A5052343767- Remote Sensing and LiDAR Applications
- Forest ecology and management
- Forest Ecology and Biodiversity Studies
- Remote Sensing in Agriculture
- Fire effects on ecosystems
- Wood and Agarwood Research
- 3D Surveying and Cultural Heritage
- Botany and Plant Ecology Studies
- Agriculture and Rural Development Research
- French Urban and Social Studies
- Ecology and Vegetation Dynamics Studies
- Forest Management and Policy
- Image Processing and 3D Reconstruction
- Plant Water Relations and Carbon Dynamics
- African Botany and Ecology Studies
- Image and Object Detection Techniques
- Gait Recognition and Analysis
- Bioenergy crop production and management
- Peatlands and Wetlands Ecology
- Biometric Identification and Security
- User Authentication and Security Systems
- Tree Root and Stability Studies
- Wildlife Ecology and Conservation
- Global Energy and Sustainability Research
- Horticultural and Viticultural Research
Office National des Forêts
2011-2024
FDI (France)
2016
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2005
Tropical forest canopies are comprised of tree crowns multiple species varying in shape and height, ground inventories do not usually reliably describe their structure. Airborne laser scanning data can be used to characterize these individual crowns, but analytical tools developed for boreal or temperate forests may require adjusted before they applied tropical environments. Therefore, we compared results from six different segmentation methods plots (39 ha) a study site French Guiana. We...
This study assessed the species composition and development of regeneration plots in gaps created by a windstorm mixed-species broadleaved stand. The stand was former coppice-with-standards characterized high tree diversity. Thirteen years after gap creation, all were fully stocked almost exclusively dominated Fagus sylvatica Acer pseudoplatanus seedlings, two shade tolerance their early stages. All other (Quercus sp., Fraxinus excelsior, Carpinus betulus, campestre, platanoïdes, Sorbus...
There is considerable evidence for the presence of positive species diversity–productivity relationships in plant populations, but population parameters determining type and strength relationship are poorly defined. Relationships between evenness tree survival or coexistence not well established. The objective this study was to quantify joint effects density on productivity coexistence. A 12-year-old experimental plantation mixing two according a double gradient proportion used....
Leaf biomass distribution is a key factor for modeling energy and carbon fluxes in forest canopies assessing fire behavior. We propose new method to estimate 3D leaf bulk density distribution, based on calibration of indices derived from T-LiDAR. applied the four contrasted plots mature Quercus pubescens forest. densities were measured inside 0.7 m-diameter spheres, referred as Calibration Volumes. Indices LiDAR point clouds calibrated over Volume densities. Several proposed tested account...
Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during inventories. Various specialized algorithms have been developed automatic objective estimates attributes from clouds. The STEP (Snakes for Tuboid Extraction Point cloud) algorithm was estimate both stem diameter at breast height diameters along the bole length. Here, we evaluate accuracy this compare its performance with two other...
Abstract The here-on presented SimpleForest is written in C++ and published under GPL v3. As input data utilizes forestry scenes recorded as terrestrial laser scan clouds. provides a fully automated pipeline to model the ground digital terrain model, then segment vegetation finally build quantitative structure models of trees (QSMs) consisting up thousands topologically ordered cylinders. These QSMs allow us calculate traditional metrics such diameter at breast height, but also volume other...
Segmentation of defects on the tree log surface remains a challenge due to unclear seperation between foreground and background high variability surface. Even if some first works exist process specific species, generic method robust various species is missing. We propose new approach for segmenting based tabular object analysis. firstly compute centerline by normal accumulation then threshold point cloud difference distance reference estimated from patch neighbors. The performance proposed...
The aim of the work presented in this paper is to develop a method for automatic identification tree species using Terrestrial Light Detection and Ranging (T-LiDAR) data. approach that we propose analyses depth images built from 3D point clouds corresponding 30 cm segment trunk order extract characteristic shape features used classifying different Random Forest classifier. We will present transform cloud image region based segmentation before are computed on segmented images. Our has been...
Tree species recognition from Terrestrial Light Detection and Ranging (T-LiDAR) scanner data is essential for estimating forest inventory attributes in a mixed planting. In this paper, we propose new method individual tree based on the analysis of 3D geometric texture barks. Our transforms point cloud 30 cm segment trunk into depth image which hybrid segmentation using watershed region merging techniques applied order to reveal bark shape characteristics. Finally, intensity features are...
With specific flora and fauna, regional landscapes forests constitute an important part of the cultural heritage. Several natural environments have already been classified as national or parks. The UNESCO World Heritage covers 13% protected in world. Thus, preserving those sites represents a crucial issue. Such safeguarding involves detailed knowledge forestry management plans. forest is traditionally based on plot inventories which several features trees are measured. set data collected...
After publication of the research paper [1] an error during data analysis process was recognized. [...]
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