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<p>Meeting ecological requirements in power planning demands engineering-ready evidence. This study targets provincial-scale decision making by operationalizing ecological carbon assets (ECA) for the power industry. Using Geographic Information System (GIS) and county-level multi-source data for 2000–2023, we compile high-resolution ECA value maps consistent with standard accounting, providing GIS-ready spatial layers that can be integrated with candidate generation sites and transmission corridors in provincial planning exercises. We then apply Exploratory Spatiotemporal Data Analysis (ESTDA)—global Moran’s I and local indicators of spatial association (LISA) time path—to characterize the clustering, persistence and evolution of ECA, thereby helping to screen regions with sustained ecological sensitivity. Next, a Decision-Making Trial and Evaluation Laboratory–Adjacency Interpretive Structure Modeling (DEMATEL-AISM) is employed to identify direct and indirect drivers of ECA dynamics that are relevant for delineating feasible planning corridors and for informing priority setting and risk control in project siting. Finally, based on the empirical evidence, we outline an ecological information-integration mechanism for grid and generation planning, together with a whitelist/redline zoning scheme for siting and corridor comparison. The Shandong case shows that the total value of ecological carbon assets has increased substantially, with pronounced clustering of high-value areas in central–southern and eastern ecological function zones and low-value areas around urbanized load centers; land transfer, green and new-technology patents, and pollution indicators emerge as dominant drivers. The framework provides transferable support for embedding ecological considerations into provincial power planning and investment.</p>

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Embedding ecological carbon assets in provincial power planning: a GIS–ESTDA–DEMATEL framework for Shandong, China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月5日

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  • Yuying Wu,
  • Yunjing Wang

摘要

Meeting ecological requirements in power planning demands engineering-ready evidence. This study targets provincial-scale decision making by operationalizing ecological carbon assets (ECA) for the power industry. Using Geographic Information System (GIS) and county-level multi-source data for 2000–2023, we compile high-resolution ECA value maps consistent with standard accounting, providing GIS-ready spatial layers that can be integrated with candidate generation sites and transmission corridors in provincial planning exercises. We then apply Exploratory Spatiotemporal Data Analysis (ESTDA)—global Moran’s I and local indicators of spatial association (LISA) time path—to characterize the clustering, persistence and evolution of ECA, thereby helping to screen regions with sustained ecological sensitivity. Next, a Decision-Making Trial and Evaluation Laboratory–Adjacency Interpretive Structure Modeling (DEMATEL-AISM) is employed to identify direct and indirect drivers of ECA dynamics that are relevant for delineating feasible planning corridors and for informing priority setting and risk control in project siting. Finally, based on the empirical evidence, we outline an ecological information-integration mechanism for grid and generation planning, together with a whitelist/redline zoning scheme for siting and corridor comparison. The Shandong case shows that the total value of ecological carbon assets has increased substantially, with pronounced clustering of high-value areas in central–southern and eastern ecological function zones and low-value areas around urbanized load centers; land transfer, green and new-technology patents, and pollution indicators emerge as dominant drivers. The framework provides transferable support for embedding ecological considerations into provincial power planning and investment.