Outdoor thermal comfort in different urban settings of sub-tropical high-density cities: An approach of adopting local climate zone (LCZ) classification

2019 ◽  
Vol 154 ◽  
pp. 227-238 ◽  
Author(s):  
Kevin Ka-Lun Lau ◽  
Sum Ching Chung ◽  
Chao Ren
Keyword(s):  
Thermal Comfort ◽  
High Density ◽  
Outdoor Thermal Comfort ◽  
Climate Zone ◽  
Urban Settings ◽  
Local Climate ◽  
Local Climate Zone

GIS-based mapping of Local Climate Zone in the high-density city of Hong Kong

Urban Climate ◽  
2018 ◽  
Vol 24 ◽  
pp. 419-448 ◽  
Author(s):  
Yingsheng Zheng ◽  
Chao Ren ◽  
Yong Xu ◽  
Ran Wang ◽  
Justin Ho ◽  
...  
Keyword(s):  
Hong Kong ◽  
High Density ◽  
Climate Zone ◽  
Local Climate ◽  
Local Climate Zone

scholarly journals Feature Importance Analysis for Local Climate Zone Classification Using a Residual Convolutional Neural Network with Multi-Source Datasets

2018 ◽  
Vol 10 (10) ◽  
pp. 1572 ◽  
Author(s):  
Chunping Qiu ◽  
Michael Schmitt ◽  
Lichao Mou ◽  
Pedram Ghamisi ◽  
Xiao Zhu
Keyword(s):  
Neural Network ◽  
Land Use ◽  
Convolutional Neural Network ◽  
Large Scale ◽  
Landsat 8 ◽  
Climate Zone ◽  
Local Climate ◽  
Feature Importance ◽  
Local Climate Zone ◽  
Sentinel 2

Global Local Climate Zone (LCZ) maps, indicating urban structures and land use, are crucial for Urban Heat Island (UHI) studies and also as starting points to better understand the spatio-temporal dynamics of cities worldwide. However, reliable LCZ maps are not available on a global scale, hindering scientific progress across a range of disciplines that study the functionality of sustainable cities. As a first step towards large-scale LCZ mapping, this paper tries to provide guidance about data/feature choice. To this end, we evaluate the spectral reflectance and spectral indices of the globally available Sentinel-2 and Landsat-8 imagery, as well as the Global Urban Footprint (GUF) dataset, the OpenStreetMap layers buildings and land use and the Visible Infrared Imager Radiometer Suite (VIIRS)-based Nighttime Light (NTL) data, regarding their relevance for discriminating different Local Climate Zones (LCZs). Using a Residual convolutional neural Network (ResNet), a systematic analysis of feature importance is performed with a manually-labeled dataset containing nine cities located in Europe. Based on the investigation of the data and feature choice, we propose a framework to fully exploit the available datasets. The results show that GUF, OSM and NTL can contribute to the classification accuracy of some LCZs with relatively few samples, and it is suggested that Landsat-8 and Sentinel-2 spectral reflectances should be jointly used, for example in a majority voting manner, as proven by the improvement from the proposed framework, for large-scale LCZ mapping.

Outdoor thermal comfort in a tropical coastal tourist resort in Haikou, China

2019 ◽  
Vol 29 (5) ◽  
pp. 730-745 ◽  
Author(s):  
Chunjing Shang ◽  
Xinyu Huang ◽  
Yufeng Zhang ◽  
Maoquan Chen
Keyword(s):  
Solar Radiation ◽  
Thermal Comfort ◽  
Thermal Sensation ◽  
Outdoor Thermal Comfort ◽  
Survey Period ◽  
Physiological Equivalent Temperature ◽  
Local Climate ◽  
Acceptable Range ◽  
Tropical Areas ◽  
Autumn And Winter

Considering the importance of thermal comfort in decision-making in tourism, a transverse study involving micrometeorological measurements and questionnaires was performed at a popular coastal destination during the seasons of spring, autumn and winter. We examined the thermal sensation and thermal acceptability using the physiological equivalent temperature (PET). The results indicate that tourists’ thermal sensations varied with the season and the neutral PETs were 19.2°C, 23.8°C and 23.3°C in winter, spring and autumn. The 90% acceptable ranges of the PET affected by the local climate were 19.6–29.5°C during the entire three-season survey period, 21.4–27.1°C in the spring, 19.2–32°C in the autumn and more than 15.9°C in the winter. The analysis of microclimate parameters that affect thermal comfort in three seasons reveals that people expected weaker solar radiation, stronger wind and lower humidity with the air temperature rising, and vice versa. The acceptable range of wind speed was 0.6–2.5 m/s in winter, 0.6–3.5 m/s in spring and autumn. The acceptable range of solar radiation was 0–150 W/m2 in autumn and 0–250 W/m2 in winter. These findings contribute to the better designs for coastal facilities and the thermal comfort of tropical areas.

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