Local Climate Zone Mapping for Energy Resilience: A Fine-grained and 3D Approach

Quan, Steven Jige; Dutt, Florina; Woodworth, Erik; Yamagata, Yoshiki; Yang, Perry Pei‐Ju

doi:10.1016/j.egypro.2017.03.883

Cited by 37 publications

(20 citation statements)

References 7 publications

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“…It is worth noting that, although the building classes are currently of moderate accuracy, i.e., approximately 40%, the potential of LCZ maps can also be explored as they carry more detailed information on urban morphology than do other classification datasets and they are valued at both the domestic and the international levels. At the national level, the development of LCZ maps for 20 individual cities and 3 major economic regions in China can serve as a fundamental database for various applications, such as urban climate investigation 32 , urban energy consumption estimation 26 , urbanization projection and air pollution distribution detection 43 . The correlation analysis results of the developed LCZ data show the morphological characteristics of both built-up areas and natural landscapes of Chinese cities and regions.…”

Section: Resultsmentioning

confidence: 99%

“…The LCZ scheme categorizes the urban surface into 10 built types and 7 natural types 15,16 , from which UCPs can be determined and thereby improved climate model results can be achieved. Due to its detailed description of urban areas, the LCZ scheme is gaining popularity in studies of local air/surface temperature features 16–21 , urban heat islands 22–24 , urban energy budgets 25,26 , outdoor thermal comfort 27,28 , machine learning 20,29 and urban ventilation simulations 30 . When historical LCZ datasets are available, there are useful for examining the impacts of local cover change on the spatial pattern of land surface temperature 31 , evolution of the climatological effects of urbanization 32 , and urban growth monitoring 33 .…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Local Climate Zone Classification Maps of Cities in China and Feasible Refinements

Ren

Cai

et al. 2019

Sci Rep

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Local climate zone (LCZ) maps that describe the urban surface structure and cover with consistency and comparability across cities are gaining applications in studies of urban heat waves, sustainable urbanization and urban energy balance. Following the standard World Urban Database and Access Portal Tools (WUDAPT) method, we generated LCZ maps for over 20 individual cities and 3 major economic regions in China. Based on the confusion matrices constructed by manual comparison between the predicted classes and ground truths, we highlight the following: (1) notable variation in overall accuracies (i.e., 60%–89%) among cities were observed, which was mainly due to class incompleteness and distinct proportions of natural landscapes; (2) building classes in selected cities were poorly classified in general, with a mean accuracy of 48%; (3) the sparsely built class (i.e., LCZ 9), which is rare in the selected Chinese cities, had the lowest classification accuracy (32% on average), and the class of low plants had the widest accuracy range. The findings indicate that the standard WUDAPT method alone is insufficient for generating LCZ products that demonstrate practical value, especially for built-up areas in China, and the misclassification is largely caused by the lack of building height data. This result is confirmed by a refinement test, in which the urban DEM retrieved from Sentinel-1 data with radar interferometry technique was used. The study shows a detailed and comprehensive assessment of applying the WUDAPT method in China and a feasible refinement strategy to improve the classification accuracy, especially for the built-up types of LCZ. The study could serve as a useful reference for generating quality-ensured LCZ maps. This study also examines and explores the relationship between socio-economic status and LCZ products, which is essential for further implementations.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Local Climate Zone Classification Maps of Cities in China and Feasible Refinements

Ren

Cai

et al. 2019

Sci Rep

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“…Future 3D urban growth is an inevitable trend, and the LCZ will help to investigate urban thermal environmental processes and then to develop mitigation measures. LCZ has been popularly used in studies of urban LST features [9][10][11][12], UHI [13,14], urban ventilation [6], outdoor thermal comfort [15], and urban energy budgets [16,17]. WUDAPT (the World Urban Database and Access Portal Tools) provide a standard workflow for LCZ classification from free satellite remote sensing data (e.g., Landsat), using Google Earth images for sampling selection and SAGA software for classification [18].…”

Section: Introductionmentioning

confidence: 99%

Urban Thermal Characteristics of Local Climate Zones and Their Mitigation Measures across Cities in Different Climate Zones of China

Yang

Qiao

et al. 2021

Remote Sensing

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Understanding the urban thermal environment is vital for improving urban planning and strategy development when mitigating urban heat islands. However, urban thermal characteristics of local climate zones (LCZ) are different within cities and most studies lack regional perspective. This study explored surface thermal performances of cities in three urban agglomerations (Jing-Jin-Ji, Yangtze River Delta and Pearl River Delta) in China using MODIS land surface temperature (LST). Besides that, the diurnal and seasonal LST variations of LCZs are also studied. Moreover, the optimal LCZs for better urban cooling are also investigated in this study. Although the thermal distributions of LCZs are different in China, there are still some similar features. Our four key findings were as follows. (1) LCZs in China are well classified, with average overall accuracy of 82% being higher than that in some previous studies. (2) The LST of mid-rise (LCZ 2, 5) is higher than that of high- and low-rise buildings (LCZ 1, 3, 4, 6); and compact buildings are warmer than open buildings (LCZ 1–3 > LST 4–6) in summer of China. That shows both mid-rise and compact buildings are not beneficial to cool urban. In addition, LST variations at daytime and in summer are more significant than nighttime and other seasons. (3) LST differences within LCZs are significant at p < 0.05, and are most significant in Jing-Jin-Ji (JJJ). The LST difference within built types (LCZ 1–10) is more significant than within natural types (LCZ A–G), showing that built types alteration will be more effective for thermal environmental improvement. (4) Under the current population and urban area, increasing greenness and water area in compact high-rise buildings are the most effective strategies for urban cooling in all three urban agglomerations, with the largest reduction in LST of 4.11 K in JJJ. These findings will provide support for thermal environment mitigation, urban planning and sustainable urban development.

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“…In addition to its strong usefulness in urban climate studies (Stewart and Oke, 2012, Stewart et al, 2014, Fenner et al, 2017, Quan et al, 2017, Quanz et al, 2018, Kotharkar and Bagade, 2018), the potential of LCZ for classifying the internal urban structure of human settlements, to provide auxiliary data for applications such as disaster mitigation, urban planning, and population assessment (Bechtel et al, 2016, Wicki and Parlow, 2017) in a rapidly urbanizing world (Taubenböck et al, 2012) has recently been explored. Furthermore, accurate LCZ maps can be used to extract and analyze reliable and detailed information on the extent of human settlement to provide assistance in fulfilling the evaluation and monitoring requirements of the 2030 Agenda for Sustainable Development and provide reference information for achieving the Sustainable Development Goal 11 (United and Nations, 2015), “Make cities and human settlements inclusive, safe, resilient, and sustainable.” As an example of such applications, the LCZ framework was exploited to monitor sustainable urbanization in terms of access to safe housing using data from an exemplary study in Pretoria and Johannesburg, South Africa (Danylo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network

Qiu

Mou

Schmitt

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

132

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The local climate zone (LCZ) scheme was originally proposed to provide an interdisciplinary taxonomy for urban heat island (UHI) studies. In recent years, the scheme has also become a starting point for the development of higher-level products, as the LCZ classes can help provide a generalized understanding of urban structures and land uses. LCZ mapping can therefore theoretically aid in fostering a better understanding of spatio-temporal dynamics of cities on a global scale. However, reliable LCZ maps are not yet available globally. As a first step toward automatic LCZ mapping, this work focuses on LCZ-derived land cover classification, using multi-seasonal Sentinel-2 images. We propose a recurrent residual network (Re-ResNet) architecture that is capable of learning a joint spectral-spatial-temporal feature representation within a unitized framework. To this end, a residual convolutional neural network (ResNet) and a recurrent neural network (RNN) are combined into one end-to-end architecture. The ResNet is able to learn rich spectral-spatial feature representations from single-seasonal imagery, while the RNN can effectively analyze temporal dependencies of multi-seasonal imagery. Cross validations were carried out on a diverse dataset covering seven distinct European cities, and a quantitative analysis of the experimental results revealed that the combined use of the multi-temporal information and Re-ResNet results in an improvement of approximately 7 percent points in overall accuracy. The proposed framework has the potential to produce consistent-quality urban land cover and LCZ maps on a large scale, to support scientific progress in fields such as urban geography and urban climatology.

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Local Climate Zone Mapping for Energy Resilience: A Fine-grained and 3D Approach

Cited by 37 publications

References 7 publications

Assessment of Local Climate Zone Classification Maps of Cities in China and Feasible Refinements

Assessment of Local Climate Zone Classification Maps of Cities in China and Feasible Refinements

Urban Thermal Characteristics of Local Climate Zones and Their Mitigation Measures across Cities in Different Climate Zones of China

Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network

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