Context: Government-led ecological resettlement (ER) is a critical strategy in China to mitigate environmental degradation and alleviate poverty in fragile arid mountainous regions. The success of these programs, however, is critically dependent on the suitability of the new resettlement sites. This study aims to develop and apply a comprehensive multi-criteria evaluation (MCE) framework to assess the suitability of concentrated resettlement sites in Gansu Province, China.

Methods: We established an MCE index system consisting of 18 indicators across three core dimensions: Natural-Ecological, Socio-Economic, and Location-Accessibility. A spatial multi-criteria decision analysis (SMCDA), integrated with the Analytical Hierarchy Process (AHP) for weight determination, was used to quantify the overall suitability level. The obstacle factor model and Local Indicators of Spatial Association (LISA) were applied to diagnose key limiting factors and spatial clustering.

Results: The assessment revealed a predominantly Medium-to-Low suitability level across the surveyed sites, with significant spatial heterogeneity. The average Resettlement Suitability Index () was . The Obstacle Factor analysis clearly identified water resource carrying capacity and access to sustainable employment opportunities as the two most critical limiting factors (obstacles). The results underscore that favorable physical site conditions alone are insufficient for long-term ER success, highlighting a critical Economic Integration Deficit.

Conclusion: The findings suggest that while ER addresses immediate environmental risk, the long-term viability and success of the programs are compromised by socio-economic and resource-related constraints. Policy should shift focus from mere relocation to targeted post-resettlement support, prioritizing sustainable livelihoods, human capital development, and infrastructure investment to enhance the overall suitability and livelihood resilience of the migrants

Ecological Resettlement (ER), Resettlement Suitability, Multi-Criteria Evaluation (MCE), Arid Mountainous Areas

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