Detecting Urban Land-Use and Land-Cover Changes in Mississauga Using Landsat TM Images
Bibliographic record
Abstract
The City of Mississauga in Ontario has been experiencing a fast urban growth in the past two decades which has caused rapid loss of the valuable farm and open space land. Land-use and land-cover maps of the City were produced from Landsat TM images for 1985 and 1999, spanning a period of 14 years. Dramatic changes in land use and land cover have occurred, with loss of forest, cropland and water body to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 7.4% between 1985 and 1999. These land-use and land-cover changes have drastically altered the land surface characteristics. An analysis of Landsat TM images revealed an increase of 23.7 km2 of built-up area and a decrease of non-built (23.2 km2) and water area (0.5 km2). This paper illustrates the usefulness of a remote sensing approach for the urban change studies. According to the land-use and land-cover maps, four vegetation-impervious surface-soil (V-I-S) patterns of the city development were identified pertain to Mississauga’s features.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".