scholarly journals Mapping and assessment of urban heat island effects in the city of Sofia, Bulgaria through integrated application of remote sensing, unmanned aerial systems (UAS) and GIS

2020 ◽  
Author(s):  
Stelian Dimitrov ◽  
Anton Popov ◽  
Martin Iliev
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Unmanned Aerial Systems ◽  
Heat Island ◽  
Urban Heat ◽  
Aerial Systems ◽  
The City

Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing

2012 ◽  
Vol 34 (9-10) ◽  
pp. 3177-3192 ◽  
Author(s):  
José A. Sobrino ◽  
Rosa Oltra-Carrió ◽  
Guillem Sòria ◽  
Juan Carlos Jiménez-Muñoz ◽  
Belén Franch ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Thermal Remote Sensing ◽  
Island Effect ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The City

scholarly journals Data and techniques for studying the urban heat island effect in Johannesburg

2015 ◽  
Vol XL-7/W3 ◽  
pp. 203-206 ◽  
Author(s):  
C. H. Hardy ◽  
A. L. Nel
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Urban Areas ◽  
Remote Sensing Data ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Sensing Data ◽  
Island Effect ◽  
Urban Heat ◽  
The City

The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability of the levels of vegetation across Johannesburg’s residential regions has an influence on the urban heat island effect within the city. Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis of influencing factors.

scholarly journals Spatio-Temporal Analysis of UHI using Geo-Spatial Techniques: A case study of Ahmedabad

2014 ◽  
Vol XL-8 ◽  
pp. 997-1002 ◽  
Author(s):  
A. Vyas ◽  
B. Shastri ◽  
Y. Joshi
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Urban Heat Island ◽  
Urban Area ◽  
Rural Areas ◽  
Remote Sensing Data ◽  
Observation Data ◽  
Heat Island ◽  
Urban Heat ◽  
The City

As per the current estimates, nearly half of the world’s population lives in the cities, by 2030 it is calculated to increase to 70%. This calls for a need of more sustainable structure in the urban areas as to support increase in the urban population. Urban Heat Island is one such conspicuous phenomenon which has its significance at local regional and also at the global levels. It is a microscale temperature variation between urban and rural areas, in which urban area are warmer compare to surrounding rural area. The temperature difference between the urban and the rural areas are usually modest, averaging less than 1°C, but occasionally rising to several degrees when urban, topographical and meteorological conditions are favorable for the UHI to develop. It is defined as the phenomena where in the occurrence of surface and atmospheric modifications due to the urbanization causes modification in the thermal climatic conditions which results into warmer areas as compared to the surrounding non urbanized areas, particularly in night. In that case urban built forms such as buildings, roofs, pavements etc. absorb more solar heat/radiation and remain warmer throughout the day time and slowly release energy during night time. The two major causes are rapid urbanization and anthropogenic heat generated due to transport and industrial activities. Urban Heat Island is a crucial subject for global environment. Urbanization has significant effects on local weather and climate. Among these effects one of the most popular is the urban heat island, for which the temperatures of the central urban locations are several degrees higher than those of nearby rural areas of similar elevation. Satellite data provides important inputs for estimating regional surface albedo and evapo-transpiration required in the studies related to surface energy balance. <br><br> The phenomenon of UHI affects environment and population in so many ways it can also be considered as an active element that cause vulnerabilities to human health, the marginal population affected largely as the natural environment is their only home or their main shelter. Furthermore elderly people also affected in greater amount as their weakening immunes system. Major effects of UHI on environment include: a) Air Quality, b) Energy consumption and c) Human health. <br><br> To study the causes and effect of UHI of any urban area, the first step is to demarcate the spatial distribution of UHI and its intensity over different time period of the day as well as difference in the temperature of urban area with the surrounding rural areas. Secondly, study of land use land cover change in the area also helps in identifying causes of heat accumulation for particular region. After marking up of intensity, analysis of different zones for understanding the relationship between UHI and urban morphological features can be done which further became suggestive towards planning of urban center that mitigates the effect of UHI. Mainly two approaches are there to demarcate UHI study as: <br><br> &ndash; Field data collection and observations <br> &ndash; Remote sensing data analysis <br><br> For a long period of time observations from interior of the city and outwards of it can analyze by a climatic methods, by observing many days as well as many times of a day continuously to analyze the daily variation law of the heat island effects. As the city is for its developmental approaches may cover an area of hundreds of square kilometers, the ground observation data is not able to provide enough detail about the urban heat island distribution characteristics. The most precise method is the Satellite Remote Sensing method. The UHI phenomenon can be analyzed by using the thermal infrared data obtained meteorological satellite sensing. The atmospheric attenuation can be corrected for the remote sensing data by use of meteorological soundings and ground observation data. Ideally the heat island effect over a city is not same for any other city. <br><br> Satellite images from AVHRR Advanced Very High Resolution Radiometer) or ENVISAT AATSR provides thermal infrared data and comparatively easy to acquire, process and analyze. In the case of Ahmedabad city, land cover changes over the time is to be studied by classifying the image and then temperature can be derived by using a quadratic regression model from Malaret at al. (1985). Band 6 produces the images that show the relative difference emitted thermal energy that correlate in part with the effects of solar heating on surface of varying composition and orientation. The surface temperatures are suitable to detect UHI at Urban canopy level. Nichol (1996) found that surface temperatures extracted are moreover similar to the actual ambient air temperatures recorded. <br><br> The paper has narrated analylitical framework on which the research has been carried out. The result derived on Land Surface Temperature variation causing Urban Heat Island, its relationship with the land use land cover. A time series data has been used. Authors are thankful to Ms. Darshana Rawal, Ms. Pallavi Knahdewal and Mr. Hardik Panchal.

Evaluation of Absolute Maximum Urban Heat Island Intensity Based on a Simplified Remote Sensing Approach

2021 ◽  
Author(s):  
Valentino Sangiorgio ◽  
Alessandra Capolupo ◽  
Eufemia Tarantino ◽  
Francesco Fiorito ◽  
Mattheos Santamouris
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Urban Heat Island Intensity ◽  
Absolute Maximum ◽  
Heat Island ◽  
Urban Heat

Evaluating the spatial distribution and the intensity of urban heat island using remote sensing, case study of Isfahan city in Iran

2019 ◽  
Vol 45 ◽  
pp. 686-692 ◽  
Author(s):  
Niloufar Shirani-bidabadi ◽  
Touraj Nasrabadi ◽  
Shahrzad Faryadi ◽  
Adnan Larijani ◽  
Majid Shadman Roodposhti
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Urban Heat Island ◽  
Heat Island ◽  
Urban Heat

scholarly journals Urban "Heat-Island Effect" and its Connection with Architectural and Climatic Features on the Example of Poltava

2018 ◽  
Vol 7 (3.2) ◽  
pp. 597
Author(s):  
Yuri Golik ◽  
Oksana Illiash ◽  
Nataliia Maksiuta
Keyword(s):  
Urban Heat Island ◽  
Traditional Method ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Island Effect ◽  
Temperature Regimes ◽  
Architectural Features ◽  
Urban Heat ◽  
The Given ◽  
The City

The concept of "heat-island effect", its structure and features of formation over the city are given. The climatic and other features of the city that influence the formation of this phenomenon are mentioned.  The data on functioning in the city of the municipal production enterprise of the heat economy is indicated. The traditional method for determining the formation of the urban "heat-island effect" is described. The data and comparative graphs on the temperature regimes of the city and region are presented. The possibility of influencing architectural features of the city on the formation of the "heat-island-effect" is determined. According to the obtained results, further integrated researches are proposed for obtaining reliable results of the given question. 

scholarly journals A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform Observations

2021 ◽  
Author(s):  
Shihan Chen ◽  
Yuanjian Yang ◽  
Fei Deng ◽  
Yanhao Zhang ◽  
Duanyang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Model Framework ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
The City

Abstract. Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high spatial resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a Random Forest (RF) model. Firstly, the observed environmental parameters [e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF)] around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 °C. Then, the spatial distribution of CUHII was evaluated at 30-m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the de-creasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.

Sign in / Sign up

Export Citation Format

Share Document