The suitability of the urban local climate zone classification scheme for surface temperature studies in distinct macroclimate regions

Eldesoky, Ahmed Hazem Mahmoud; Gil, Jorge; Pont, Meta Berghauser

doi:10.1016/j.uclim.2021.100823

Cited by 37 publications

(12 citation statements)

References 70 publications

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“…The LCZ system is capable of explaining the LST variability of different types [40] and the relationship between built lands and LST [41]. For 10 built LCZ types, the highest temperature usually occurs in the heavy industrial land in cities of different sizes [41] [42] or the large low-rise areas in Nanjing [43], within tropical, temperate and cold climate regions of the globe [44]. Nevertheless, compact and high-rise pattern contributes to an LST increase [22], and some studies [23] indicated that scattered high-rise buildings can facilitate LST reduction.…”

Section: Introductionmentioning

confidence: 99%

Variabilities of Land Surface Temperature and Frontal Area Index Based on Local Climate Zone

Zhao

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Urban temperature increase brings a challenge to public health so that urban warming has been widely concerned. Within the central area of Shenyang, a 3×3 fishnet with nine grids was built, to analyze land surface temperature (LST) and frontal area index (FAI) variations based on the local climate zone (LCZ) classification and to explore relationships among them to generate implications for using wind for urban cooling. The results indicate that LST in the 4# grid (central grid) was the highest (35.11 °C) among the nine grids. In general, a higher LST occurred in the grid with a larger building area, and vice versa. LCZ-G underwent the largest temperature reduction among the 17 LCZ types. LCZ-2 had the highest LST, while the LCZ-1 had the lowest LST among the three high and intensive building types, except for the LST in the 2# and 4# grids. The FAI in Shenyang decreased from the center to the surroundings. The FAI value was greatest in the 4# grid, and the lowest was in the 2# and 8# grids under the prevailing wind of summer and winter. The FAI variations suggested that prevailing SW, SSW, and S winds in summer were difficult to penetrate central urban area, and wind cooling effect could not perform. The prevailing NEN and EEN winds in winter could enter the central urban area, enhancing wind cooling effect, while it was a disadvantage in winter. Overall, there was a significant positive relationship among LST, FAI and area of LCZ-building.

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Section: Introductionmentioning

confidence: 99%

Variabilities of Land Surface Temperature and Frontal Area Index Based on Local Climate Zone

Zhao

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…The urban landscape classification in this study adopted the LCZ scheme by Stewart and Oke [17]. The recent and most widely used method for LCZ mapping was following the World Urban Data Access Portal Tools (WUDAPT) protocols [24][25][26][27][28]. WUDAPT is a tool to map the physical geography of cities worldwide using a standard classification scheme, Landsat data and crowdsourced knowledge [29].…”

Section: Methods 231 Lcz Mappingmentioning

confidence: 99%

Urban Heat Island Mitigation Strategy based on Local Climate Zone Classification using Landsat 8 satellite imagery

Yunita

Wibowo

Supriatna

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Appropriate strategies on urban climate mitigation should be formulated by considering the physical morphology of the urban landscape. This study aimed to investigate, analyze, and promote possible strategies to mitigate Jakarta’s urban heat island (UHI) phenomena. Jakarta’s local climate zone (LCZ) was classified into 17 classes using Landsat 8 data and the random forest method. Land surface temperature (LST) characteristic in each LCZ class was analyzed from 2018, 2019 and 2020. The result revealed that most of the local climate zone in Jakarta is dominated by LCZ 6 (open low-rise) and LCZ 3 (compact low-rise), which is the typical residential area in Jakarta. However, the mean LST in 2018, 2019 and 2020 showed that LCZ 3 (compact low-rise) and LCZ 7 (lightweight low-rise) are the areas that were most likely causing high surface temperature with the highest UHI intensity. During the COVID-19 pandemic in 2020, LST in Jakarta decreased drastically in some parts of the area, especially in public facility such as airport. However, the LST value in low-rise areas (LCZ 3 and LCZ 7) remains higher than the other LCZ classes. Materials of the building and land cover play a significant role in raising the land surface temperature. Therefore, mitigation strategies for urban heat islands in Jakarta should be focused on such particular areas mentioned.

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“…Since the LCZ typology was initially designed for urban temperature studies (Stewart and Oke, 2012), typical applications focus on the UHI, usually providing the context for designing and analysing observations from urban meteorological networks (Skarbit et al, 2017;Beck et al, 2018;Chieppa et al, 2018;Verdonck et al, 2018;Yang et al, 2018;Leconte et al, 2020;Milošević et al, 2021;Zong et al, 2021), from crowd-sourced data (Fenner et al, 2017;Varentsov et al, 2021;Fenner et al, 2021;Potgieter et al, 2021;Brousse et al, 2022), or from remote sensing (Wang and Ouyang, 2017;Bechtel et al, 2019b;Eldesoky et al, 2021;Stewart et al, 2021). However, the typology has been used for other purposes (see also Lehnert et al, 2021, for European applications), such as urban heat (risk) assessment studies (Verdonck et al, 2019b;Van de Walle et al, 2022), climate-sensitive design, land use/land cover change, urban planning (policies) (Perera and Emmanuel, 2018;Aminipouri et al, 2019;Vandamme et al, 2019;Maharoof et al, 2020;Chen et al, 2021b;Zhi et al, 2021), anthropogenic heat, building energy demand and consump-tion, carbon emissions (Wu et al, 2018;Santos et al, 2020;Yang et al, 2020;Benjamin et al, 2021;Kotharkar et al, 2022), quality of life (Sapena et al, 2021), urban ventilation (Z.…”

Section: )mentioning

confidence: 99%

A global map of local climate zones to support earth system modelling and urban-scale environmental science

Demuzere

Kittner

Martilli

et al. 2022

Earth Syst. Sci. Data

127

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Abstract. There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale. These data can support a range of environmental services, since cities are places of intense resource consumption and waste generation and of concentrated infrastructure and human settlement exposed to multiple hazards of natural and anthropogenic origin. In the face of climate change, urban data are also required to explore future urbanization pathways and urban design strategies in order to lock in long-term resilience and sustainability, protecting cities from future decisions that could undermine their adaptability and mitigation role. To serve this purpose, we present a 100 m-resolution global map of local climate zones (LCZs), a universal urban typology that can distinguish urban areas on a holistic basis, accounting for the typical combination of micro-scale land covers and associated physical properties. The global LCZ map, composed of 10 built and 7 natural land cover types, is generated by feeding an unprecedented number of labelled training areas and earth observation images into lightweight random forest models. Its quality is assessed using a bootstrap cross-validation alongside a thematic benchmark for 150 selected functional urban areas using independent global and open-source data on surface cover, surface imperviousness, building height, and anthropogenic heat. As each LCZ type is associated with generic numerical descriptions of key urban canopy parameters that regulate atmospheric responses to urbanization, the availability of this globally consistent and climate-relevant urban description is an important prerequisite for supporting model development and creating evidence-based climate-sensitive urban planning policies. This dataset can be downloaded from https://doi.org/10.5281/zenodo.6364594 (Demuzere et al., 2022a).

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The suitability of the urban local climate zone classification scheme for surface temperature studies in distinct macroclimate regions

Cited by 37 publications

References 70 publications

Variabilities of Land Surface Temperature and Frontal Area Index Based on Local Climate Zone

Variabilities of Land Surface Temperature and Frontal Area Index Based on Local Climate Zone

Urban Heat Island Mitigation Strategy based on Local Climate Zone Classification using Landsat 8 satellite imagery

A global map of local climate zones to support earth system modelling and urban-scale environmental science

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