A systematic review of GIS-based local climate zone mapping studies

Quan, Steven Jige; Bansal, Parth

doi:10.1016/j.buildenv.2021.107791

Cited by 56 publications

(49 citation statements)

References 38 publications

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“…Standardized procedures for delimiting LCZ are aimed at defining larger territorial units of the same morphology of built-up areas and land cover in a grid scale of 100 × 100 m. A more universal use of the LCZ classification would be helped by the choice of more detailed data and the resulting scale of spatial units [25,26], or a link to territorial units of administrative-functional use [29]. For practical application of the results is more suitable, when units delimited as urban blocks according to type of built-up area are used for the assessment of the territory on the basis of LCZ [27]. On the other hand, the standardization of procedures is limited by the fact that LCZ categorization is applied worldwide in different climatic zones with different urban development.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the definition of local climate zones (LCZ), tools for modeling of urban climate have been developed that can be used for the purpose of planning for adaptation measures [22][23][24]. Professional discussion on the LCZ delimitation has been happening in terms of scale of spatial units processed via GIS-based [25][26][27], selection of thermal analysis techniques [28,29] or automatic data processing [27,29]. The current analysis of European LCZ studies shows the need to focus on the refining LCZ and higher accuracy in defining training areas [28].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Ecohydrological and Climatological Zoning of the Cities: Case Study of the City of Pilsen

Kopp

Frajer

Novotná

et al. 2021

IJGI

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Standardized delimiting of local climate zones (LCZ) will be better applicable to the urban adaptation to climate change when the ecohydrological properties of LCZ units are known. Therefore, the properties of LCZ units based on the methodology of ecohydrological zoning of the urban landscape, which was created in GIS as a basis for planning blue-green infrastructure of cities in the Czech Republic, are presented in the paper. The goal of this study is to compare approaches and results of our own ecohydrological zonation and standardized LCZ delimiting in the city of Pilsen. Both methodological approaches differ in input data, resolution details and parameters used. The results showed that the areas of the individual LCZ classes show different levels of ecohydrological qualities. Internal heterogeneity of LCZ classes demonstrated by variance of ecohydrological parameters’ values can be partly explained by different techniques and data sources for delimitation of both zonations, but by different sets of delimitation criteria. The discussion is held on the importance of terrain slope for supplementing the LCZ classification. A case study can be a stimulus for further development of holistic urban zoning methodologies that would take into account both climatological and ecohydrological conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Ecohydrological and Climatological Zoning of the Cities: Case Study of the City of Pilsen

Kopp

Frajer

Novotná

et al. 2021

IJGI

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“…CAD software allows organizations to view the details of a single drawing, while GIS allows organizations to view multiple sites with less detail [ 31 ]. As a decision support system, GIS can explain and solve practical problems in various fields such as land resource management, surveying and mapping, urban planning, market analysis, geology, and hydrology [ 32 ]. CAD applications usually focus on design, which is suitable for the scale of buildings or infrastructure engineering, and usually lack the reliable attribute model.…”

Section: Methodsmentioning

confidence: 99%

Intelligent Optimization of Tower Crane Location and Layout Based on Firefly Algorithm

Liu

Zhang

Han

et al. 2022

Computational Intelligence and Neuroscience

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The existing tower crane positioning layout mainly depends on the experience of construction personnel, and the best tower crane positioning can be found through a large number of manual data calculation. This manual method is time-consuming and impractical. In view of this, aiming at the current situation that building information modeling (BIM) software can only obtain the relative coordinates of components, this article puts forward the key technology of importing computer-aided design (CAD) graphics into geographic information system (GIS) software to automatically obtain the world coordinate information. By clarifying the transfer relationship between the component material supply point, the component initial positioning point, and the tower crane optional positioning point, as well as the cooperative relationship between each positioning point and the tower crane operation, the tower crane positioning optimization model is formed, and the firefly algorithm is used to automatically calculate and generate the best positioning layout method of the tower crane on the project site. In this study, the vertical transportation and positioning of components are studied, and intelligent construction is formed by integrating information technology. It can further enrich the functions of perception, analysis, decision-making, and optimization; realize the decision-making intelligence of industrial buildings; and achieve the organic unity of engineering construction execution system and decision-making command system.

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“…In fact, the percentage of vegetation and the PLAND were both highly correlated with surface temperature [9][10][11][12][13]. Besides this, scholars have conducted studies related to thermal environment effects of the land-use/land-cover change with various methods in recent decades [14,15]. The correlation analysis of the surface temperature and remote sensing index have been widely used, and Autocorrelation using Getis-Ord Gi* was also widely used to explore the relationship between the built-up land and LST [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…Besides this, scholars have conducted studies related to thermal environment effects of the land-use/land-cover change with various methods in recent decades [14,15]. The correlation analysis of the surface temperature and remote sensing index have been widely used, and Autocorrelation using Getis-Ord Gi* was also widely used to explore the relationship between the built-up land and LST [14][15][16]. However, the above-mentioned studies generally provide limited information on the response mechanism between the PLAND and LST, and it is of particular significance to deeply understand the impacts of built-up land expansion on the surface thermal environment in fast-growing cities [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Thermal Environment Effects of Built-Up Land Expansion in Shijiazhuang

Qin

Liu

Shang

et al. 2022

Land

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Exploring the thermal environment effects of built-up land expansion can lay a firm foundation for urban planning and design. This study revealed the spatiotemporal dynamic characteristics of built-up land and heat island center points in Shijiazhuang using land-use/land-cover data and land surface temperature (LST) products from 1996 to 2019, and the response mechanism between the percentage of built-up land (PLAND) and LST with the grid sampling method and statistical analysis. Results indicated that heat islands are mainly clustered in the downtown, built-up areas of counties and the Hutuo River Basin. The spatiotemporal shift direction of the center point of the urban heat island (UHI) and built-up land in the whole study area varied due to the eco-environmental transformation of the Hutuo River Basin. In areas far from the Hutuo River Basin, the center points of UHI and built-up land were shifted in a similar direction. There is a remarkable linear correlation between the PLAND and LST, the correlation coefficient of which was higher than 0.7 during the study period. Areas with PLAND > 60% are urban regions with stronger heat island effects, and areas with PLAND < 55% are villages and towns where the temperature raised more slowly.

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A systematic review of GIS-based local climate zone mapping studies

Cited by 56 publications

References 38 publications

Comparison of Ecohydrological and Climatological Zoning of the Cities: Case Study of the City of Pilsen

Comparison of Ecohydrological and Climatological Zoning of the Cities: Case Study of the City of Pilsen

Intelligent Optimization of Tower Crane Location and Layout Based on Firefly Algorithm

Thermal Environment Effects of Built-Up Land Expansion in Shijiazhuang

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