scholarly journals Identification of SUHI in Urban Areas by Remote Sensing Data and Mitigation Hypothesis through Solar Reflective Materials

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 70
Author(s):  
Sofia Costanzini ◽  
Francesca Despini ◽  
Leonardo Beltrami ◽  
Sara Fabbi ◽  
Alberto Muscio ◽  
...  
Keyword(s):  
Urban Areas ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Urban Environments ◽  
Landsat 8 ◽  
Local Climate ◽  
Po Valley ◽  
Infrared Spectral ◽  
Widespread Phenomenon ◽  
Urban Heat

The urban heat island (UHI) is an increasingly widespread phenomenon of concern to the wellbeing and the health of populations living in urban environments. The SUHI (Surface UHI) is directly related to UHI and influences its extension and intensity. Satellite images in the thermal infrared spectral region can be used to identify and study the SUHI. In this work, Landsat 8 TIR images were acquired to study the SUHI of a medium-sized municipality of the Po valley in the northern part of Italy. An additional Worldview 3 satellite image was used to classify the study area and retrieve the surface albedo of building roofs. Using the Local Climate Zone approach, existing roof materials were virtually replaced by solar reflective materials, and the mitigation potential of the SUHI and the UHI was quantified. This virtual scenario shows a decrease in the overheating of building roofs with respect to the ambient temperature of up to 33% compared to the current situation in the industrial areas. Focusing on UHI intensity, the air temperature decrease could be up to 0.5 °C.

scholarly journals IDENTIFICATION OF URBAN HEAT ISLAND SPREADING TO CONCENTRATION OF NO2, O3, AND PM10 POLLUTANT IN DKI JAKARTA

2019 ◽  
pp. 125-133
Author(s):  
Alfiyah Nur Fitriani ◽  
Kania Dewi ◽  
Laras Tursilowati
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Urban Areas ◽  
Rapid Development ◽  
Satellite Image ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Heat Island ◽  
Observation Area ◽  
Urban Heat

Urban Heat Island is usually caused by Land use Land-Cover Changes (LULCC), including in Jakarta-Indonesia. Rapid development in Jakarta causes green open space to decrease and increase surface temperature in urban areas. In addition, Urban Heat Island also affects the spread of pollutants due to increased turbulence. Therefore, this study aims to find the link between temperature rise in DKI Jakarta which is influenced by land cover changes to pollutant spread such as NO2, PM10, and O3. This research begins with data processing observation of average temperature of DKI Jakarta area with meteorology station Tangerang, Banten for spatial calculation from year 2011-2016. In addition, LANDSAT 8 satellite image data is processed for spatial land and temperature encapsulation with Remote Sensing software from 2013-2015. As a result, in 2013 and 2015 there is a reduction in the area of vegetation that turns into non-vegetation (residential and industrial areas) that affect the temperature of the DKI Jakarta region is increasing. After that, sought the linkage between Urban Heat Island and the spread of pollutant concentrations in DKI Jakarta in 2013 and 2015. As a result, the increase of Jakarta area temperature, especially in pollutant observation area at five points, influenced the distribution of pollutant NO2, O3, and PM10 pollutant concentration balance with the dominan area such as roadside, industry, settlement in the time and area study in DKI Jakarta.

scholarly journals Mapping summer SUHI and its impact on the environment using GIS and Remote Sensing techniques: A case study on Municipality of Prishtina (Kosovo)

2021 ◽  
Vol 12 (3) ◽  
pp. 113-129
Author(s):  
Albert Berila ◽  
◽  
Florim Isufi ◽  
Keyword(s):  
Remote Sensing ◽  
Rural Areas ◽  
Urban Areas ◽  
Satellite Image ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Remote Sensing Techniques

Urban areas, compared to peripheral and rural areas, have higher temperatures which are caused by a series of unplanned activities that are undertaken by humans. Such a thing leads to the emergence of the Surface Urban Heat Island (SUHI) phenomenon. In this paper, summer SUHI is determined through the calculation of LST for the Municipality of Prishtina using GIS and Remote Sensing techniques. To make this calculation, the Landsat 8 satellite image with 0% cloud cover was used. From the calculations made it turns out that the pixels with the highest value of LST are found in those parts where the urban area appears, where there are numerous constructions with impermeable materials, as well as in those areas where there are bare surfaces. Whereas, the pixels with lower values of LST appear in those parts where there are vegetation and water bodies, making these areas fresher. The SUHI phenomenon makes the lives of citizens difficult, therefore, such information is very important for the leaders and urban planners of the city of Prishtina, so that they take a series of steps towards minimizing such an effect in order to the life of the citizens to be as healthy as possible.

scholarly journals Combining Satellite Data and Spatial Analysis to Assess the UHI Amplitude and Structure within Urban Areas: The Case of Moroccan Cities

Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 67
Author(s):  
Laila El Ghazouani ◽  
Lahouari Bounoua ◽  
Joseph Nigro ◽  
Majid Mansour ◽  
Hassan Radoine ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Spatial Scales ◽  
European Space Agency ◽  
Landsat 8 ◽  
Local Climate ◽  
Coastal Cities ◽  
Space Agency ◽  
Urban Heat ◽  
The Impact

Landsat-8 surface temperature and the European Space Agency land cover are used to assess the impact of land cover on the Urban Heat Island (UHI) and Urban Heat Sink (UHS). We analyzed five Moroccan cities selected for their different local climate, size, and typology during summer at three different spatial scales. The results show multiple causes defining the different forms and amplitudes of the UHI, namely: the ambient climate, the proximity to the sea, the presence of landscaped areas, and the color of building roofs and walls. Contrary to what was expected, the vegetation was not systematically an island of coolness, either because of its typology or its irrigation status. In the coastal cities of Tangier and Casablanca, UHIs around 20 °C are observed on the seaside, whereas a UHS of up to 11 °C is observed between the city center and the southern periphery of Casablanca. A moderate amplitude UHI of 7 °C is formed in the mountainous city of Ifrane. For cities built in desert-like environments, well-defined UHSs between 9 °C and 12 °C are observed in Smara and Marrakech, respectively. At a finer scale, towns recorded lower temperatures than their immediate surroundings, which are attributed to evaporation from irrigated plants.

scholarly journals Atmospheric correction of multispectral satellite imagery

2020 ◽  
pp. 4-11
Author(s):  
Leonid Katkovsky
Keyword(s):  
Land Surface ◽  
Satellite Image ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Sensor Data ◽  
Physical Parameters ◽  
Landsat 8 ◽  
Optical Parameters ◽  
Outgoing Radiation ◽  
Correction Technique

Atmospheric correction is a necessary step in the processing of remote sensing data acquired in the visible and NIR spectral bands.The paper describes the developed atmospheric correction technique for multispectral satellite data with a small number of relatively broad spectral bands (not hyperspectral). The technique is based on the proposed analytical formulae that expressed the spectrum of outgoing radiation at the top of a cloudless atmosphere with rather high accuracy. The technique uses a model of the atmosphere and its optical and physical parameters that are significant from the point of view of radiation transfer, the atmosphere is considered homogeneous within a satellite image. To solve the system of equations containing the measured radiance of the outgoing radiation in the bands of the satellite sensor, the number of which is less than the number of unknowns of the model, it is proposed to use various additional relations, including regression relations between the optical parameters of the atmosphere. For a particular image pixel selected in a special way, unknown atmospheric parameters are found, which are then used to calculate the reflectance for all other pixels.Testing the proposed technique on OLI sensor data of Landsat 8 satellite showed higher accuracy in comparison with the FLAASH and QUAC methods implemented in the well-known ENVI image processing software. The technique is fast and there is using no additional information about the atmosphere or land surface except images under correction.

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 NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals STUDY OF TEMPERATURE PROFILE ON VARIOUS LAND USE AND LAND COVER FOR EMERGING HEAT ISLAND

2015 ◽  
Vol 9 (1) ◽  
pp. 32-37 ◽  
Author(s):  
Sainu Franco ◽  
Venkata Ravibabu Mandla ◽  
K. Ram Mohan Rao ◽  
Pramod Kumar M ◽  
Anand P.C.
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Ghg Emissions ◽  
Climatic Changes ◽  
Heat Island ◽  
Sharp Decline ◽  
Geospatial Technologies ◽  
Local Climate ◽  
Green House Gas ◽  
Urban Heat

Greater Hyderabad a twin city in earlier days, has grown into a tricity of Cyberabad - Hyderabad – Secunderabad. This concentrated development with impetus on industrialization has led to unprecedented urbanization and sprawl, resulting in heavy population growth and ultimately raising serious challenges such as traffic congestion, enhanced Green House Gas (GHG) emissions causing climatic changes apart from over-use of basic amenities and infrastructure. This study shows that urban areas have grown from a mere 172 sq km of MCH (Municipal Corporation of Hyderabad) in the 1970’s to a whopping 1905 sq km at present, currently known as the Greater Hyderabad Metropolitan Corporation. The phenomenon of Urban Heat Island (UHI) can be observed in several localities. The pattern of growth of Greater Hyderabad and its repercussions on the local climate are studied with the help of geospatial technologies. An increase of ~20C to 2.50C is observed over the last 2 decades. The Vegetation and water bodies also show a sharp decline.

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 THE EFFECT OF GREEN SPACE ON THE LAND SURFACE TEMPERATURE IN HUE CITY

2018 ◽  
Vol 55 (4C) ◽  
pp. 129
Author(s):  
Nguyen Bac Giang
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Green Space ◽  
Satellite Image ◽  
Urban Green Space ◽  
Landsat 8 ◽  
Urban Green ◽  
Study Results

This paper presents the analysis of the effect of urban green space types on land surface temperature in Hue city. Data are collected with temperature monitoring results from each green space type and the interpretation of surface temperature based on Landsat 8 satellite image data to determine temperatures at different times of the year. Results showed that there was a significant correlation between types of urban green space and the surface temperature. Types of green space with a large area and vegetation indexes have a greater effect on temperature than areas with a smaller green space do. Green space types including forest green space, dedicated green space and agriculture green space have the most effect on the surface temperature. The forest area has the greatest influence on the temperature with a temperature difference of more than 1.6 degrees Celsius at 9:00 in the daytime. Besides, the results extracted from satellite images also show that the area of urban green space going to be reduced makes a contribution to increase the surface temperature of urban areas. The study results have established foundation for planning the green spaces in climate change challenges in Hue City.

scholarly journals Analisis Heat Island pada Perkebunan Kelapa Sawit: Studi Kasus di Kabupaten Kayong Utara, Kalimantan Barat

2020 ◽  
Vol 8 (2) ◽  
pp. 106-115
Author(s):  
Nurul Ihsan Fawzi ◽  
Marindah Yulia Iswari
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Palm Oil ◽  
Secondary Forest ◽  
Remote Sensing Data ◽  
Primary Forest ◽  
Landsat 8 ◽  
Heat Island ◽  
Local Climate ◽  
Island Effect

Between 2000 – 2017, 3.06 million hectares of primary forest in Kalimantan have been converted into palm oil plantation. This change impacts local climate changes. This study aims is to analyze the heat island in palm oil plantation. The analytical method used surface temperature estimation through remote sensing and zonal statistics. The remote sensing data that are used is Landsat 8 images acquired on 15 July 2018 and 3 August 2019. From this research, we found that young palm oil plantations have an average IHI value of 2.1 ± 1.7oC in 2018 and 1.7 ± 1.4oC in 2019. The IHI value is close to the heat island in a built-up area. IHI for mature palm oil plantation (11-12 years) created a cool island with an intensity close to secondary forest. The decreasing value of IHI for 2018 and 2019 in palm oil plantations is due to the growth of palm oil trees, which decreases surface temperature. The implication of this research is to know heat island effect due to deforestation or land cover changes, especially change into palm oil plantations.

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