An Assessment of Urban Expansion Impacts on Land Transformation of Rajpur-Sonarpur Municipality
Bibliographic record
Abstract
Urban expansion, population pressure, and increasing industrialization are influenced the world's natural environment, increased climate change, and global warming. Land use and land cover (LULC) changes are occurring due to anthropogenic activities and the results are land transformation, thermal variation, heat stress, and massive vegetation loss, which is increased oxygen deficiency and air pollution. Remote sensing-based Landsat TM and OLI/TIRS data were used to identify the land transformation and the effect of urbanization in Rajpur-Sonarpur Municipality in the years 2000 and 2020. The Built-up land was increased due to anthropogenic activities and around 12.16% area has been increased. Similarly, the agricultural land has been increased by 2.10 km2 area and vegetation area has been decreased around 6.52 km2 in the study area. The vegetation degradation areas were located in the South, South-west, and central parts of this study area. Correspondingly, North, North-west and central parts have a noticeable amount of built-up area developed. During twenty years, 6.97°C temperature was increased due to urban expansion, population pressure, transportation accessibility, and other urban amenities. The overall accuracies of classification maps were 96.25% and 91.64 % and the kappa coefficients were 0.95 and 0.89 respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".