Green infrastructure connectivity analysis across spatiotemporal scales: A transferable approach in the Ruhr Metropolitan Area, Germany

The impacts of power transmission and transformation projects on ecological corridors and landscape connectivity: a case study of Shandong province, China

With the rapid urbanization and electrification in recent years, investment and construction in power infrastructure have been strengthened. Although it has a positive impact on economic development and energy distribution, the ecological and landscape impacts brought by the construction of related auxiliary facilities are often overlooked. To achieve a harmonious relationship between energy development and ecological protection, this study aims at the impacts of power transmission and transformation projects on ecological corridors and landscape connectivity. By coupling the morphological spatial pattern analysis and the least-cost path model, the regional ecological corridors are first constructed. In addition, the influences of power transmission and transformation projects on landscape connectivity can be evaluated and compared. This framework is verified through a case study of Shandong Province in China. The results indicated that power transmission and transformation projects had a significant impact on the migration resistance of landscapes, impeding the formation of ecological corridors for species. Additionally, these projects have exerted a pronounced cutting effect on landscapes, reducing ecological corridor permeability and landscape connectivity. It is crucial to preserve the habitats of major ecological sources while maintaining and developing the ecological nodes along the key ecological corridors. The findings contributed to the harmonization of regional energy planning and ecological protection, providing a reference for the future layout of transmission and transformation project construction and development.

Measuring spatio-temporal heterogeneity and interior characteristics of green spaces in urban neighborhoods: A new approach using gray level co-occurrence matrix

Urban green space (UGS) is a complex and highly dynamic interface between people and nature. The existing methods of quantifying and evaluating UGS are mainly implemented on the surface features at a landscape scale, and most of them are insufficient to thoroughly reflect the spatial-temporal relationships, especially the internal characteristics changes at a small scale and the neighborhood spatial relationship of UGS. This paper thus proposes a method to evaluate the internal dynamics and neighborhood heterogeneity of different types of UGS in Leipzig using the gray level co-occurrence matrix (GLCM) index. We choose GLCM variance, contrast, and entropy to analyze five main types of UGS through a holistic description of their vegetation growth, spatial heterogeneity, and internal orderliness. The results show that different types of UGS have distinct characteristics due to the changes of surrounding buildings and the distance to the built-up area. Within a one-year period, seasonal changes in UGS far away from built-up areas are more obvious. As for the larger and dense urban forests, they have the lowest spatial heterogeneity and internal order. On the contrary, the garden areas present the highest heterogeneity. In this study, the GLCM index depicts the seasonal alternation of UGS on the temporal scale and shows the spatial form of each UGS, being in line with local urban planning contexts. The correlation analysis of indices also proves that each type of UGS has its distinct temporal and spatial characteristics. The GLCM is valid in assessing the internal characteristics and relationships of various UGS at the neighborhood scales, and using the methodology developed in our study, more studies and field experiments could be fulfilled to investigate the assessment accuracy of our GLCM index approach and to further enhance the scientific understanding on the internal features and ecological functions of UGS.

Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens

Green Infrastructure (GI) is gaining wide recognition in cooperative research projects seeking to find solutions for climate adaptation in urbanized areas. However, the potential effects of co-produced GI plans and the underlying preparation process are rarely evaluated. To bridge this gap, the aim of this article is to examine what works in addressing environmental burdens in the urban neighborhood of Dortmund Marten, Germany. As part of a larger transdisciplinary process, selective GI measures were delineated in the case study area through a cooperative workshop between scientists and urban planners. Workshop ideas were incorporated into a mitigative scenario considering a hot summer day to quantify the effects of the derived GI measures on thermal comfort and particulate matter dispersion (PM10 and PM2.5). To evaluate the experiences of the science-practice collaboration, the viewpoints of researchers and urban planners on learning effects, knowledge integration, and GI planning were summarized and compared via an online survey. The results indicate that the proposed GI measures could reduce physiological equivalent temperature (PET) by 25 °C. At the same time, additional roadside trees could increase PM10 concentrations by up to 36 µg/m3 due to wind blocking effects. Reflections on the science-practice workshop show that learning effects were higher for the participating researchers than for planning practitioners, while the integration of individual expertise during the workshop was more difficult for academics. These findings point to the importance of continuous reflections on individual understandings in cooperating stakeholder groups and the value of the evaluation of outcomes in transdisciplinary GI planning.