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Integrating deep learning-based surrogate modeling into urban forest allocation optimization for maximizing carbon

Da Seul Kim1, Dong Kun Lee2, Eun Sub Kim3

  • 1Department of Landscape Architecture and Rural System Engineering, Seoul National University, Seoul, Republic of Korea.

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Summary
This summary is machine-generated.

Optimizing urban afforestation using a deep learning framework maximizes carbon sequestration. Strategic planting near existing forests enhances Net Primary Productivity (NPP) and landscape connectivity for climate mitigation.

Keywords:
Genetic algorithm optimizationNature-based solutionNet primary productivity (NPP)Spatial decision support systemUrban afforestation

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Area of Science:

  • Urban ecology
  • Climate change mitigation
  • Geospatial analysis

Background:

  • Urban afforestation is crucial for carbon sequestration, but current strategies often ignore spatial variations and ecological connections.
  • Area-expansion targets may not be the most effective approach for maximizing carbon uptake.

Purpose of the Study:

  • To develop and apply an integrated optimization framework for urban afforestation.
  • To maximize Net Primary Productivity (NPP) and carbon sequestration in urban environments.
  • To enhance ecological connectivity through strategic green infrastructure planning.

Main Methods:

  • Developed a deep learning surrogate model combining an Artificial Neural Network (ANN) and a Genetic Algorithm (GA).
  • Trained the ANN on topographic, climatic, land-use, and landscape variables to predict NPP.
  • Utilized SHapley Additive exPlanations (SHAP) for factor importance and GA for optimizing afforestation patches.

Main Results:

  • The ANN model accurately predicted NPP (R²=0.82 on test data).
  • Proximity to existing forests was identified as a key factor for NPP enhancement.
  • GA optimization showed that afforestation near green spaces significantly boosted NPP via improved connectivity.

Conclusions:

  • The data-driven framework effectively optimizes urban afforestation for carbon sequestration.
  • Strategic placement of afforestation, prioritizing ecological connectivity, is more efficient than simple area expansion.
  • This approach supports adaptive urban green infrastructure planning for a carbon-neutral future.