Urban Expansion and Loss of Agricultural Land: A Remote Sensing Based Study of Shirpur City, Maharashtra
Bibliographic record
Abstract
In present urban expansion is important field of geographic study. This is an attempt to study the urban expansion and land use pattern of Shirpur city of Dhule district (MS). For that purpose used land landsat images (1991, 2001 and 2011) of Shirpur city. These satellite images further processed and analyzed by GIS software. Shirpur city lies in Shirpur tehsil and administrative head quarter of tehsil. Total population of Shirpur city was 44246 in 1991 that increase up to 76905 in 2011. The total area of Shirpur city is 1113.36 hectares out of that 459.64 hectares area under built up in 1991 that increase 760.16 hectares in 2011. This expansion of city area responsible for loss of agricultural land there were 540.33 hectares in 1991 that has been decline 298.72 hectares in 2011. Finely it is concluded that the growing population and its increasing demands of land for non-agricultural activities responsible for turn agricultural land for built up area, industrial plants, roads and plotting for future growth of city.
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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 | 0.000 | 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".