Article
Ecology
Marc Fuhr, Etienne Lalechere, Jean-Matthieu Monnet, Laurent Berges
Summary: Building a network of interconnected overmature forests is crucial for biodiversity conservation. LiDAR technology can accurately assess forest structural parameters and identify overmature forest patches over large areas. In this study, an index combining forest structural maturity attributes was developed to characterize the maturity of field plots. LiDAR metrics, along with elevation, slope, and echo intensity distribution, were important for predicting forest maturity. The model showed a high correlation between observed and predicted maturity values, indicating accurate ranking of field plots.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2022)
Article
Environmental Sciences
Aaron M. Sparks, Mark Corrao, Alistair M. S. Smith
Summary: This study evaluated the accuracy of seven individual tree detection methods in coniferous forest stands, showing that higher ALS pulse density data resulted in higher ITD accuracy. Omission errors were mainly related to stand density, and the use of simple canopy height model methods could reduce omission errors.
Article
Ecology
Jessica M. Stitt, Andrew T. Hudak, Carlos A. Silva, Lee A. Vierling, Kerri T. Vierling
Summary: The study tested a method for quantifying canopy gaps around snags and live trees, finding that snags had more gaps surrounding them than live trees. It suggests that incorporating lidar-derived canopy gap analyses can improve snag modelling and enhance understanding of gap dynamics in closed-canopy forests. Highest differences in canopy gaps were observed at mid-canopy heights and smallest footprint size.
METHODS IN ECOLOGY AND EVOLUTION
(2022)
Article
Forestry
Caden P. Chamberlain, Andrew J. Sanchez Meador, Andrea E. Thode
Summary: Accurate estimates of canopy base height (CBH) and canopy bulk density (CBD) are crucial for fire modeling. This study developed a method using airborne lidar data for estimating CBH and CBD, showing that airborne lidar produced more accurate estimates compared to traditional methods. The study also found that airborne lidar is more accurate at estimating CBH in unmanaged stands, while CBD estimates maintain similar accuracy regardless of management history.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Environmental Sciences
Hangkai You, Shihua Li, Yifan Xu, Ze He, Di Wang
Summary: Tree information in urban areas is vital in various fields, and ALS is efficient in acquiring spatial information. This paper proposes a new point-based method for tree extraction, based on 3D morphological features, which has been proven effective in complex urban scenes. The method showed high accuracy in extracting trees from ALS data, making it suitable for urban area studies with only one adjustable parameter.
Article
Optics
Yadong Guo, Xiankun Wang, Dianpeng Su, Fanlin Yang, Guoyu Li, Chao Qi
Summary: This study proposes a hierarchical registration algorithm for laser point clouds considering building eave attributes. By using the FPPE dataset to improve registration accuracy, the method effectively enhances the registration accuracy of laser point clouds.
Review
Environmental Sciences
Junbo Wang, Lanying Wang, Shufang Feng, Benrong Peng, Lingfeng Huang, Sarah N. Fatholahi, Lisa Tang, Jonathan Li
Summary: This paper provides a narrative review of shoreline mapping using airborne LiDAR over the past two decades. More than 130 articles were summarized to assess the current state and challenges of this method. It was found that while there are limitations and challenges, the combination of LiDAR point cloud processing techniques, such as deep-learning algorithms, shows promise for improving shoreline extraction and mapping.
Article
Biodiversity Conservation
Syed Adnan, Ruben Valbuena, Tuomo Kauranne, Ranjith Gopalakrishnan, Matti Maltamo
Summary: Through the study, it was found that for forest structure assessment, a concentric circular plot size of approximately 11-14 meters radius and a sample size of approximately 50-80 trees may be the optimal choice for reliable BALM estimation. Additionally, the ALS point density does not have a significant impact on the relationship between BALM estimates and various ALS metrics as long as the point density is at least 5 points per square meter.
ECOLOGICAL INDICATORS
(2022)
Article
Environmental Sciences
Manuela Hirschmugl, Florian Lippl, Carina Sobe
Summary: This study examines the options for assessing vertical forest structure in a mountainous near-natural forest in the Austrian Alps using airborne and spaceborne LiDAR data. The indicators of foliage height diversity (FHD) and number of layers (NoL) are investigated. Expert-based assessment (EBA) outperforms break-detection algorithm (BDA) in terms of overall accuracy (OA) for estimating NoL. ALS data shows better OA for NoL than GEDI data. The usability of waveform-based structure parameters shows promise and should be further tested on larger areas.
Article
Environmental Sciences
Maxence Martin, Osvaldo Valeria
Summary: This research aims to determine the ability of Airborne Laser Scanning (ALS) technology to identify age-related structural diversity in old-growth boreal forests. The study found that ALS technology can accurately distinguish between early and late old-growth forests, and revealed the presence of large tracts of late old-growth forests within old-growth forests of unknown age.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Chemistry, Analytical
Jean-Francois Prieur, Benoit St-Onge, Richard A. Fournier, Murray E. Woods, Parvez Rana, Daniel Kneeshaw
Summary: This paper compares the applicability of different types of airborne laser scanning systems for species identification at the individual tree level and finds that the overall accuracies of the methods are similar across all sensor types.
Article
Biodiversity Conservation
Langning Huo, Joachim Strengbom, Tomas Lundmark, Per Westerfelt, Eva Lindberg
Summary: In sustainable forest resource management, establishing forest conservation areas is crucial for maintaining forest biodiversity. However, assessing the conservation value of forests can be challenging due to their large and remote nature. This study explores the use of dense airborne laser scanning (ALS) data to estimate conservation values, specifically focusing on identifying different types of indicator trees.
ECOLOGICAL INDICATORS
(2023)
Article
Plant Sciences
Peter B. Boucher, Ian Paynter, David A. Orwig, Ilan Valencius, Crystal Schaaf
Summary: The research evaluated the impact of occlusion on TLS scans and compared different stem sets, finding that occlusion from non-stem sources was the major influence on TLS line of sight. It was also discovered that transect and point TLS samples demonstrated better representativeness of some stem properties. Deriving sampled area from TLS scans improved estimates of stem density.
Article
Environmental Sciences
Jan Hanus, Lukas Slezak, Tomas Fabianek, Lukas Fajmon, Tomas Hanousek, Ruzena Janoutova, Daniel Kopkane, Jan Novotny, Karel Pavelka, Miroslav Pikl, Frantisek Zemek, Lucie Homolova
Summary: FLIS is a multi-sensor platform that integrates optical, thermal, and laser scanning remotely sensed data to study terrestrial ecosystems. It provides spectral data, landscape orography, and 3D structure information, allowing for the assessment of vegetation ecosystems and the study of thermal behavior in urban systems.
Article
Environmental Sciences
Martin Queinnec, Joanne C. White, Nicholas C. Coops
Summary: This study used ICESat-2 data to estimate forest structure in different boreal forest types in Ontario, Canada, including canopy height, cover, and height variability. Results showed strong agreement between ICESat-2 and airborne LiDAR for estimating canopy height in different forest development stages, but ICESat-2 tended to underestimate canopy height variability and cover compared to LiDAR data.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Forestry
Maryem Fadili, Jean-Pierre Renaud, Jerome Bock, Cedric Vega
ANNALS OF FOREST SCIENCE
(2019)
Article
Environmental Sciences
Dinesh Babu Irulappa-Pillai-Vijayakumar, Jean-Pierre Renaud, Francois Morneau, Ronald E. McRoberts, Cedric Vega
Article
Remote Sensing
Marc Bouvier, Sylvie Durrieu, Richard A. Fournier, Nathalie Saint-Geours, Dominique Guyon, Eloi Grau, Florian de Boissieu
CANADIAN JOURNAL OF REMOTE SENSING
(2019)
Review
Plant Sciences
Jonathan Lenoir, Eva Gril, Sylvie Durrieu, Helene Horen, Marianne Laslier, Jonas J. Lembrechts, Florian Zellweger, Samuel Alleaume, Boris Brasseur, Jerome Buridant, Karun Dayal, Pieter De Frenne, Emilie Gallet-Moron, Ronan Marrec, Camille Meeussen, Duccio Rocchini, Koenraad Van Meerbeek, Guillaume Decocq
Summary: Understanding time-lag dynamics in biodiversity response to contemporary environmental changes requires considering past human activities. This is particularly important in European temperate forests, where legacies from past land uses can confound the effects of recent macro-environmental changes. By using LiDAR technology, we can uncover the impacts of past land uses and management practices, helping to explain biotic responses to long-term environmental changes.
JOURNAL OF ECOLOGY
(2022)
Article
Geography, Physical
Karun R. Dayal, Sylvie Durrieu, Kamel Lahssini, Samuel Alleaume, Marc Bouvier, Jean-Matthieu Monnet, Jean-Pierre Renaud, Frederic Reverse
Summary: This study aims to investigate the influence of lidar scan angle on ABA predictions and evaluate the potential of voxelisation approaches in mitigating scan angle effects. The results showed that models built with point clouds scanned from multiple flight lines were more robust, while datasets with a predominantly nadir configuration did not always lead to better predictions. The use of voxelisation methods helped to mitigate the impacts of changes in scan angles.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Ecology
Eva Gril, Fabien Spicher, Caroline Greiser, Michael B. B. Ashcroft, Sylvain Pincebourde, Sylvie Durrieu, Manuel Nicolas, Benoit Richard, Guillaume Decocq, Ronan Marrec, Jonathan Lenoir
Summary: Most statistical models of microclimate focus on the difference or offset between standardized air temperatures of specific habitats and macroclimate. This study proposes a more parsimonious and flexible approach using two parameters: slope and equilibrium, to establish a general linkage between microclimate and macroclimate temperatures. By installing temperature sensors in forest understoreys and nearby open grasslands across 13 sites in France, the study found that the slope was primarily determined by stand structure variables and the leaf-on/leaf-off period, while the equilibrium was positively related to mean macroclimate temperature and habitat type.
METHODS IN ECOLOGY AND EVOLUTION
(2023)
Article
Engineering, Electrical & Electronic
Anouk Schleich, Sylvie Durrieu, Maxime Soma, Cedric Vega
Summary: GEDI is a lidar system on-board the International Space Station designed for studying forest ecosystems. The low accuracy geolocation of GEDI is a major obstacle for optimal data utilization. Therefore, a geolocation correction method called GeoGEDI, based on high-resolution digital elevation models (DEMs) and GEDI derived ground elevations, has been proposed.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
Karun R. Dayal, Sylvie Durrieu, Kamel Lahssini, Dino Ienco, Jean-Matthieu Monnet
Summary: This study investigates the use of neural networks to improve the robustness of area-based approach (ABA) models by considering the interplay of lidar acquisition parameters, terrain properties, and vegetation characteristics. Results show that the use of expanded datasets containing lidar, terrain, and scan information leads to more accurate predictions compared to standard datasets containing only lidar metrics.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Eva Gril, Marianne Laslier, Emilie Gallet-Moron, Sylvie Durrieu, Fabien Spicher, Vincent Le Roux, Boris Brasseur, Stef Haesen, Koenraad Van Meerbeek, Guillaume Decocq, Ronan Marrec, Jonathan Lenoir
Summary: Mapping the microclimate effect of forest canopies on understory temperature using LiDAR technology combined with multiple forest structure parameters can effectively predict the thermal regulation effect of forest canopies on understory temperature. Airborne LiDAR measurements and calculations can help generate high-resolution forest thermal environment maps.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Engineering, Electrical & Electronic
Florian de Boissieu, Florence Heuschmidt, Nicolas Lauret, Dav M. Ebengo, Gregoire Vincent, Jean-Baptiste Feret, Tiangang Yin, Jean-Philippe Gastellu-Etchegorry, Josiane Costeraste, Marie-Jose Lefevre-Fonollosa, Sylvie Durrieu
Summary: With the advancements in lidar technology, the development of a reliable lidar simulator is crucial for defining sensor specifications, performing comparisons, training machine learning algorithms, and transferring information across scales. This study aims to evaluate the outputs of the discrete anisotropic radiative transfer (DART) model by comparing them with actual sensor acquisitions in complex forest scenes. The results show a high similarity between simulated and measured waveforms at different scales, indicating potential for improved lidar data processing and system development.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Remote Sensing
Shaohui Zhang, Cedric Vega, Christine Deleuze, Sylvie Durrieu, Pierre Barbillon, Olivier Bouriaud, Jean-Pierre Renaud
Summary: The French National Forest Inventory provides detailed forest information at national and regional scales, but small area estimation is also important for local decision making. Remote sensing technology, such as airborne laser scanning and satellite imagery, can be used as auxiliary information to improve the accuracy of small area estimation. This study demonstrates that pairing the French National Forest Inventory plots with nearby GEDI footprints and using a two-phase sampling scheme can improve the accuracy of forest volume estimates.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Kamel Lahssini, Karun Reuel Dayal, Sylvie Durrieu, Jean-Matthieu Monnet
Summary: Forest ecosystems play a significant role in natural balances and climate mechanisms, and are important reservoirs of biodiversity. The sustainable management and conservation of forest resources is crucial in the face of global warming and biodiversity loss. Earth observation data, particularly LiDAR remote sensing, has been recognized as a valuable source of information for forest ecosystem management. In this study, a deep learning based strategy incorporating metrics derived from high density 3D-point clouds acquired by airborne laser scanning and topography descriptors was proposed to estimate forest variables. The results show that the multi-output framework outperformed other algorithms and achieved satisfactory performance in estimating the forest variables of interest.
2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022)
(2022)
Article
Engineering, Electrical & Electronic
Kamel Lahssini, Florian Teste, Karun Reuel Dayal, Sylvie Durrieu, Dino Ienco, Jean-Matthieu Monnet
Summary: Forest ecosystems play a crucial role in global carbon storage and climate mechanisms. Utilizing earth observation data, this study proposes a deep learning-based fusion strategy to combine airborne laser scanning and high-resolution optical imagery for forest characterization. The results highlight the importance of effectively combining multimodal data for improved performance.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Proceedings Paper
Agriculture, Multidisciplinary
Rim Douss, Imed Riadh Ferah, Sylvie Durrieu, Florion De Boissieu
2020 MEDITERRANEAN AND MIDDLE-EAST GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (M2GARSS)
(2020)
Proceedings Paper
Geosciences, Multidisciplinary
Florian de Boissieu, Marc Lang, Jean-Baptiste Feret, Jean-Matthieu Monnet, Sylvie Durrieu
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
(2019)
