scholarly journals CLASSIFICATION FRAMEWORK OF LOCAL CLIMATE ZONES USING WORLD URBAN DATABASE AND ACCESS PORTAL TOOLS: CASE STUDY OF ALEXANDRIA CITY, EGYPT

2020 ◽  
Author(s):  
SARAH M. ABOUGENDIA ◽  
HANY M. AYAD ◽  
ZEYAD T. EL-SAYAD
Keyword(s):  
Climate Zones ◽  
Local Climate ◽  
Classification Framework ◽  
Local Climate Zones ◽  
Alexandria City

scholarly journals Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones

2019 ◽  
Vol 11 (23) ◽  
pp. 2828
Author(s):  
Zhao ◽  
Ma ◽  
Zhong ◽  
Zhao ◽  
Cao
Keyword(s):  
Spatial Information ◽  
Conditional Random Field ◽  
Contextual Information ◽  
Spatial Smoothing ◽  
Unified Framework ◽  
Climate Zones ◽  
Local Climate ◽  
Remote Sensing Classification ◽  
Classification Framework ◽  
Local Climate Zones

Local climate zones (LCZ) have become a generic criterion for climate analysis among global cities, as they can describe not only the urban climate but also the morphology inside the city. LCZ mapping based on the remote sensing classification method is a fundamental task, and the protocol proposed by the World Urban Database and Access Portal Tools (WUDAPT) project, which consists of random forest classification and filter-based spatial smoothing, is the most common approach. However, the classification and spatial smoothing lack a unified framework, which causes the appearance of small, isolated areas in the LCZ maps. In this paper, a spatial-contextual information-based self-training classification framework (SCSF) is proposed to solve this LCZ classification problem. In SCSF, conditional random field (CRF) is used to integrate the classification and spatial smoothing processing into one model and a self-training method is adopted, considering that the lack of sufficient expert-labeled training samples is always a big issue, especially for the complex LCZ scheme. Moreover, in the unary potentials of CRF modeling, pseudo-label selection using a self-training process is used to train the classifier, which fuses the regional spatial information through segmentation and the local neighborhood information through moving windows to provide a more reliable probabilistic classification map. In the pairwise potential function, SCSF can effectively improve the classification accuracy by integrating the spatial-contextual information through CRF. The experimental results prove that the proposed framework is efficient when compared to the traditional mapping product of WUDAPT in LCZ classification.

Mapping the local climate zones of urban areas by GIS-based and WUDAPT methods: A case study of Hong Kong

Urban Climate ◽  
2018 ◽  
Vol 24 ◽  
pp. 567-576 ◽  
Author(s):  
Ran Wang ◽  
Chao Ren ◽  
Yong Xu ◽  
Kevin Ka-Lun Lau ◽  
Yuan Shi
Keyword(s):  
Hong Kong ◽  
Urban Areas ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones

scholarly journals Issues with using Landsat based Surface Temperature for Investigating Linkage between Local Climate Zones and Surface Urban Heat Island in Different Seasons: A Case Study of Manhattan, N.Y.

2019 ◽  
Author(s):  
Parth Bansal
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Summer Season ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Different Seasons ◽  
Urban Heat

This study was conceptualized to investigate differences in surface temperature profile of Local Climate Zones (LCZ) classes in different seasonal conditions. Manhattan was selected as case study due to its dense, but heterogeneous built-up profile and presence of green area which formed the baseline for temperature comparison. However, this study failed to find significant results, in terms of the distinct Urban Heat Island (UHI) feature often reported in literature. Instead, this study suggests that in the case of Manhattan UHI is predominantly within ± 0.5 C° except during summer season. In summer season, where more difference in built and green LCZ is observed, the noise in data, defined by standard deviation of surface temperature in the class, is also higher. Thus, our study concludes that Landsat based surface temperature should be used with extreme caution to investigate UHI since most imagery is taken during day time.

scholarly journals How relevant are local climate zones and urban climate zones for urban climate research? Dijon (France) as a case study

Urban Climate ◽  
2018 ◽  
Vol 26 ◽  
pp. 258-274 ◽  
Author(s):  
Yves Richard ◽  
Justin Emery ◽  
Julita Dudek ◽  
Julien Pergaud ◽  
Carmela Chateau-Smith ◽  
...  
Keyword(s):  
Urban Climate ◽  
Climate Zones ◽  
Local Climate ◽  
Climate Research ◽  
Local Climate Zones
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