Climate change migration is increasing and necessitates a re-examination of resettlement planning and processes. Although evidence-based selection of host places would improve climate change resettlement outcomes, few methods for the selection of host communities exist. Consequently, the information base on which most resettlement programs select a host place is often inadequate. This article proposes an empirical methodology to assess resettlement capacity. The methodology uses a hierarchical aggregation approach, where resettlement capacity indicator values are aggregated first into sub-dimension resettlement capacity scores, then further into dimension resettlement capacity scores, and finally into an overall resettlement capacity index. The aggregation allows for the calculation of the relative importance of the different sub-dimensions and the two primary dimensions – assets and conditions. Using 75 indicators and a hierarchical min–max additive approach based on a five-kilometer grid, we create an overall resettlement capacity index for Ethiopia, with and without normalizing the relevant indicators for population size. The results show significant spatial variation in resettlement capacity, and a clear difference between using the population size normalized and non-normalized indicators, particularly regarding places with very low population density. High resettlement capacity sites are scattered in central, southcentral, and northern Ethiopia, and they also occur in small clusters along southern and northwestern borders. Moderate resettlement capacity sites occur more generally all over Ethiopia. Sites with low resettlement capacity cluster in southeastern and western parts of the country. Compared to the low and moderate resettlement capacity sites, those with high resettlement capacity are endowed with human, physical, and financial capital infrastructures. In all three capacity groups, assets contribute significantly less to resettlement capacity than conditions. Sites that are prone to natural hazards, both currently and in the future, are concentrated in the western and northern tips of the country. The calculated resettlement capacity indices are robust to potential missing indicators and change in the unit of analysis. The findings of the study can be used to identify areas for more comprehensive, localized analyses to determine their suitability for resettlement.

气候变化移民正在增加，需要重新审视移民规划和流程。尽管以证据为基础的选择接纳地可以改善气候变化的移民安置结果，但选择接纳社区的方法很少。因此，大多数移民安置计划选择收容地点的信息基础往往不足。本文提出了一种评估移民安置能力的实证方法。该方法采用分层聚合的方法，先将移民安置能力指标值聚合为子维度移民安置能力得分，然后进一步聚合为维度移民安置能力得分，最后聚合为整体移民安置能力指数。聚合允许计算不同子维度和两个主要维度——资产和条件的相对重要性。使用 75 个指标和基于五公里网格的分层最小-最大加法方法，我们创建了埃塞俄比亚的整体移民安置能力指数，无论是否对人口规模的相关指标进行标准化。结果表明，移民安置能力存在显着的空间差异，使用归一化和非归一化的人口规模指标之间存在明显差异，特别是在人口密度非常低的地方。高安置能力的地点分散在埃塞俄比亚中部、中南部和北部，它们也分布在南部和西北部边界的小群落中。中等安置能力的地点更普遍地出现在埃塞俄比亚各地。东南部和西部地区移民安置能力低的地点聚集。与低、中等安置能力点相比，高安置能力点具有人力、物力和金融资本基础设施。在所有三个能力组中，资产对移民安置能力的贡献明显低于条件。目前和未来容易发生自然灾害的地点都集中在该国的西部和北部。计算出的移民安置能力指数对于潜在的缺失指标和分析单位的变化是稳健的。研究结果可用于确定更全面的领域，