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| 정책 시나리오 셀룰러 오토마타× | 정책 시나리오 분석× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1979–1997 | 1967–1990s |
| 창시자≠ | Tobler, W. (CA foundations); Clarke, K.C. et al. (policy/urban CA scenarios) | Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD |
| 유형≠ | Grid-based scenario simulation | Qualitative-quantitative hybrid scenario method |
| 원전≠ | Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24(2), 247–261. DOI ↗ | Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146. DOI ↗ |
| 별칭 | PSCA, CA Policy Scenario Modeling, Policy-driven CA Simulation, Scenario-based Cellular Automata | PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis |
| 관련 | 5 | 5 |
| 요약≠ | Policy Scenario Cellular Automata (PSCA) combines cellular automata simulation with structured scenario analysis to evaluate how alternative policy decisions reshape spatially distributed systems over time. Each scenario encodes a different set of transition rules or constraints, and the model iterates to reveal divergent spatial outcomes — enabling direct, visual comparison of policy consequences at the local and system level. | Policy Scenario Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health. |
| ScholarGate데이터셋 ↗ |
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