Ecosystem Service Flow Perspective of Urban Green Land: Spatial Simulation and Driving Factors of Cooling Service Flow

被引:2
|
作者
Zhou, Yanru [1 ]
Feng, Zhe [1 ,2 ,3 ]
Xu, Kaiji [1 ]
Wu, Kening [1 ,2 ,3 ]
Gao, Hong [1 ]
Liu, Peijia [4 ,5 ,6 ]
机构
[1] China Univ Geosci Beijing, Sch Land Sci & Technol, Beijing 100083, Peoples R China
[2] Minist Nat Resources MNR, Technol Innovat Ctr Land Engn, Beijing 100035, Peoples R China
[3] Minist Nat Resources MNR, Key Lab Land Consolidat, Beijing 100035, Peoples R China
[4] Zhengzhou Univ, Sch Polit & Publ Adm, Zhengzhou 450001, Peoples R China
[5] Henan Acad Geol, Zhengzhou 450001, Peoples R China
[6] Zhengzhou Univ, Publ Adm Res Ctr, Zhengzhou 450001, Peoples R China
关键词
urban cooling service; ecosystem service flow; green landscape management; GeoDetector; GAUSSIAN PLUME MODEL; WATER SECURITY; POWER-PLANT; HEAT-ISLAND; FRAMEWORK; COVER; EMISSIONS; CAPACITY; HEALTH; REGION;
D O I
10.3390/land12081527
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The linking of ecosystem service flows (ESFs) with urban land management is still in its nascent stage. The spatial process modeling of ESFs plays a crucial role in establishing connections between urban land sustainability and human benefits. However, the spatial processes and driving mechanisms associated with urban cooling services (UCS) remain ambiguous. In this study, we selected the area within the 6th Ring Road of Beijing as the study area, where the population is highly concentrated and the urban greenery is relatively developed. We modeled the spatial processes of cooling service flow (UCSF) in this area and elucidated the contribution of landscape patterns to UCSF. Firstly, the cooling capacity, referred to as UCS, of the urban blue-green landscape, was estimated using the InVEST tool. Subsequently, the UCSF spatial process was simulated by employing a two-dimensional Gaussian function at the pixel level. In order to characterize the landscape features in the study area, eight landscape indices were selected, and Fragstats v4.2 was employed for their calculation. Finally, GeoDetector was utilized to explore the driving mechanisms of landscape patterns on UCSF. The predominant area for both UCS and UCSF lies between the 5th and 6th Ring Road in Beijing, exhibiting a declining trend from the 6th Ring Road toward the city center. The UCSF coverage area, which represents the beneficiary area, accounted for approximately 87.78% of the study area, with the largest increase occurring within the 2nd Ring Road. The Landscape Shape Index demonstrated the strongest individual contribution to UCSF, while its combined bivariate contribution was significant. Geometry exerted a greater influence on UCSF compared to landscape scale and spatial configuration. This study presents novel insights for assessing the omnidirectional flow of ESFs through the modeling of flow functions. The findings of this study can serve as a valuable reference for sustainable urban landscape management and planning.
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页数:16
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