scholarly journals Determination of The Intensity and Georeferencing of Urban Heat Islands in Temuco, Chile

2021 ◽  
Author(s):  
Aner Martinez-Soto ◽  
Michelle Vera-Fonseca ◽  
Pablo Valenzuela-Toledo ◽  
Aliwen Melillan-Raguileo
Keyword(s):  
Monitoring Network ◽  
Urban Heat Islands ◽  
Temperature Record ◽  
Heat Islands ◽  
National Monitoring ◽  
Combined Use ◽  
Urban Heat ◽  
Individual Use ◽  
The City

Abstract Various methodologies to estimate the intensity of urban heat islands (UHI) have been proposed. However, there is no consensus on their combined or individual use. This study presents and analyzes the validation of the combined use of methodologies to capture data from UHI’a (mobile transects and fixed stations) and the location of the UHI phenomenon by considering the city of Temuco, Chile as a case study. The database used for the fixed station methodology consists of twenty-three stations belonging to the National Monitoring Network of Chile distributed throughout the city. For the mobile transect methodology the database was generated with three cars that crossed the city simultaneously taking one temperature record per minute. The results show that the two methodologies yield similar results, so it is possible to obtain the intensity of the IHU phenomenon using at least one of them. The results also showed that Temuco has a maximum intensity of the UHI phenomenon of 13°C, with this value being one of the highest recorded in UHI studies in the world.

scholarly journals Urban heat island in Bloemfontein during winter

2013 ◽  
Vol 32 (1) ◽  
Author(s):  
Pieter Snyman ◽  
A. Stephen Steyn
Keyword(s):  
Maximum Intensity ◽  
Urban Heat Islands ◽  
Urban Air ◽  
Heat Island ◽  
Heat Islands ◽  
Air Temperatures ◽  
Local Topography ◽  
Urban Heat ◽  
The Difference ◽  
The City

Urban heat islands (UHIs) are characterised by warmer urban air temperatures compared to rural air temperatures, and the intensity is equal to the difference between the two. Air temperatures are measured at various sites across the city of Bloemfontein and then analysed to determine the UHI characteristics. The UHI is found to have a horseshoe shape and reaches a maximum intensity of 8.2 °C at 22:00. The UHI is largely affected by the local topography.

scholarly journals Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1449 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Image Resolution ◽  
Urban Heat Islands ◽  
Land Uses ◽  
Regression Kriging ◽  
Heat Islands ◽  
Urban Heat ◽  
Land Covers ◽  
The City

Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

scholarly journals SATELLITE-DRIVEN ASSESSMENT OF SURFACE URBAN HEAT ISLANDS IN THE CITY OF ZAGREB, CROATIA

2020 ◽  
Vol V-3-2020 ◽  
pp. 757-764
Author(s):  
A. Krtalić ◽  
A. Kuveždić Divjak ◽  
K. Čmrlec
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Principal Component ◽  
Urban Heat Islands ◽  
City Centre ◽  
Landsat 8 ◽  
Heat Islands ◽  
Critical Areas ◽  
Urban Heat ◽  
The City

Abstract. This study aims to assess surface urban heat islands (SUHIs) pattern over the city of Zagreb, Croatia, based on satellite (optical and thermal) remote sensing data. The spatio-temporal identification of SUHIs is analysed using the 12 sets of Landsat 8 imagery acquired during 2017 (in each month of the year). Vegetation cover within the city boundaries is extracted by using Principal Component Analysis (PCA) data fusion method on calculated three vegetation indices (VI): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Ratio Vegetation Index (RVI) for each set of bands. The first principal component was used to compute the land surface temperature (LST) and deductive Environmental Criticality Index (ECI). As expected, the relationship between LST and all VI scores shows a negative correlation and is most negative with RVI. The environmentally critical areas and the patterns of seasonal variations of the SUHIs in the city of Zagreb were identified based on the LST, ECI and vegetation cover. The city centre, an industrial area in the eastern part and an area with shopping centers and commercial buildings in the western part of the city were identified as the most critical areas.

scholarly journals The Influence of Vegetation on UHIs, MUHIs, and Microclimate of Selected Southern Cities

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 509A-509
Author(s):  
Derald A. Harp ◽  
Edward L. McWilliams
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Building Materials ◽  
Urban Heat Islands ◽  
Shopping Malls ◽  
Heat Islands ◽  
Suburban Areas ◽  
Winter Temperatures ◽  
Urban Heat ◽  
The City

Urban areas have average annual temperatures 2–3°C warmer than surrounding rural areas, with daily differences of 5–6°C common. A suggested reason for this temperature difference is the extensive use of concrete, asphalt, and other building materials in the urban environment. Vegetation can moderate these temperatures by intercepting incoming radiation. The influence of vegetation patterns on the magnitude of urban and micro-urban “heat islands” (UHI and MUHI, respectively) is compared for several cities including Houston, Austin, College Station, and Ft. Worth, Texas; Huntsville, Ala.; and Gainesville, Fla. Temperatures for all cities studied were greatest in the built-up areas and dropped off in suburban areas and adjacent rural areas. In Houston, surrounding rice fields were 3–5°C cooler than urban areas. Heavily built-up areas of Austin were 2–4°C warmer than parks and fields outside of the city. In all of the cities, large parks were typically 2–3°C cooler than adjacent built-up areas. Large shopping malls varied in nocturnal winter and summer temperature, with winter temperatures near door openings 2–3°C warmer, and summer daytime temperatures as much as 17°C cooler beneath trees. This effect seemed to persist at the microclimatic scale. Areas beneath evergreen trees and shrubs were warmer in the winter than surrounding grass covered areas. Video thermography indicated that the lower surfaces of limbs in deciduous trees were warmer than the upper surfaces. Overall, vegetation played a significant role, both at the local and microscale, in temperature moderation.

scholarly journals Features of the formation of urban heat islands effects in tropical climates and their impact on the ecology of the city

2019 ◽  
Vol 91 ◽  
pp. 05005 ◽  
Author(s):  
Minh Tuan Le ◽  
Nguyen Anh Quan Tran
Keyword(s):  
Urban Areas ◽  
Building Materials ◽  
Urban Landscape ◽  
Urban Climate ◽  
Ecological Systems ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Urban Heat ◽  
Tropical Climates ◽  
The City

The cumulative heating in some urban areas due to the urban growth and its types of industry, energy and transport, is the effect of urban heat island (UHI). It is recognized as one of the characteristics of the urban climate. The temperature increase caused by the effect (UHI) affects the energy flow in urban ecological systems, creates an unusual urban climate. By studying the effects of climate factors, local building materials to optimize energy efficiency, urban landscape, UHI phenomenon could be significantly moderated.

Building a new high-density air temperature measurement network in two Swiss cities

2021 ◽  
Author(s):  
Julien G. Anet ◽  
Sebastian Schlögl ◽  
Curdin Spirig ◽  
Martin P. Frey ◽  
Manuel Renold ◽  
...  
Keyword(s):  
Temperature Measurement ◽  
Air Temperature ◽  
Heat Waves ◽  
Low Cost ◽  
High Density ◽  
Urban Heat Islands ◽  
Temperature Measurements ◽  
Heat Islands ◽  
Urban Heat ◽  
The City

<p>With progressive climate change, weather extremes are very likely to become more frequent. While rural regions may suffer from more intense and longer drought periods, urban spaces are going to be particularly affected by severe heat waves. This urban temperature anomaly, also known as “urban heat island” (UHI), can be traced back to different factors, the most prominent being soil sealing, lower albedo and lack of effective ventilation.</p><p>City planners have started developing mitigation strategies to reduce future forecasted heat stress in urban regions. While some heat reduction strategies are currently intensely scrutinized and applied within pilot projects, the efficiency of latter mitigation actions can be overseen due to the low density of reference in situ air temperature measurements in urban environments. The same problem applies when trying to benchmark modeling studies of UHI as the amount of benchmarking data may be insufficient.</p><p>To overcome this lack of data, over the last two years, a dense air temperature measurement network has been installed in the Swiss cities of Basel and Zurich, counting more than 450 sensors. The low-cost air temperature sensors are installed on street lamps and traffic signs in different local climate zones of the city with an emphasis on street canyons, where air temperatures are expected to be the largest and most of the city’s population lives and works. These low-cost sensors add valuable meteorological information in cities and complement the WMO reference stations.</p><p>Air temperature measurements from the low-cost sensor network were controlled for accuracy, reliability and robustness and homogenized in order to minimize radiation errors, although 40% of the stations were equipped with self-built radiation shields, allowing an efficient passive ventilation of the installed sensors.</p><p>We demonstrate the strength of our network by presenting first results of two exemplary heat waves that occurred in July 2019 and August 2020 and show that a) the radiation-error corrected datasets correlate well with different high-quality reference WMO stations, and b) the existence of urban heat islands in Zurich and Basel can be well confirmed, showing significant air temperature differences of several degrees between rural and urban areas.</p><p>The results demonstrate the advantages of a high-density low-cost air temperature network as a benchmark for future urban heat islands modelling studies.</p>

scholarly journals Real-Time Thermal Mapping for Heat & Cool Archipelagos of Bengaluru, India

2017 ◽  
Vol 13 (2) ◽  
pp. 106-111
Author(s):  
Rajesh Gopinath ◽  
Aditya Banerjee ◽  
S. Sachin ◽  
Prakhar Tiwari ◽  
Sunny Wilson
Keyword(s):  
Real Time ◽  
Decision Makers ◽  
Urban Heat Islands ◽  
Subsequent Increase ◽  
Thermal Discomfort ◽  
Heat Islands ◽  
Human Thermal Comfort ◽  
The Past ◽  
Urban Heat ◽  
The City

Abstract Blessed with a salubrious climate, the city of Bengaluru over the past few decades has constantly witnessed thermal discomfort owing to several Urban Heat islands that have mushroomed within the city. The subsequent increase in builtup area, consequent loss of productive agricultural lands/green zones, encroachment of surface water bodies coupled with the ill-preparedness of decision makers to handle the demand for land have invariably crumbled the natural micro-climate of the city. In this present research, an attempt has been made to detect the distribution of Urban Heat Islands in Bengaluru City by conducting real-time survey at 100 observatories marked across the entire urban & rural locations; with thermohygrometers as per the W.M.O. guidelines. The study confirmed the violation of the Human Thermal Comfort Range in 9, 83, 98, 99, 98 and 80 observatories for the monitoring at 6 AM, 9 AM, 12 PM, 3 PM, 6 PM and 9 PM respectively.

scholarly journals IASI observations at the city scale

2020 ◽  
Author(s):  
Sarah Safieddine ◽  
Maya George ◽  
Cathy Clerbaux ◽  
Ana Paracho ◽  
Anne Boynard ◽  
...  
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Spatial Scales ◽  
Urban Heat Islands ◽  
Atmospheric Composition ◽  
Heat Islands ◽  
Large Cities ◽  
Urban Heat ◽  
Good Tracer ◽  
The City

<p>IASI is a versatile mission, allowing the measurement of both meteorological parameters such as temperature and atmospheric composition for infrared absorbing species. With its long observation record and frequent overpasses, IASI is able to follow changes at different spatial scales. We studied IASI’s capability to track the anthropogenic signature associated with large cities, both in terms of temperature fingerprint (urban heat islands) and carbon monoxide (CO) content, a good tracer of human activity (transport, heating, and industrial activities). For this study we averaged the IASI data available since the launch of the first IASI, in order to increase the signal to noise, and allow discriminating the city from its surroundings. For skin temperatures we show that some cities experience much warmer temperatures than nearby rural areas, with day and night differences, whereas other urban areas appear as cold urban islands when surrounded by deserts Examples will be shown and compare with MODIS observations. For CO emitted by human activities, we identified some cities that stand out from their background, and were able to compare their CO associated signatures with measurements provided by other available spaceborne instruments such as Mopitt and TROPOMI.</p>

scholarly journals Study of the Parameters of Urban Heat Islands on the Irkutsk Region Territory According to Remote Sensing Data

2020 ◽  
Vol 34 ◽  
pp. 131-140
Author(s):  
E. N. Sutyrina ◽  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Dimensional Structure ◽  
Heat Islands ◽  
Irkutsk Region ◽  
Urban Heat ◽  
The Difference ◽  
The City

The investigation is aimed to determine the boundaries and intensity of urban heat islands in the Irkutsk region and assess the change in these parameters over a long-term period. The formation of an urban heat island is an example of anthropogenic influence on the urban climate. Land surface temperature and its spatial and temporal variations can be used to study urban heat islands, since the difference between the land surface temperature within the city and its surroundings is the result of the transformation of the underlying surface, heat capacity and three-dimensional structure of urban buildings in the process of urbanization. In order to study the phenomenon of urban heat islands of cities of the Irkutsk region, the land surface temperature data reconstructed from AVHRR-based thermal infrared imagery for 1998-2019 was used. As a result of the study, multi-temporal maps showing the urban heat islands of the agglomeration of Irkutsk-Angarsk-Shelekhov and the city of Bratsk were obtained. The investigated heat islands are characterized by a significant diurnal dynamic, so the difference in temperature values between the city and the suburbs in summer daytime reached 8-10 °C, in the evening and at night in summer this parameter decreases to 3-5 °C. The dimensions of the urban heat islands of the cities under investigation in the daytime exceed the dimensions of these heat anomalies in the evening and at night. Interannual variability in the intensity of urban heat islands did not show statistically significant trends from 1998 to 2019, the areas of urban heat islands increased significantly over the study period. The observed increase in area was probably associated with the development of the cities under study, with the transformation of landscapes and a decrease in the density of vegetation in the suburbs. In order to assess the contribution of the lack of vegetation to the formation of the urban heat islands in summer daytime, the values of the land surface temperature were compared with the values of the vegetation index NDVI. An analysis of the relationships between these parameters found that daytime land surface temperature was in close inverse relationship with the NDVI value, while this relationship was less pronounced at night and in the evening.

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