scholarly journals Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review

Environments ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 105
Author(s):  
Cátia Rodrigues de Almeida ◽  
Ana Cláudia Teodoro ◽  
Artur Gonçalves
Keyword(s):  
Remote Sensing ◽  
Systematic Review ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Urban Heat Islands ◽  
Pollution Effects ◽  
Heat Islands ◽  
Urban Heat ◽  
Number Of Publications

Urban Heat Islands (UHI) consist of the occurrence of higher temperatures in urbanized areas when compared to rural areas. During the warmer seasons, this effect can lead to thermal discomfort, higher energy consumption, and aggravated pollution effects. The application of Remote Sensing (RS) data/techniques using thermal sensors onboard satellites, drones, or aircraft, allow for the estimation of Land Surface Temperature (LST). This article presents a systematic review of publications in Scopus and Web of Science (WOS) on UHI analysis using RS data/techniques and LST, from 2000 to 2020. The selection of articles considered keywords, title, abstract, and when deemed necessary, the full text. The process was conducted by two independent researchers and 579 articles, published in English, were selected. Qualitative and quantitative analyses were performed. Cfa climate areas are the most represented, as the Northern Hemisphere concentrates the most studied areas, especially in Asia (69.94%); Landsat products were the most applied to estimates LST (68.39%) and LULC (55.96%); ArcGIS (30.74%) was most used software for data treatment, and correlation (38.69%) was the most applied statistic technique. There is an increasing number of publications, especially from 2016, and the transversality of UHI studies corroborates the relevance of this topic.

MONITORING THERMAL POLLUTION SOURCES IN VORONEZH (RUSSIA) USING REMOTE SENSING DATA

2021 ◽  
pp. 54-65
Author(s):  
Дмитрий Владимирович Сарычев ◽  
Ирина Владимировна Попова ◽  
Семен Александрович Куролап
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Heat Islands ◽  
Land Surface Temperatures ◽  
Treatment Facilities ◽  
Urban Heat ◽  
Industrial Zones

Рассмотрены вопросы мониторинга теплового загрязнения окружающей среды в городах. Представлена методика отбора спектрозональных спутниковых снимков, их обработки и интерпретации полученных результатов. Для оценки городского острова тепла были использованы снимки с космического аппарата Landsat 8 TIRS. На их основе построены карты пространственной структуры острова тепла города Воронежа за летний и зимний периоды. Определены тепловые аномалии и выявлено 11 основных техногенных источников теплового загрязнения в г. Воронеже, установлена их принадлежность к промышленным зонам предприятий, а также к очистным гидротехническим сооружениям. Поверхностные температуры данных источников в среднем были выше фоновых температур приблизительно на 6° зимой и на 15,5° С летом. Синхронно со спутниковой съемкой были проведены наземные контрольные тепловизионные измерения температур основных подстилающих поверхностей в г. Воронеже. Полученные данные показали высокую сходимость космических и наземных измерений, на основании чего сделан вывод о надежности используемых данных дистанционного зондирования Земли в мониторинговых наблюдениях теплового загрязнения городской среды. Результаты работ могут найти применение в городском планировании и медицинской экологии. The study deals with the remote sensing and monitoring of urban heat islands. We present a methodology of multispectral satellite imagery selection and processing. The study bases on the freely available Landsat 8 TIRS data. We used multitemporal thermal band combinations to make maps of the urban heat island of Voronezh (Russia) during summer and winter periods. That let us identify 11 artificial sources of heat in Voronezh. All of them turned out to be allocated within industrial zones of plants and water treatment facilities. Land surface temperatures (LST) of these sources were approximately 6° and 15.5° C above the background temperatures in winter and summer, respectively. To prove the remotely sensed temperatures we conducted ground control measurements of LST of different surface types at the satellite revisit moments. Our results showed a significant correlation between the satellite and ground-based measurements, so the maps we produced in this study should be robust. They are of use in urban planning and medical ecology studies.

scholarly journals Urban heat island: Aerodynamics or imperviousness?

2019 ◽  
Vol 5 (4) ◽  
pp. eaau4299 ◽  
Author(s):  
Dan Li ◽  
Weilin Liao ◽  
Angela J. Rigden ◽  
Xiaoping Liu ◽  
Dagang Wang ◽  
...  
Keyword(s):  
Green Infrastructure ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Lower Atmosphere ◽  
Geographic Variations ◽  
Heat Islands ◽  
Urban Heat ◽  
The Difference ◽  
Urban And Rural Areas

More than half of the world’s population now live in cities, which are known to be heat islands. While daytime urban heat islands (UHIs) are traditionally thought to be the consequence of less evaporative cooling in cities, recent work sparks new debate, showing that geographic variations of daytime UHI intensity were largely explained by variations in the efficiency with which urban and rural areas convect heat from the land surface to the lower atmosphere. Here, we reconcile this debate by demonstrating that the difference between the recent finding and the traditional paradigm can be explained by the difference in the attribution methods. Using a new attribution method, we find that spatial variations of daytime UHI intensity are more controlled by variations in the capacity of urban and rural areas to evaporate water, suggesting that strategies enhancing the evaporation capability such as green infrastructure are effective ways to mitigate urban heat.

scholarly journals Transformation of Urban Surfaces and Heat Islands in Nanjing during 1984–2018

2020 ◽  
Vol 12 (16) ◽  
pp. 6521
Author(s):  
Yanxia Li ◽  
Xinkai Zhang ◽  
Sijie Zhu ◽  
Xiaoyu Wang ◽  
Yongdong Lu ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Heat Islands ◽  
Island Effect ◽  
Urban Heat ◽  
The Many

One of the many consequences of urbanization is the expansion of cities into rural areas, which leads to the transformation of lands from natural surfaces to developed surfaces. It is widely considered an established fact that urbanization generally increases the heat island effect. The objective of this study is to understand the pattern of urban surface transformation in the city of Nanjing since 1980 and to find, if any, the correlation between such transformation and the urban heat island effect. The supervised classification technique was used to analyze the remote sensing data obtained from Landsat to identify the different kinds of underlying surfaces. Land surface temperatures were calculated using a subset of Landsat data. The correlation between the transformation of underlying surfaces and the heat island effect was established through analytical and statistical approaches. The results clearly show that the proportion of developed surfaces has been steadily rising in Nanjing in the past 30 years and that the urban heat island effect is positively correlated with the expansion of hard pavement and the deterioration of green surfaces and water bodies considering the general trend.

Assessment of Urban Heat Islands in Brazil based on MODIS remote sensing data

Urban Climate ◽  
2021 ◽  
Vol 35 ◽  
pp. 100726
Author(s):  
Felipe Ferreira Monteiro ◽  
Weber Andrade Gonçalves ◽  
Lara de Melo Barbosa Andrade ◽  
Lourdes Milagros Mendoza Villavicencio ◽  
Cássia Monalisa dos Santos Silva
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Sensing Data ◽  
Urban Heat

scholarly journals TEMPORAL AND SPATIAL ANALYSIS OF URBAN HEAT ISLAND USING LANDSAT SATELLITE DATA: TWO INDIAN CASE STUDIES

2018 ◽  
Vol IV-5 ◽  
pp. 71-78
Author(s):  
K. Dutta ◽  
D. Basu ◽  
S. Agrawal
Keyword(s):  
Land Cover ◽  
Rural Areas ◽  
Land Surface ◽  
Thermal Environment ◽  
Smart Cities ◽  
Vegetation Indices ◽  
Urban Heat Islands ◽  
Spatiotemporal Pattern ◽  
Heat Islands ◽  
Urban Heat

<p><strong>Abstract.</strong> Urban environment is examined through time series Landsat TM (Thematic Mapper) and OLI/TIRS (Operational Land Imager &amp;amp; Thermal Infrared Sensor) sensor images. A continuous surface of Land Surface Temperature (LST) can be extracted from Landsat thermal bands. Similarly different band combinations and ratios will give spatial pattern of land cover categories. Among these, building and vegetation indices are used to characterize the spatiotemporal pattern of elevated temperature zones in cities. This excess heat concentration creates thermal hotspots which are known as Urban Heat Islands (UHI). Parameters of land cover are then related to LST to detect the influence of urbanization on intensity and extent of heat islands, by pixel based quantitative analysis. This paper focuses on two megacities of India and their surrounding districts for identifying the critical UHI areas. The purpose of this paper is to create a database for reconstruction in old cities and planning of new smart cities. Results suggest that urban sprawl and substitution of rural areas with impervious surface plays significant role in microclimate, causing formation of new thermal hotspots. The analysis of urban thermal environment and its dynamics is to provide a scientific basis for future strategy building.</p>

scholarly journals Surface Urban Heat Islands Dynamics in Response to LULC and Vegetation across South Asia (2000–2019)

2021 ◽  
Vol 13 (16) ◽  
pp. 3177
Author(s):  
Talha Hassan ◽  
Jiahua Zhang ◽  
Foyez Ahmed Prodhan ◽  
Til Prasad Pangali Sharma ◽  
Barjeece Bashir
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Thermal Environment ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Urban Heat

Urbanization is an increasing phenomenon around the world, causing many adverse effects in urban areas. Urban heat island is are of the most well-known phenomena. In the present study, surface urban heat islands (SUHI) were studied for seven megacities of the South Asian countries from 2000–2019. The urban thermal environment and relationship between land surface temperature (LST), land use landcover (LULC) and vegetation were examined. The connection was explored with remote-sensing indices such as urban thermal field variance (UTFVI), surface urban heat island intensity (SUHII) and normal difference vegetation index (NDVI). LULC maps are classified using a CART machine learning classifier, and an accuracy table was generated. The LULC change matrix shows that the vegetated areas of all the cities decreased with an increase in the urban areas during the 20 years. The average LST in the rural areas is increasing compared to the urban core, and the difference is in the range of 1–2 (°C). The SUHII linear trend is increasing in Delhi, Karachi, Kathmandu, and Thimphu, while decreasing in Colombo, Dhaka, and Kabul from 2000–2019. UTFVI has shown the poor ecological conditions in all urban buffers due to high LST and urban infrastructures. In addition, a strong negative correlation between LST and NDVI can be seen in a range of −0.1 to −0.6.

Study on the Application and Comparative Analysis of Land Surface Temperature Retrieval Method Based on Multi-Sensor Remote Sensing Data

2014 ◽  
Vol 1010-1012 ◽  
pp. 1276-1279 ◽  
Author(s):  
Yin Tai Na
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Urban Heat ◽  
Split Window Algorithm ◽  
Temperature Retrieval

The three commonly used remote sensing land surface temperature retrieval methods are described, namely single-window algorithm, split window algorithm and multi-channel algorithm, which have their advantages and disadvantages. The land surface temperature (LST) of study area was retrieved with multi-source remote sensing data. LST of study area was retrieved with the split window algorithm on January 10, 2003 and November 19, 2003 which is comparatively analyzed with the LST result of ETM+data with the single-window algorithm and the LST result of ASTER data with multi channel algorithm in the same period. The results show that land surface temperature of different land features are significantly different, where the surface temperature of urban land is the highest, and that of rivers and lakes is the lowest, followed by woodland. It is concluded that the expansion of urban green space and protection of urban water can prevent or diminish the urban heat island.

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