Empirical relations between Landsat TM spectral response and forest stands near Fort Simpson, Northwest Territories, Canada
Bibliographic record
Abstract
AbstractEmpirical relationships between forest stand variables, such as age and crown closure, and spectral response measured by the Landsat Thematic Mapper (TM) satellite sensor have long been suggested as an information source to support forest inventories in many regions of the world. Using regression and correlation techniques, the authors have identified the form and strength of these empirical relationships for a sample of forest stands near Fort Simpson, Northwest Territories. Models were strongest for pioneer forest species such as jack pine and trembling aspen as these relationships were characterized by reasonably consistent changes in stand structure and composition. White spruce, a secondary successional species, produced the statistically weakest models from Landsat TM spectral response patterns for all stand variables with the exception of crown closure. The authors attribute the differences in model strength to variable trends in stem growth and stand structural changes caused by differing successional pathways for white spruce stands in this region.Depuis longtemps, des relations empiriques entre des variables des peuplements forestiers, comme l'âge et la fermeture du couvert, et la réponse spectrale mesurée par le capteur TM (Thematic Mapper) du satellite Landsat ont été proposées pour appuyer les évaluations d'inventaires forestiers dans beaucoup de régions de la planète. Par des techniques de régression et de corrélation, nous avons déterminé la forme et la force de ces relations pour un échantillon de peuplements près de Fort Simpson dans les Territoires du Nord-Ouest. Les modèles se sont avérés plus forts pour les espèces forestières pionnières telles que le pin tordu latifolié et le peuplier faux-tremble, ce que nous avons attribué aux changements assez uniformes de la structure et de la composition des peuplements en fonction de l'âge. Les modèles de l'épinette blanche, espèce de succession secondaire, se sont montrés plus faibles, sauf pour la fermeture du couvert. Nous expliquons les différences de la force des modèles par l'évolution plus variable de la croissance des arbres et de la structure des peuplements, attribuable aux différents modes de succession à l'origine des peuplements d'épinette blanche qui sont typiques de la forêt boréale dans cette région.
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 | 0.000 | 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 | 0.001 | 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".