Intégration de données de recensements et de la télédétection pour mesurer l'évolution socio-économique et environnementale en milieu urbain cas de la ville de Sherbrooke (1981-2006)
Bibliographic record
Abstract
The urban environment is complex, heterogeneous and temporally changeable. Man is the main actor in the transformation of urban areas where he interacts with intensity. Spatial differentiation is a result of human occupation in the urban environment. This occupation may vary according to land use, population density, social and economic characteristics and environment. This leads us to say that the socio-economic and environmental indicators change according to the various locations in the urban area and through time. Our goal is to measure the socio-economic and environmental changes in the urban area of the city of Sherbrooke using remote sensing data synchronized with the censuses and that we will then integrate into the geographic information system (GIS). We have used data from the 1981 and 2006 censuses, 1983 aerial photos, 2007 orthophotos and 1983 MSS and 2006 Ikons satellite images to measure the socio-economic and environmental changes in the city of Sherbrooke. We have used spatial analysis tools to integrate image data with census data.The methods uses such as global indices, principal component analysis combined with the variation between the two dates have yielded interesting results.The first factor in principal component analysis with orthogonal rotation (Varimax) justified a substantial percentage of the variance in global indices.The use of dissemination areas resulted in detailed information on the change in the city. From the perspective of spatial distribution, we noted a major difference between the central areas and the peripheral areas in 1981 and 2006. From the perspective of evolution between 1981 and 2006, we observed that are positive and negative changes at various levels took place. We also observed the evolution of ethnicity in the Sherbrooke city and Lennoxville municipality.The study showed that the French population is prevalent in the old city of Sherbrooke as the English population is prevalent in Lennoxville.The European population is spread over the two cities.The aboriginal population is well distributed over the city of Sherbrooke.The population from Asian and Oceanic backgrounds are [i.e. is] concentrated (sometimes on an exclusive basis) in the north and west-centre area of Jardins-Fleuris, in the eastern area of l'Assomption, the northeastern area of Sainte-Famille and the center area of Marie-Reine. We also find concentrations of immigrant populations from all backgrounds in areas such as in the southern part of the Immaculée-Conception and Saint-Joseph and in the south-eastern part of Sainte-Jeanne-d'Arc. This indicates that ethnic neighborhoods are taking roots in the city of Sherbrooke.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".