Studies on urban heat island from a landscape pattern view: a review

Ailian, 陈爱莲 Chen; Ranhao, 孙然好 Sun; Liding, 陈利顶 Chen

doi:10.5846/stxb201106280965

Cited by 24 publications

(9 citation statements)

References 10 publications

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“…It is worth noting that the UHI effect has been exacerbated along with ongoing urban expansion and constant population influx in recent years, presenting substantial adverse threats to both residential and environmental health in and around cities [3][4][5]. When considering this, scholars across various disciplines have not stopped discussing the topic of UHI, in order to develop deeper understandings on the coupling relationship between UHI and the urbanization process [6,7].…”

Section: Introductionmentioning

confidence: 99%

The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Wang

et al. 2020

Land

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Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

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Section: Introductionmentioning

confidence: 99%

The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Wang

et al. 2020

Land

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“…Landscape pattern is one of the important influencing factors to alleviate the urban heat island (UHI) effect. The most important influencing factor is the area and shape of the landscape [18][19][20], which are related to a certain degree [21,22], effecting the cooling efficiency of the green space on the surrounding environment [21]. The integration of the built environment and the ecological space is conducive to dissolving the unfavorable landscape pattern, improving the self-organization and independence of the city, and increasing the city's resilience.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The "sink" landscape is a landscape that has a mitigating effect on the UHI. The connotation of the "source-sink" landscape theory in UHI research has been widely recognized [18,40,42]. (The theory believes that the negative effects produced by the "source" landscape can be absorbed and offset by the "sink" landscape.…”

Section: Urban Density Resiliencementioning

confidence: 99%

Coordination Conflicts between Urban Resilience and Urban Land Evolution in Chinese Hilly City of Mianyang

et al. 2021

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Urban resilience, the combinational characteristic of nature and society, that reflects the dynamic accumulation process that is multi-level and multi-dimensional. Particularly, the rational spatial distribution structure of land mixture and compactness is an effective way to improve urban resilience because the evolution of morphology and density of the urban land blocks in the process of land spatial conversion reflect the performance characteristics of complexity, diversity, stability, compactness, and connectivity. Therefore, we evaluated the relationship between urban resilience and land use and land cover (LULC) change, to find the keys to resilient urban development for urban land and space planning. In this study, taking the Chinese hilly city of Mianyang as an example, the results show: (1) the complexity of homogeneous patch shape and heterogeneous patch combination leads to the decrease of urban morphology resilience. (2) the development trend of LULC spatial layout and structure ratio were more rational with the increased of land mixing degree. (3) the speed and intensity of urban expansion were basically coordinated with the development of urban resilience. The research provides the new ideas, approaches, and toolkits for solving the intractable problems of urban spatial planning based on coordinating conflicts between urban resilience and urban land evolution.

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“…Changes in land-use patterns related to the urban factory contribute to the spatial structuring of the urban landscape, which also influence energy transmission and balance [81,82]. These changes are considered a direct cause of the formation of the UHIs [83,84]. Thus, the relationship of changes in air temperature to land use and land cover is apparent.…”

Section: Morphological Descriptors Relevant To Air Temperature Estimamentioning

confidence: 99%

A New Approach for Understanding Urban Microclimate by Integrating Complementary Predictors at Different Scales in Regression and Machine Learning Models

Alonso¹,

Renard²

2020

Remote Sensing

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Climate change is a major contemporary phenomenon with multiple consequences. In urban areas, it exacerbates the urban heat island phenomenon. It impacts the health of the inhabitants and the sensation of thermal discomfort felt in urban areas. Thus, it is necessary to estimate as well as possible the air temperature at any point of a territory, in particular in view of the ongoing rationalization of the network of fixed meteorological stations of Météo-France. Understanding the air temperature is increasingly in demand to input quantitative models related to a wide range of fields, such as hydrology, ecology, or climate change studies. This study thus proposes to model air temperature, measured during four mobile campaigns carried out during the summer months, between 2016 and 2019, in Lyon (France), in clear sky weather, using regression models based on 33 explanatory variables from traditionally used data, data from remote sensing by LiDAR (Light Detection and Ranging), or Landsat 8 satellite acquisition. Three types of statistical regression were experimented: partial least square regression, multiple linear regression, and a machine learning method, the random forest regression. For example, for the day of August 30th, 2016, multiple linear regression explained 89% of the variance for the study days, with a root mean square error (RMSE) of only 0.23 °C. Variables such as surface temperature, Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI) have a strong impact on the estimation model. This study contributes to the emergence of urban cooling systems. The solutions available vary. For example, they may include increasing the proportion of vegetation on the ground, facades, or roofs, increasing the number of basins and water bodies to promote urban cooling, choosing water-retaining materials, humidifying the pavement, increasing the number of public fountains and foggers, or creating shade with stretched canvas.

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Studies on urban heat island from a landscape pattern view: a review

Cited by 24 publications

References 10 publications

The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Coordination Conflicts between Urban Resilience and Urban Land Evolution in Chinese Hilly City of Mianyang

A New Approach for Understanding Urban Microclimate by Integrating Complementary Predictors at Different Scales in Regression and Machine Learning Models

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