Nguyen et al., 2022 - Google Patents
Estimation of vertical plant area density from single return terrestrial laser scanning point clouds acquired in forest environmentsNguyen et al., 2022
- Document ID
- 14910239597888345007
- Author
- Nguyen V
- Fournier R
- Côté J
- Pimont F
- Publication year
- Publication venue
- Remote Sensing of Environment
External Links
Snippet
Plant area density (PAD in m 2· m− 3) defines the total one-sided total plant surface area within a given volume. It is a key variable in characterizing exchange processes between the atmosphere and land surface. Terrestrial laser scanning (TLS) provides unprecedented …
- 230000000694 effects 0 abstract description 35
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/50—Lighting effects
- G06T15/506—Illumination models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/06—Ray-tracing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/49—Scattering, i.e. diffuse reflection within a body or fluid
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/005—Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Koreň et al. | Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods | |
Lau et al. | Quantifying branch architecture of tropical trees using terrestrial LiDAR and 3D modelling | |
Nguyen et al. | Estimation of vertical plant area density from single return terrestrial laser scanning point clouds acquired in forest environments | |
Wei et al. | An assessment study of three indirect methods for estimating leaf area density and leaf area index of individual trees | |
Côté et al. | A fine-scale architectural model of trees to enhance LiDAR-derived measurements of forest canopy structure | |
Kato et al. | Capturing tree crown formation through implicit surface reconstruction using airborne lidar data | |
Liu et al. | Estimating wheat green area index from ground-based LiDAR measurement using a 3D canopy structure model | |
Waser et al. | Assessing changes of forest area and shrub encroachment in a mire ecosystem using digital surface models and CIR aerial images | |
Bremer et al. | Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality | |
Van Leeuwen et al. | Automated reconstruction of tree and canopy structure for modeling the internal canopy radiation regime | |
Li et al. | VBRT: A novel voxel-based radiative transfer model for heterogeneous three-dimensional forest scenes | |
Stereńczak et al. | Mapping individual trees with airborne laser scanning data in an European lowland forest using a self-calibration algorithm | |
Woodgate et al. | An improved theoretical model of canopy gap probability for Leaf Area Index estimation in woody ecosystems | |
Yrttimaa et al. | Detecting and characterizing downed dead wood using terrestrial laser scanning | |
Chen et al. | Estimation of forest leaf area index using terrestrial laser scanning data and path length distribution model in open-canopy forests | |
Côté et al. | Fine-scale three-dimensional modeling of boreal forest plots to improve forest characterization with remote sensing | |
Bailey et al. | Semi-direct tree reconstruction using terrestrial LiDAR point cloud data | |
Korhonen et al. | Estimation of canopy cover, gap fraction and leaf area index with airborne laser scanning | |
Vauhkonen et al. | Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies | |
Petras et al. | Generalized 3D fragmentation index derived from lidar point clouds | |
Vauhkonen et al. | Geometrically explicit description of forest canopy based on 3D triangulations of airborne laser scanning data | |
Wan et al. | A novel and efficient method for wood–leaf separation from terrestrial laser scanning point clouds at the forest plot level | |
Bremer et al. | Multi-temporal fine-scale modelling of Larix decidua forest plots using terrestrial LiDAR and hemispherical photographs | |
Schraik et al. | Crown level clumping in Norway spruce from terrestrial laser scanning measurements | |
Da Silva et al. | Multiscale framework for modeling and analyzing light interception by trees |