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Record W150942282

Mapping of intact forest landscapes in Sweden according to Global forest watch methodology

2002· article· en· W150942282 on OpenAlexaboutno aff
Filip Hájek

Bibliographic record

VenueEpsilon Archive for Student Projects (University of Southampton) · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaigaGeographyWildernessBiomeWilderness areaBorealTemperate rainforestEcologyEnvironmental protectionForestryEnvironmental resource managementEcosystemArchaeologyEnvironmental science
DOInot available

Abstract

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Currently, most of the world’s forests are directly or indirectly affected by some kind of \nhuman activity. More people are getting concerned with the state of tropical forests. \nHowever, the international community has not tracked the rate and extent of ecological \nchange in forests of the boreal zone, which is the largest biome in the world and \ncomprise one-third of the world's forest area. Although European temperate forests \nwere transformed centuries ago, there are still some large areas of forest in a relatively \nnatural state left in boreal regions of Russia, Canada, Finland and Sweden. Five years \nago, a team of Russian experts associated with non-governmental environmental \norganisations started to create new maps of Europe's last remaining wilderness forests, \nusing high-resolution satellite images in combination with GIS, existing topographical \nmaps and field work. The result of their effort, “The Last Intact Forest Landscapes of \nNorthern European Russia”, was released by the World Resources Institute's Global \nForest Watch (GFW) project and Greenpeace Russia in October 2001. The maps were \ncreated also for the rest of Russia and the “Atlas of Russia’s Intact Forest Landscapes” \nwas released early in 2002. \n The project “Mapping of Intact Forest Landscapes in Sweden” was initiated by GFW in \nMay 2002. The GFW Pan-Boreal Mapping Initiative originated as an idea to extend the \nunique Atlas of Russia’s Intact Forest Landscapes (Aksenov et al. 2002) over the \nWorld’s entire boreal zone. A number of non-governmental organizations and academic \ninstitutions in five countries (Russia, Finland, Sweden, Norway and Canada) were \ninvolved in creating a map of “Remaining Wildlands in the Northern Forests” as the first \nresult of their cooperation. The map was presented as a poster at the Johannesburg \nSummit 2002 (26th August - 4th September 2002). \n This MSc thesis describes the background context of mapping undisturbed forests in \nSweden, as well as the criteria and methods set by the initiating GFW project. Swedish \nforest conditions are partially covered in the Literature survey chapter, where the \nhistory of forest management and the natural characteristics of northern boreal forests \nare characterised. Previous works about mapping virgin forests in Sweden and related \nstudies dealing with remotely sensed data are mentioned. The essence of the study \nfocuses on the detailed description of the methodology (GIS in combination with the \ninterpretation of satellite data) and the material used to create the map of intact forest \nlandscapes in Sweden. Further, the comparison with other existing old-growth \ninventories can be found in the Discussion part, where also the significance of the \noutput and the applicability of the Russian criteria to the Swedish vegetation conditions \nare evaluated. \n

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.271
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2002
Admission routes1
Has abstractyes

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