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The interaction between water and green spaces holds significant importance as an urban carbon sink, but there has been insufficient attention to how the specific morphology of waterfront landscapes affects their capacity for carbon sink. This study focuses on typical riverfront spaces in Shanghai, employing an improved Carnegie-Ames-Stanford-Approach (CASA) model fused with remote sensing spatiotemporal images to simulate vegetation fixed carbon within urban riverfront green spaces. Furthermore, an interpretable machine learning method was utilized to unveil the mechanism driving spatial heterogeneity in carbon sink efficiency. The results reveal the carbon sink efficiency of urban riverfront green spaces exhibits noticeable spatial heterogeneity, varying according to the location, type, scale, and river elements; The internal green component factors, including vegetation coverage and tree green ratio, along with surrounding environmental factor water surface ratio, are key factors influencing the carbon sinks efficiency; Hydrological elements within specific thresholds, namely, water surface ratio ranges between 0.245 and 0.281, can effectively enhance the carbon sink capacity of green spaces. And the maximum influencing value of distance from the water body is about 1800 m. The study contributes to developing a more scientific layout for climate-adaptive urban riverfront green spaces on the mesoscale. • Green carbon sink efficiency is affected by spatial morphology and the surrounding environment. • Hydrological elements can enhance carbon sink efficiency in riverfront green patches. • Landscape spatial morphology elements interact with each other during the carbon sequestration process. [ABSTRACT FROM AUTHOR]

• Envi-met was used to simulate carbon concentration distribution in green space. • The waterbody enhanced the carbon sink of the waterfront green space. • The waterfront distance factor is the key spatial factors affects the carbon sink. • The mechanism relies on soil-vegetation-water-atmosphere coupling carbon process. Urban ecological spatial patterns affect the carbon sequestration capacity of green spaces. High-resolution carbon concentration data simulated by Envi-met4.4.5 were obtained in Nanyuan Riverside Green space in Huangpu District, Shanghai. And the correlation among green space morphology factors, microclimatic and bioclimatic factors were explored by Random Forest model. The results showed that the importance of the waterfront distance factor to the carbon sink impact reaches 28.88%, and gradually decreased with the change of distance from water from south to north. The importance of the arboreal area ratio and green biomass reached 15.79% and 12.65% respectively, which was much more important than non-green vegetation space proportion indices. The importance of Cohesion reflecting green patches connectivity was 10.33%. In terms of the internal influencing microclimate factors of green space carbon cycle, relative humidity, air temperature and wind speed, had a more significant influence, with the importance degree of influence being 33.50, 29.02 and 10.29%, respectively. Compared with the influence effect between the factors of the bioclimate, the index of photosynthetically active radiation was greater than the influence of the vapor flux. The study provides a reasonable explanation for the theoretical of coupling carbon sink enhancement of hydrological and green spatial factors. [ABSTRACT FROM AUTHOR]

The urban river corridor is an important ecological space that is known for its landscapes and ecological continuity. Compared with the natural river, the urban river is seriously affected by human activities, which are constructed with the hope of recreating a similar natural environment and are uniquely designed so that ecological specialists, landscape experts and scientists could study both the surrounding environment's ecological effects and the continuity degree of the river corridor area. A system, including 10 indices urban river corridor, is established. This assessment method adapts the Analytic Hierarchy Process, GIS data analysis and GIS space technology, and is combined with these methods based on quantitative and qualitative analyses. Using the results obtained by studying the Suzhou River Corridor and the assessment of ecological continuity is completed and the spatial distribution characteristics are approved, thus it allows future development throughout the corridor. Eventually, a development policy is proposed. Firstly, a method to improve the landscape connectivity among the river's greenways is needed. Secondly, a high value area with ecological continuity related to the river greenway is planned along the river greenway. Thirdly, a sufficient natural area is needed to give the area a river corridor influence, maintain the river's ecological continuity, and keep this natural area undisturbed by zoning. Lastly, the plant species distribution need to link ecological traits and landscape matrix. The study of this assessment method provides a rational development path and decision-making basis for the construction of healthy and sustainable urban river corridors. [ABSTRACT FROM AUTHOR]

The development of island landscape space is restricted by its eco-environmental vulnerability and ecosystem complexity. Focusing on the water-land ecotone in the southern part of Chongming Island, this study explored a multidimensional holistic assessment method of island landscape by referring to methods of Landscape Character Assessment (LCA), assisting decision-making in island land use management. This study established a system comprising 12 factors of island landscape characteristics from 3 dimensions: nature, humanity, and coastal pressure. Both qualitative and quantitative methods of fishnet network, spatial overlay, and artificial boundary recognition were used to identify island landscape character types. The results show that there are 6 landscape zones at the local scale, 18 landscape character subtypes, and 87 landscape character partitions at the site scale. Finally, suggestions for improvement of each landscape character zone were made in terms of landscape improvement, island ecological security and, especially, landscape environmental governance, to provide direction for the sustainable development and utilisation of island landscape resources. • The LCA method emphasised on identifying the landscape classifications at both local and site scales for local development. • An assessment index system of island-specific coastal landscape characteristics was suggested. • Spatial correlation on various ecosystem processes data was integrated into the landscape factors of the LCA. [ABSTRACT FROM AUTHOR]