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Record W2878837130 · doi:10.23917/forgeo.v32i1.5289

The Role of Vegetation in Controlling Air Temperature Resulting from Urban Heat Island

2018· article· en· W2878837130 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueForum Geografi · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Products and Applications
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsUrban heat islandVegetation (pathology)Environmental scienceVegetation coverSubtropicsAir temperatureLand coverTropical vegetationTropicsPhysical geographyLand useGeographyMeteorologyEcology

Abstract

fetched live from OpenAlex

Urban Heat Island (UHI) is a phenomenon exhibited by many worldwide cities. Cities, which exhibit UHI, possess higher air temperature as compared with air temperature in the surrounding areas. However, existing UHI profiles are those occurring in subtropical areas which are, of course, very much different from those in tropical cities. Therefore, the objectives of this study are to describe the UHI’s profile and the role of tree vegetation in controlling and reducing air temperature in a tropical region’s urban areas and, particularly, in DKI Jakarta. In this study, we carried out a spatial analysis of land cover and the distribution of air temperature. In this regard, we based our analysis of the potency of tree vegetation in reducing air temperature in UHI’s profile on the distribution of air temperature in various types of land cover which extended from north to south and from east to west. The ranges of air temperature in land cover in the form of built-up areas were 29.2-39.5 ⁰C, non-tree vegetation 28.6-35.6 ⁰C, and tree vegetation 27.0-35.7 ⁰C. Accordingly, tree vegetation has the highest potential to reduce air temperature and to overcome the phenomenon of UHI.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.388

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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