Quantifying landscape-metrics impacts on urban green-spaces and water-bodies cooling effect: The study of Nanjing, China

Sun, Xiang; Tan, Xingyu; Chen, Keliang; Song, Shuang; Zhu, Xiaodong; Hou, Donglin

doi:10.1016/j.ufug.2020.126838

Cited by 82 publications

(41 citation statements)

References 36 publications

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“…In addition to greening efforts in the city, these projects also contributed to wetland restoration and improved water systems and settlement environment. Although water bodies were masked out in the RSEI assessment, the expansion of urban water bodies has been reported to effectively lower surrounding temperatures [56], thereby improving the urban eco-environment. The interesting changes in the average seasonal and annual RSEI illustrated in Figure 6 highlight the importance of using more remote sensing images rather than less in RSEI-based assessment.…”

Section: Rsei Change 431 Seasonal and Annual Rsei Changementioning

confidence: 99%

Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

Zhang

Yang

et al. 2021

IJGI

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The remote-sensing ecological index (RSEI), which is built with greenness, moisture, dryness, and heat, has become increasingly recognized for its use in urban eco-environment quality assessment. To improve the reliability of such assessment, we propose a new RSEI-based urban eco-environment quality assessment method where the impact of RSEI indicators on the eco-environment quality and the seasonal change of RSEI are examined and considered. The northern Chinese municipal city of Tianjin was selected as a case study to test the proposed method. Landsat images acquired in spring, summer, autumn, and winter were obtained and processed for three different years (1992, 2005, and 2018) for a multitemporal analysis. Results from the case study show that both the contributions of RSEI indicators to eco-environment quality and RSEI values vary with the season and that such seasonal variability should be considered by normalizing indicator measures differently and using more representative remote-sensing images, respectively. The assessed eco-environment quality of Tianjin was, overall, improving owing to governmental environmental protection measures, but the damage caused by rapid urban expansion and sea reclamation in the Binhai New Area still needs to be noted. It is concluded that our proposed urban eco-environment quality assessment method is viable and can provide a reliable assessment result that helps gain a more accurate understanding of the evolution of the urban eco-environment quality over seasons and years.

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Section: Rsei Change 431 Seasonal and Annual Rsei Changementioning

confidence: 99%

Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

Zhang

Yang

et al. 2021

IJGI

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“…This phenomenon was predominantly related to natural geographical conditions (e.g., topography, climate, etc. ), regional planning (e.g., park layouts, the demarcation of nature reserves), and other socioeconomic factors (Luo et al 2020;Sun et al 2020;). In addition, barren lands had no obvious scaling relations, as its area within the three highly urbanized agglomerations was exceedingly small.…”

Section: How Did the Scaling Relations Of Lulc Change Across Differen...mentioning

confidence: 99%

Spatial scaling of land use/land cover and ecosystem services across urban hierarchical levels: patterns and relationships

Sun

Fang

2022

Landsc Ecol

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Context Land use/land cover (LULC) patterns seriously affect the ecosystem services (ESs), especially in highly developed urban agglomerations. Exploring how LULC and ESs change spatially across urban hierarchical levels and understanding the possible mechanisms can promote the sustainable planning of urban landscapes. Objectives By mapping the spatial patterns of LULC and ESs in three largest urban agglomerations of China, this study aimed to (1) identify the scaling relations of LULC and ESs across different urban hierarchical levels, (2) explore the possible mechanisms of these two types of spatial scaling, and (3) explore how the scaling relations of ESs response to LULC and its policy implications. Methods Based on LULC, we used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and other biophysical models to quantify ES indicators. Then, scalograms were used to quantify the scaling relations of LULC and ESs with respect to changing spatial extent. Results Developed land and cropland exhibited the most predictable responses with changing spatial extent. Compared to other ESs, provisioning services were the most predictable. The predictable scaling relations of ESs at different urban hierarchical levels fell into two general types: power laws at the city proper level and exponential relationships at the metropolitan region and urban agglomeration levels. Conclusions The scaling relations of both LULC and ESs varied across urban hierarchical levels. The spatial scaling of ESs was closely related to LULC patterns. Integrating the scaling relations of ESs into land use planning can help decision-makers formulate multi-scale landscape conservation strategies. Keywords Ecosystem services  Land use/land cover  Scaling relations  Urban agglomeration  Urban hierarchical levels

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“…Focus on explanation of LST of individual land cover patches rather than areas of a city, very high resolution of LST data, and inclusion of several rarely used SCDs constitute the novelty of our approach. Furthermore, we adopted a flipped methodological approach that moved away from quantification of cooling distances of urban green-blue spaces, such as for example in a recent and insightful study by Sun et al (2020b), but rather investigated the size and composition of target patches' neighbourhoods with an aspiration to provide urban design recommendations tailored to their spatial characteristics.…”

Section: Introductionmentioning

confidence: 99%

The importance of spatial configuration of neighbouring land cover for explanation of surface temperature of individual patches in urban landscapes

2021

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Context Relationships between spatial configuration of urban form and land surface temperature (LST) in the excess heat mitigation context are studied over larger tracts of land not allowing for micro-scale recommendations to urban design. Objectives To identify spatial configuration descriptors (SCDs) of urban form and the size of zone of influence conducive to the formation of the coldest and hottest land cover (LC) patches of different types (buildings, grass, paved and trees) from 2 m resolution LC and 2 and 100 m resolution LST maps at two time-steps in the summer. Methods Random Forest regression models were deployed to explain the LST of individual LC patches of different types based on SCDs of core LC patches and patches in their neighbourhoods. ANOVA was used to determine significantly different values of the most important SCDs associated with the coldest and hottest LC patches, and analysis of quartiles informed specification of their ranges. Results Urban form in the immediate neighbourhood to the core LC patches had a strong influence on their LST. Low elevation, high proximity to water, and high aggregation of trees, being important to the formation of the coldest patches of all types. High resolution of LST contributed to a higher accuracy of results. Elevation and proximity to water gained in importance as summer progressed. Conclusions Spatial configuration of urban form in the nearest proximity to individual LC patches and the use of fine resolution LST data are essential for issuing heat mitigation recommendations to urban planners relevant to micro-scales.

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Quantifying landscape-metrics impacts on urban green-spaces and water-bodies cooling effect: The study of Nanjing, China

Cited by 82 publications

References 36 publications

Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

Spatial scaling of land use/land cover and ecosystem services across urban hierarchical levels: patterns and relationships

The importance of spatial configuration of neighbouring land cover for explanation of surface temperature of individual patches in urban landscapes

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