Identifying distributions of urban ecosystem health based on Latin-hypercube sampling and multi-criteria decision analysis framework

In this study, a hybrid approach was established to identify future heterogeneity of urban ecosystem health (UEH) transferred by variations of land-use, socio-economic development, and ecological function in lower scales of cities (i.e., districts), incorporating uncertainty analysis into a multi-criteria decision assessment framework. In consideration of multiple driving factors of UEH scores, the contribution of the main indicators to UEH scores was identified by geographical detector model. To verify effectiveness of the approach, a case study was applied in Dongguan City of China. The results indicated that UEH scores of Dongguan didn't greatly change during 2010-2020. Conversely, the scores would increase from 2023 to 2030, influenced by socio-economic develop-ment and ecological function under the district scale. Concurrently, the heterogeneity of urban ecosystem health ranks (UEHRs) in 32 districts occurred during 2010-2020, further influencing UEH scores of Dongguan. Owing to inconsistent of land-use, ecological function, and socio-economic development of districts, the heterogeneity of UEHRs was intensified in 2025-2030. From 2010 to 2020, the spatial variations of UEH scores in Dongguan City depended on the synergy of land-use intensity and economic growth. The joint influence from economic development, energy consumption and land-use patterns would contribute greatly to the variations of UEH scores in Dongguan City from 2023 to 2030. Thus, heterogeneity of UEHRs under district scale as well as pro-motion for sustainable economic development should be paid attention to by decision-makers, to identify in-ternal characteristics in urban ecosystems.