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 ◽  
...  
Author(s):  
Jinling Quan

Urban forms and functions have critical impacts on urban heat islands (UHIs). The concept of a “local climate zone” (LCZ) provides a standard and objective protocol for characterizing urban forms and functions, which has been used to link urban settings with UHIs. However, only a few structure types and surface cover properties are included under the same climate background or only one or two time scales are considered with a high spatial resolution. This study assesses multi-temporal land surface temperature (LST) characteristics across 18 different LCZ types in Beijing, China, from July 2017 to June 2018. A geographic information system-based method is employed to classify LCZs based on five morphological and coverage indicators derived from a city street map and Landsat images, and a spatiotemporal fusion model is adopted to generate hourly 100-m LSTs by blending Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and FengYun-2F LSTs. Then, annual and diurnal cycle parameters and heat island and cool island (HI or CI) frequency are linked to LCZs at annual, seasonal, monthly, and diurnal scales. Results indicate that: (1) the warmest zones are compact and mid and low-rise built-up areas, while the coolest zones are water and vegetated types; (2) compact and open high-rise built-up areas and vegetated types have seasonal thermal patterns but with different causes; (3) diurnal temperature ranges are the highest for compact and large low-rise settings but the lowest for water and dense or scattered trees; and (4) HIs are the most frequent summertime and daytime events, while CIs occur primarily during winter days, making them more or less frequent for open or compact and high- or low-rise built-up areas. Overall, the distinguishable LSTs or UHIs between LCZs are closely associated with the structure and coverage properties. Factors such as geolocation, climate, and layout also interfere with the thermal behavior. This study provides comprehensive information on how different urban forms and functions are related to LST variations at different time scales, which supports urban thermal regulation through urban design.


2014 ◽  
Vol 21 ◽  
pp. 3-13 ◽  
Author(s):  
George Thomas ◽  
A.P. Sherin ◽  
Shareekul Ansar ◽  
E.J. Zachariah

2019 ◽  
Vol 136 ◽  
pp. 05011
Author(s):  
Kaikai Mu ◽  
Yan Liu ◽  
Moyan Zhang ◽  
Bing Han ◽  
Liu Yang

Urbanization seriously affects the urban climate and the quality of human settlement. Based on Landsat8 remote sensing and building vector data, local climate zone (LCZ) method is employed to study the influences of urban form on land surface temperature (LST) of Xi'an. The results confirmed that the LST of the built-up LCZ is higher than the land cover LCZ. In built-up LCZ, LST is increasing with the increasing of building density. In land cover LCZ, the LST of bare land is the highest. Surface urban heat island (SUHI) of 14 samples in LCZ also been calculated. Highest SUHI intensity is found in low-rise buildings with high density area. LST intensity of water body and forest are lower than others in land cover LCZ.


2021 ◽  
Vol 13 (10) ◽  
pp. 1902
Author(s):  
Chaomin Chen ◽  
Hasi Bagan ◽  
Xuan Xie ◽  
Yune La ◽  
Yoshiki Yamagata

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.


2016 ◽  
Vol 25 (6) ◽  
pp. 2609-2616 ◽  
Author(s):  
Zhihao Wang ◽  
Wu Xing ◽  
Yi Huang ◽  
Tongan Xie

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