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| Land Value Capture Analysis× | Multi-Criteria Site Selection× | |
|---|---|---|
| Lĩnh vực | Urban Studies | Urban Studies |
| Họ≠ | Process / pipeline | MCDM |
| Năm ra đời | 2006 | 2006 |
| Người khởi xướng≠ | Jeffery J. Smith & Thomas A. Gihring (value-capture synthesis) | Jacek Malczewski (GIS-MCDA synthesis); Thomas Saaty (AHP weighting) |
| Loại≠ | Estimation of land/property value uplift attributable to public investment for value capture | Spatial multi-criteria decision analysis for siting facilities or land uses |
| Công trình gốc≠ | Smith, J. J., & Gihring, T. A. (2006). Financing transit systems through value capture: An annotated bibliography. American Journal of Economics and Sociology, 65(3), 751–786. DOI ↗ | Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726. DOI ↗ |
| Tên gọi khác | Value Capture Analysis, Land Value Uplift Estimation, Betterment Value Analysis, Transit Value Uplift Analysis | GIS-MCDA, Weighted Overlay Suitability, AHP Site Suitability, Spatial Multi-Criteria Evaluation |
| Liên quan | 4 | 4 |
| Tóm tắt≠ | Land value capture analysis measures the increase in land and property values that a public investment — a new transit line, station, park, or rezoning — creates, so that some of that windfall can be recovered to help pay for the investment. Grounded in classical economics and synthesized for transit by Smith and Gihring, it isolates the value uplift attributable to the public action, usually with hedonic price models and quasi-experimental before/after comparisons, and then quantifies how large a capturable surplus exists. The logic is one of fairness and finance: when public spending lifts private land values, recovering part of the gain funds the public good that created it. | Multi-criteria site selection combines multi-criteria decision analysis (MCDA) with geographic information systems to choose where to locate a facility or land use when many, often conflicting, spatial criteria matter at once. Synthesized as GIS-based MCDA by Jacek Malczewski, it standardizes each criterion layer to a common scale, assigns the criteria importance weights — frequently via Saaty's Analytic Hierarchy Process — and combines them through weighted overlay to produce a suitability surface that ranks every candidate location. The method makes an inherently messy, value-laden siting decision explicit, reproducible, and auditable. |
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