LiDAR Applications to Estimate Forest Biomass at Individual Tree Scale: Opportunities, Challenges and Future Perspectives

Abstract

Accurate forest biomass estimation at the individual tree scale is the foundation of timber industry and forest management. It plays an important role in explaining ecological issues and small-scale processes. Remotely sensed images, across a range of spatial and temporal resolutions, with their advantages of non-destructive monitoring, are widely applied in forest biomass monitoring at global, ecoregion or community scales. However, the development of remote sensing applications for forest biomass at the individual tree scale has been relatively slow due to the constraints of spatial resolution and evaluation accuracy of remotely sensed data. With the improvements in platforms and spatial resolutions, as well as the development of remote sensing techniques, the potential for forest biomass estimation at the single tree level has been demonstrated. However, a comprehensive review of remote sensing of forest biomass scaled at individual trees has not been done. This review highlights the theoretical bases, challenges and future perspectives for Light Detection and Ranging (LiDAR) applications of individual trees scaled to whole forests. We summarize research on estimating individual tree volume and aboveground biomass (AGB) using Terrestrial Laser Scanning (TLS), Airborne Laser Scanning (ALS), Unmanned Aerial Vehicle Laser Scanning (UAV-LS) and Mobile Laser Scanning (MLS, including Vehicle-borne Laser Scanning (VLS) and Backpack Laser Scanning (BLS)) data.

Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management

“…ITD approaches have included a wide array of semi-automatic and automatic methods and are described in multiple reviews [4,[28][29][30][31]. These ITD methods have included using 2-dimensional wavelet analysis to detect tree locations, heights, and crown widths [9,12,16,19,[32][33][34], detection of tree heights associated with a local height maxima and then using valley forming or region growing to delineate the crowns [35][36][37], associating tree crowns with clusters and a local density maximum [38], assessment of canopy cover and aggregates of crowns using object-oriented and geographic object-based image analysis methods [12,39], and using machine learning for characterizing the structural and species information of individual trees [40][41][42].…”

Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data

“…Goodness-of-fit statistics of the models fitted, using the three different sets of metrics (TLS, ALS and TLS + ALS) as independent variables. These results were expected as these variables are strongly related to canopy size, and its vertical and horizontal distribution and the combination of ALS-derived metrics (considering zenith angle) and ground-based TLS-derived metrics provides much more complete information regarding spatial structure [102]. The models developed for estimating W LFH and W debris that were fitted using metrics from both sensors also showed RMSE reductions of 6.47 and 7.22%, respectively.…”

Studying the vegetation impact of terrestrial ecosystems on reducing the carbon footprint in in the territory of the Russian Federation

“…Дистанционное зондирование земли на сегодняшний день является наиболее предпочтительным в использовании методом, так как обеспечивает мониторинг растительности в режиме реального времени, позволяет регулярно обновлять данные о площади распространения растительных сообществ и их биомассе, а также применим для картирования неоднородности биомассы [11]. Применение спутников и беспилотных летательных аппаратов особенно актуально при получении характеристических данных растительности с больших площадей, а также труднодоступных территорий [12].…”

“…Несомненное преимущество дистанционного мониторинга при помощи спутниковых снимков, как уже говорилось ранее, заключается в проведении исследования на больших территориях с оценкой биомассы деревьев в глобальном масштабе [11]. Однако осуществление такого вида съемки ограничивается низкой способностью проникновения сквозь облака, а также низкой детализированностью снимков.…”