Generation of a ground-level DEM in a dense equatorial forest zone by merging airborne laser data and a top-of-canopy DEM
Bibliographic record
Abstract
Abstract(i) selecting ground points from the airborne data and deducing a pseudo canopy height for these points, (ii) characterizing the canopy height from a statistical and geostatistical standpoint, (iii) kriging the canopy height and subtracting the resulting model from the top-of-canopy DEM to obtain a DEM corresponding to a ground-level DEM, and (iv) validation. Validation consists of comparing the results with topographic maps and a local heliborne DEM and studying the relationship between the configuration of the airborne trials, in terms of flight-line spacing, and accuracy of the resulting kriged DEM. The results show that the accuracy of the kriged ground-level DEM is significantly better than that of the initial radargrammetric DEM. The standard deviation of elevation errors is reduced from 21.2 to 11.9 m or from 25.3 to 11.1 m, depending on the validation source adopted (French National Geographic Institute spot heights and local heliborne DEM, respectively). In addition, the relationship between flight-line spacing and accuracy of the resulting kriged DEM helps estimate what flight-line spacing is needed to obtain a given accuracy.(i) sélection des points sol à partir des données laser aéroportées et estimation d'une pseudo hauteur de la canopée pour ces points, (ii) caractérisation de la hauteur de la canopée du point de vue statistique et géostatistique, (iii) krigeage de la hauteur de la canopée et calcul de la différence entre le MNT sommet de la canopée et le résultat du krigeage pour obtenir le MNT sol, et (iv) validation. La validation consiste à comparer les résultats avec des points coté issus des cartes topographiques et un MNT héliporté local. Le lien entre l'espacement des lignes de vol laser et la précision du MNT krigé a également été étudié. Les résultats montrent que la précision du MNT krigé au niveau du sol est bien meilleure que celle du MNT radargrammétrique. L'écart type des erreurs altimétriques passe de 21,2 à 11,9 m ou de 25,3 à 11,1 m, selon la source de validation adoptée (points cotés IGN et MNT héliporté, respectivement). De plus, la relation entre l'espacement des lignes de vol et la précision du MNT krigé permet de déterminer l'espacement des lignes de vol nécessaire pour obtenir une précision donnée sur le MNT krigé.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".