Local climate zone ventilation and urban land surface temperatures: Towards a performance-based and wind-sensitive planning proposal in megacities

2019 ◽  
Vol 47 ◽  
pp. 101487 ◽  
Author(s):  
Jun Yang ◽  
Shanhe Jin ◽  
Xiangming Xiao ◽  
Cui Jin ◽  
Jianhong (Cecilia) Xia ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Land ◽  
Climate Zone ◽  
Local Climate ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Local Climate Zone ◽  
A Performance

Inter-local climate zone differentiation of land surface temperatures for Management of Urban Heat in Nairobi City, Kenya

Urban Climate ◽  
2020 ◽  
Vol 31 ◽  
pp. 100540 ◽  
Author(s):  
Emmanuel Matsaba Ochola ◽  
Elham Fakharizadehshirazi ◽  
Aggrey Ochieng Adimo ◽  
John Bosco Mukundi ◽  
John Mwibanda Wesonga ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Zone ◽  
Local Climate ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Urban Heat ◽  
Local Climate Zone

scholarly journals The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season

2015 ◽  
Vol 7 (4) ◽  
pp. 4689-4706 ◽  
Author(s):  
Sadroddin Alavipanah ◽  
Martin Wegmann ◽  
Salman Qureshi ◽  
Qihao Weng ◽  
Thomas Koellner
Keyword(s):  
Land Surface ◽  
Warm Season ◽  
Urban Land ◽  
Surface Temperatures ◽  
Land Surface Temperatures

scholarly journals Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China

2021 ◽  
Vol 13 (10) ◽  
pp. 1902
Author(s):  
Chaomin Chen ◽  
Hasi Bagan ◽  
Xuan Xie ◽  
Yune La ◽  
Yoshiki Yamagata
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Grid Cell ◽  
Classification Model ◽  
Textural Features ◽  
Climate Zone ◽  
Local Climate ◽  
Dual Polarized ◽  
Local Climate Zone ◽  
Sentinel 2

Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.

A physical model-based method for retrieving urban land surface temperatures under cloudy conditions

2019 ◽  
Vol 230 ◽  
pp. 111191 ◽  
Author(s):  
Peng Fu ◽  
Yanhua Xie ◽  
Qihao Weng ◽  
Soe Myint ◽  
Katherine Meacham-Hensold ◽  
...  
Keyword(s):  
Physical Model ◽  
Land Surface ◽  
Urban Land ◽  
Model Based ◽  
Surface Temperatures ◽  
Land Surface Temperatures
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