Evaluation of seasonal variability in magnitude of urban heat islands using local climate zone classification and surface albedo

2021 ◽  
Author(s):  
K. Dutta ◽  
D. Basu ◽  
S. Agrawal
Keyword(s):  
Seasonal Variability ◽  
Surface Albedo ◽  
Urban Heat Islands ◽  
Climate Zone ◽  
Local Climate ◽  
Heat Islands ◽  
Urban Heat ◽  
Local Climate Zone

scholarly journals Multi-Temporal Effects of Urban Forms and Functions on Urban Heat Islands Based on Local Climate Zone Classification

2019 ◽  
Vol 16 (12) ◽  
pp. 2140 ◽  
Author(s):  
Jinling Quan
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Forms ◽  
Heat Islands ◽  
Multi Temporal ◽  
Urban Heat ◽  
Local Climate Zone

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.

scholarly journals Urban heat island analysis using the ‘local climate zone’ scheme in Presidente Prudente, Brazil

2018 ◽  
pp. 107 ◽  
Author(s):  
Renata dos Santos Cardoso ◽  
Margarete Cristiane de Costa Trindade Amorim
Keyword(s):  
Urban Morphology ◽  
Urban Heat Islands ◽  
Climate Zone ◽  
Local Climate ◽  
Heat Islands ◽  
Rural Landscapes ◽  
Recent Climate ◽  
Urban Heat ◽  
Mobile Measurements ◽  
Local Climate Zone

Although urban heat islands (UHIs) have been widely studied, a recent climate-based classification of urban and rural landscapes provides a new framework for UHI researchers. Based on the Local Climate Zone (LCZ) system, we studied heat islands in a tropical city, analysing the effects of urban morphology and surface cover on UHI intensity. Mobile measurements were taken in Presidente Prudente, São Paulo, Brazil, on five winter evenings (June and July 2014). Observed temperatures across the city show compact built zones with higher temperatures, followed by open midsize, lightweight low-rise, and low plants zones. A maximum nocturnal temperature difference of more than 5°C was detected between areas with significant differences in physical characteristics (ΔT LCZ 24–D), whereas average inter-zone thermal differences reached 3.8ºC (ΔT LCZ 3–D).

scholarly journals Advances of Local Climate Zone Mapping and Its Practice Using Object-Based Image Analysis

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1146
Author(s):  
Lei Ma ◽  
Xiaoxiang Zhu ◽  
Chunping Qiu ◽  
Thomas Blaschke ◽  
Manchun Li
Keyword(s):  
Image Analysis ◽  
Urban Heat Islands ◽  
Local Climate ◽  
Heat Islands ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Local Climate Zones ◽  
Urban Heat ◽  
Future Object ◽  
Local Climate Zone

In the context of climate change and urban heat islands, the concept of local climate zones (LCZ) aims for consistent and comparable mapping of urban surface structure and cover across cities. This study provides a timely survey of remote sensing-based applications of LCZ mapping considering the recent increase in publications. We analyze and evaluate several aspects that affect the performance of LCZ mapping, including mapping units/scale, transferability, sample dataset, low accuracy, and classification schemes. Since current LCZ analysis and mapping are based on per-pixel approaches, this study implements an object-based image analysis (OBIA) method and tests it for two cities in Germany using Sentinel 2 data. A comparison with a per-pixel method yields promising results. This study shall serve as a blueprint for future object-based remotely sensed LCZ mapping approaches.

scholarly journals Inclusion of vegetation in the Town Energy Balance model for modeling urban green areas

2012 ◽  
Vol 5 (2) ◽  
pp. 1295-1340 ◽  
Author(s):  
A. Lemonsu ◽  
V. Masson ◽  
L. Shashua-Bar ◽  
E. Erell ◽  
D. Pearlmutter
Keyword(s):  
Global Climate ◽  
A Priori ◽  
Urban Canopy ◽  
Bare Soil ◽  
Urban Heat Islands ◽  
Balance Model ◽  
Local Climate ◽  
Heat Islands ◽  
Planning Strategy ◽  
Urban Heat

Abstract. Cities impact both local climate, through urban heat islands, and global climate, because they are an area of heavy greenhouse gas release into the atmosphere due to heating, air conditioning and traffic. Including more vegetation into cities is a planning strategy having possible positive impacts for both concerns. Improving vegetation representation into urban models will allow to address more accurately these questions. This paper presents an improvement of the TEB urban canopy model. Vegetation is directly included inside the canyon, allowing shadowing of grass by buildings, better representation of urban canopy form, and, a priori, a more accurate simulation of canyon air microclimate. The development is performed so that any vegetation model can be used to represent the vegetation part. Here the ISBA model is used. The model results are compared to microclimatic and evaporation measurements performed in small courtyards in a very arid region of Israel. Two experimental landscaping strategies – bare soil or irrigated grass in the courtyard – are observed and simulated. The new version of the model with integrated vegetation performs better than if vegetation is treated outside the canyon. Surface temperatures are closer to the observations, especially at night when radiative trapping is important. The integrated vegetation version simulates a more humid air inside the canyon. The microclimatic quantities are better simulated with this new version. This opens opportunities to study with better accuracy the urban microclimate, down to the micro (or canyon) scale.

scholarly journals Analysis of Urban Heat Island in Kochi, India, Using a Modified Local Climate Zone Classification

2014 ◽  
Vol 21 ◽  
pp. 3-13 ◽  
Author(s):  
George Thomas ◽  
A.P. Sherin ◽  
Shareekul Ansar ◽  
E.J. Zachariah
Keyword(s):  
Urban Heat Island ◽  
Heat Island ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Heat ◽  
Local Climate Zone

scholarly journals Investigations of Surface Urban Heat Island Effect Based on Local Climate Zone Method: A Case of Xi'an

2019 ◽  
Vol 136 ◽  
pp. 05011
Author(s):  
Kaikai Mu ◽  
Yan Liu ◽  
Moyan Zhang ◽  
Bing Han ◽  
Liu Yang
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Urban Form ◽  
Heat Island ◽  
Zone Method ◽  
Climate Zone ◽  
Local Climate ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Local Climate Zone

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.

Use of Local Climate Zones to investigate surface urban heat islands in Texas

2020 ◽  
Vol 57 (8) ◽  
pp. 1083-1101 ◽  
Author(s):  
Chunhong Zhao ◽  
Jennifer L. R. Jensen ◽  
Qihao Weng ◽  
Nathan Currit ◽  
Russell Weaver
Keyword(s):  
Urban Heat Islands ◽  
Climate Zones ◽  
Local Climate ◽  
Heat Islands ◽  
Local Climate Zones ◽  
Urban Heat

scholarly journals Investigating Surface Urban Heat Islands in South America Based on MODIS Data from 2003–2016

2019 ◽  
Vol 11 (10) ◽  
pp. 1212 ◽  
Author(s):  
Xiaojun Wu ◽  
Guangxing Wang ◽  
Rui Yao ◽  
Lunche Wang ◽  
Deqing Yu ◽  
...  
Keyword(s):  
South America ◽  
Urban Area ◽  
Urban Heat Islands ◽  
Anthropogenic Heat ◽  
Rural Land ◽  
Night Time ◽  
Climate Zone ◽  
Heat Islands ◽  
Urban Heat ◽  
The Mean

Surface urban heat islands (SUHIs) have been investigated in many regions around the world, but little attention has been given with regard to SUHIs in South America. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data was used to investigate the diurnal, seasonal, and interannual variations in the SUHI intensity (SUHII, the urban LST minus the rural LST) in 44 South American cities in different climate zones and types of rural land. To examine the effects of factors that may influence the SUHII, correlations between the SUHII and the enhanced vegetation index (EVI), urban area, population, altitude, and anthropogenic heat emissions were performed. The results showed that the SUHI effect was obvious in South America. The mean daytime SUHII was higher than the mean night-time SUHII in all areas except for the arid climate zone. In the daytime, the summer displayed a stronger SUHII in the warm temperate climate zone than the other seasons. The night-time SUHII showed less obvious seasonal variations. In addition, the surrounding land cover influenced the SUHII. During the day, the SUHII was therefore stronger in rural areas that were covered by forests than in other types of rural land. Interannually, most cities showed an insignificant temporal trend in the SUHII from 2003 to 2016. The daytime SUHII was significantly and negatively correlated with the ∆EVI (the urban EVI minus the rural EVI) across the 44 cities, but a poor relationship was observed at night. In addition, anthropogenic heat emissions were positively correlated with the night-time SUHII. Urban area, population, and altitude were weakly correlated with the SUHII, which suggested that these factors may not have a significant impact on the spatial variations in the SUHII in South America.

scholarly journals Confusion Matrices Help Prevent Reader Confusion: Reply to Bechtel, B., et al. A Weighted Accuracy Measure for Land Cover Mapping: Comment on Johnson et al. Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment, Remote Sens. 2019, 11, 2420

2020 ◽  
Vol 12 (11) ◽  
pp. 1771
Author(s):  
Brian Alan Johnson ◽  
Shahab Eddin Jozdani
Keyword(s):  
Land Cover ◽  
Thermal Environment ◽  
Confusion Matrix ◽  
Urban Heat Islands ◽  
Estimation Errors ◽  
Climate Zone ◽  
Local Climate ◽  
Accuracy Measure ◽  
Local Climate Zone ◽  
Map Accuracy

Land use/land cover (LULC) maps are now being used across disciplines for many different types of applications, e.g., to analyze urban heat islands or rainfall-runoff dynamics. Traditional map accuracy metrics are limited in this regard, as they only assess LULC map thematic accuracy. In reality, some types of misclassification lead to larger estimation errors for these specific applications. In a previous study, we developed a new map accuracy metric (referred to here as “JJ19”) to assess the accuracy of local climate zone maps for urban microclimate analysis. In the previous work, we also attempted to reproduce another metric (weighted accuracy (WA)) proposed for this purpose, but misinterpreted it due to a lack of methodological information available (principally, the lack of a confusion matrix to demonstrate how WA was derived). We sincerely thank the authors of Bechtel et al. 2019 for providing more information on WA in response to our previous study and are happy to report that we found that the metric is now both reproducible and valid. On the other hand, we found some other aspects of Bechtel et al. 2019’s study to be inaccurate, particularly their claims regarding the suitability of the JJ19 metric. Finally, we made a minor improvement to the JJ19 metric based on Bechtel et al.’s comments.

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