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Record W2055415870 · doi:10.5589/m05-015

Interpretation of land cover changes using aerial photography and satellite imagery in the Foothills Model Forest of Alberta

2005· article· en· W2055415870 on OpenAlexvenueaboutno aff
Steven E. Franklin, Peter K. Montgomery, Gordon Stenhouse

Bibliographic record

VenueCanadian Journal of Remote Sensing · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsThematic MapperFoothillsAerial photographyGeographySatellite imageryLand coverRemote sensingForestryThematic mapCartographySatelliteLand useMultispectral ScannerPhysical geographyEcology

Abstract

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AbstractAerial photographs acquired in 1948-1952, Corona "spy-satellite" imagery acquired in 1963, and Landsat multispectral scanner (MSS), thematic mapper (TM), and enhanced thematic mapper plus (ETM+) imagery acquired since 1974 were used to interpret land cover changes in the Foothills Model Forest of Alberta. The different image characteristics of aerial photographs and satellite sensor data require different analysis methods, but increasingly these data are being used together to determine changes in land cover and structure over a longer time period than is possible using satellite image data alone. The interpretations from this study suggest that in an active forest management area, conifer forest cover was reduced, broadleaf and mixed-forest cover was increased, and the forests were structured in smaller patches with greater edge density over the years circa 1950–1999. Another part of the study area, recovering from a major fire in the early part of the century, was interpreted to have experienced an increase in conifer forest area and mean patch size over this same time period. Overall, changes in the Foothills Model Forest landscape were relatively easily identified and deemed significant by resource managers; this study suggests additional work is warranted on understanding the effect of these changes in applications such as wildlife management.Nous avons utilisé des photographies aériennes acquises de 1948-1952, des images acquises en 1963 par le « satellite espion » Corona et des données MSS (« multispectral scanner »), TM (« thematic mapper ») et ETM+ (« enhanced thematic mapper plus ») de Landsat acquises depuis 1974 pour l'interprétation des changements du couvert dans la Forêt modèle de Foothills en Alberta. Les différentes caractéristiques intrinsèques des photographies aériennes et des données satellitaires font appel à des méthodes d'analyse différentes, mais de plus en plus ces données sont utilisées conjointement pour la détermination des changements dans le couvert et la structure sur une plus longue période que si l'on utilisait uniquement des données satellitaires. Nos interprétations indiquent que dans une zone d'aménagement forestière active, le couvert de conifères a diminué, que le couvert de feuillus et de forêt mixte a augmenté et que les forêts ont été structurées en fonction de zones plus petites avec une densité plus grande à la limite au cours de la période 1950–1999. Dans un autre secteur de la zone d'étude, qui se remettait des effets d'un incendie majeur survenu dans la première partie du centenaire, il a été possible d'observer une augmentation dans la surface de forêt coniférienne et des zones moyennes de peuplement au cours de la même période. Globalement, les changements dans le paysage de la Forêt modèle de Foothills ont été relativement faciles à identifier et jugés significatifs par les gestionnaires des ressources; cette étude suggère de poursuivre les travaux afin de mieux connaître les effets de ces changements au niveau de certaines applications dont la gestion de la sauvagine.[Traduit par la Rédaction]

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.204
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2005
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Remote SensingSame topicFire effects on ecosystemsFrench-language works237,207