Extracting tree crown properties from ground-based scanning laser data
Notice bibliographique
Résumé
The spatial organization of above-ground plant material plays an important role in controlling not only plant functional activities like photosynthesis and evapotranspiration, but also the photo-vegetation interactions. To improve our understanding of such interactions, the acquisition of highly detailed information about the 3D architecture of individual plants and communities of plants is required. Recently, Light detection and ranging (LiDAR) sensors, both at the ground and the airborne-level, have emerged as useful tools for mapping 3D plant structure. One such ground-based instrument is the Intelligent Laser Ranging and Imaging System (ILRIS 3D), which was developed at Optech Incorporated. This laser scanner, generates a 3D digital reconstruction of any scene, by actively emitting laser pulses and recording the time elapsed for the return of a pulse, thereby measuring the distance of any given object. It is the objective of this research to utilize the ILRIS 3D to measure structural, and biophysical information of individual trees for use as direct inputs into complex radiative transfer models. The key parameters under investigation are crown dimensions (i.e. shape, area, and volume), crown-level gap fraction (GF) and crown- level leaf area index (LAI). The ILRIS 3D was used to acquire 3D point clouds of an artificial 6' Ficus tree, in a controlled laboratory environment. Measured XYZ point cloud data was segmented to retrieve laser pulse return density profiles, which subsequently were used to estimate gap fraction and LAI . Gap fraction estimates were cross-validated with traditional methods of histogram thresholding of digital photographs (r <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.96). Crown LAI estimates were compared with the actual values (r <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.95, RMSE = 0.45). The next challenge was to implement the developed algorithms to real crowns, namely olive (Olea europaea L.) orchards in southern Spain. Individual tree-level ILRIS 3D data was collected from 24 structurally diverse crowns. Crown dimensional profiles were extracted for ILRIS data that was collected from a horizontal view (i.e ground-based) and a nadir view (i.e from platform 12 meters above ground). Preliminary retrievals from the olive orchards dataset is described here, while current ongoing field measurements are being conducted to validate the findings. Successful demonstration of extracting crown-level structural parameters like gap fraction and LAI from ground-based LiDAR will be important new information that can be used for detailed radiative transfer modeling in olive orchards and likely lead to more robust inversion algorithms.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».