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Record W2087915639 · doi:10.3138/carto.47.4.1504

Land-Use Change in Portugal, 1990–2006: Main Processes and Underlying Factors

2012· article· en· W2087915639 on OpenAlexvenueno aff
Vasco Diogo, E. Koomen

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsAbandonment (legal)Land use, land-use change and forestryUrbanizationLand useSpatial changeEnforcementLand developmentGeographyAgricultural landAgricultureDriving factorsSoftware deploymentNatural resource economicsEconomic geographyEnvironmental resource managementPhysical geographyEnvironmental scienceEconomicsEconomic growthEcologyPolitical science

Abstract

fetched live from OpenAlex

This article studies the processes of land-use change in Portugal between 1990 and 2006 and analyses the effects of different driving forces in shaping land-use patterns during that period. While urbanization and the abandonment of agricultural land were the most prevalent processes between 1990 and 2000, concurrent processes of land abandonment and agriculture intensification seem to have predominated in recent years. Nevertheless, annual rates of change for all land-use change processes appear to be increasing overall, following a sharp increase in economic growth. The effect of driving forces in shaping land-use change tends to remain stable over time, but the deployment of new infrastructure and the gradual enforcement of spatial planning policies appear to be important factors in dynamically changing spatial patterns of land-use change.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.035
GPT teacher head0.289
Teacher spread0.254 · 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 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

Citations20
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicLand Use and Ecosystem ServicesFrench-language works237,207