EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A decision support tool for evaluating the Ecological mitigation measures based on optimization algorithms 

Eun-sub Kim1, Young-suk Lee2, Dong-kun Lee2, Hui-cheul Jung3, Jung-hee Hyun4, and Seong-cheol Kim5
Eun-sub Kim et al.
  • 1Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul 08826, Korea
  • 2College of Agriculture and Life Sciences, Seoul National University
  • 3Korea Environment Institute
  • 4International Institute for Applied System Analysis
  • 5Korea Environmental Industry and Technology Institute

A recent issue highlights the need for Ecological mitigation measures to mitigate habitat and biodiversity loss caused by increasing human disturbance and urban development. Ecological mitigation measures have become quite effective and efficient in habitat preservation and reducing the extinction rate of the population. In this study, a decision support tool was developed to mitigate environmental impacts on urban development using optimization algorithms. This study seeks to identify a spatial planning model that determines the optimal location and type of mitigation measures based on increasing biodiversity and mitigating the impact of species on urban development and calculates the implementation cost using meta-heuristic optimization algorithms.

We used the evaluation fitness value as landscape structural and functional and threat factors. It is possible to analyze the biodiversity and connectivity using the landscape pattern index and landscape connectivity. As a result of this study, the optimal location of ecological mitigation measures (ecological corridor, guide fences, and alternative habitats) was different for each species, and the Pareto plan showed that a trade-off effect was presented between cost and environmental impact minimization. Then we validated through comparison between the results of the optimization model and planning mitigation in the previous report. It is also expected to increase the effectiveness of the mitigation measures with a flexible model that can be planned within a limited cost.

This work was supported by Korea Environment Industry &Technology Institute(KEITI) through "Climate Change R&D Project for New Climate Regime." , funded by Korea Ministry of Environment(MOE) (RE202201509)


How to cite: Kim, E., Lee, Y., Lee, D., Jung, H., Hyun, J., and Kim, S.: A decision support tool for evaluating the Ecological mitigation measures based on optimization algorithms , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4937,, 2023.