方法对比
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| 景观格局指数× | CA-马尔可夫土地利用变化模型× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1988 | 1997 |
| 提出者≠ | R. V. O'Neill et al.; McGarigal & Marks (FRAGSTATS) | Cellular automata (Clarke) + Markov chain (Muller & Middleton) |
| 类型≠ | Quantitative landscape pattern description | Spatio-temporal land-use change simulation |
| 开创性文献≠ | O'Neill, R. V., et al. (1988). Indices of landscape pattern. Landscape Ecology, 1(3), 153–162. DOI ↗ | 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, 24(2), 247–261. DOI ↗ |
| 别名 | landscape pattern indices, FRAGSTATS metrics, fragmentation indices, peyzaj metrikleri | CA-Markov model, cellular automata Markov, land-use change simulation, CA-Markov arazi kullanımı modeli |
| 相关 | 3 | 3 |
| 摘要≠ | Landscape metrics are quantitative indices that describe the composition and spatial configuration of a categorical map — typically land cover — at the patch, class, and whole-landscape levels. Developed in landscape ecology (O'Neill and colleagues, 1988) and made widely usable by the FRAGSTATS software, they turn maps into numbers like patch density, edge density, fragmentation, diversity, and connectivity for ecological, planning, and change analysis. | CA-Markov is a hybrid spatio-temporal model that projects land-use and land-cover change by combining a Markov chain — which predicts how much of each class will change — with cellular automata, which decide where that change happens. Widely used for urban-growth and land-cover forecasting, it answers both the quantity and the location of change, something neither component does well alone. |
| ScholarGate数据集 ↗ |
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