GIS- based Land Suitability Analysis Using AHP for Public Parks Planning in Larkana City
Bibliographic record
Abstract
Optimal locations for public facilities such as public parks are significant issues in the urban planning of Larkana city. Therefore, specifically, Larkana city of Pakistan is selected as the study area where the land suitability model was applied to determine suitable land for public parks. This study was carried out within the framework of an Analytic Hierarchy Process (AHP) as a multi-criteria evaluation approach by integrating it with the Geographic Information System (GIS). Decision support system software called Expert choice 11.5 was used to calculate the weights based on three alternative scenarios. Computed composite weights were inserted into the spatial analysis function of GIS and produced three scenarios of suitability maps, i.e.: (a) land availability, (b) land value and (c) population density. Hence, based on the analysis and findings made in this research, finding suitable locations using the land suitability model for future park development is highly helpful. Results can be useful in the planning of public facilities and future land use planning in Larkana city.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".