demonstrate that lower-altitude flights (40 m) narrow scanning angles achieve highest visibility (81%) require more paths, while higher-altitude wider offer efficient coverage (47% visibility) single paths. For 250 trees per 25 hectares (heights 5–15 m), analysis showed above 90 degrees consistently delivered 46–47% visibility, regardless height. research provides quantitative guidance optimizing surveys though future work needed incorporate canopy complexity seasonal variations.

Язык: Английский

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Phenotypic Trait Monitoring of Victoria amazonica Plants Using Unmanned Aerial Vehicles

Journal of the Indian Society of Remote Sensing, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

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Aboveground-canopy and belowground-root-trait correlations contribute to root system characteristics estimation: Insights from ground penetrating radar data

Ecological Indicators, Год журнала: 2025, Номер 173, С. 113354 - 113354

Опубликована: Март 22, 2025

Язык: Английский

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Mapping Individual Tree- and Plot-Level Biomass Using Handheld Mobile Laser Scanning in Complex Subtropical Secondary and Old-Growth Forests

Remote Sensing, Год журнала: 2025, Номер 17(8), С. 1354 - 1354

Опубликована: Апрель 10, 2025

Forests are invaluable natural resources that provide essential ecosystem services, and their carbon storage capacity is critical for climate mitigation efforts. Quantifying this would require accurate estimation of forest structural attributes deriving aboveground biomass (AGB). Traditional field measurements, while precise, labor-intensive often spatially limited. Handheld Mobile Laser Scanning (HMLS) offers a rapid alternative building inventories; however, its effectiveness accuracy in diverse subtropical forests with complex canopy structure remain under-investigated. In study, we employed both HMLS traditional surveys within structurally plots, including old-growth (Fung Shui Woods) secondary forests. These characterized by dense understories abundant shrubs lianas, as well high stem density, which pose challenges Light Detection Ranging (LiDAR) point cloud data processing. We assessed tree detection rates extracted attributes, diameter at breast height (DBH) height. Additionally, compared tree-level plot-level AGB estimates using allometric equations. Our findings indicate successfully detected over 90% trees types precisely measured DBH (R2 > 0.96), although exhibited relatively higher uncertainty 0.35). The derived from were comparable to those obtained measurements. By producing highly demonstrates potential an effective non-destructive method inventory forests, making it competitive option aiding estimations environments.

Язык: Английский

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