scholarly journals Quantifying the effect of waterways and green areas on the surface temperature

2017 ◽  
Vol 39 (1) ◽  
pp. 89 ◽  
Author(s):  
Elis Dener Lima Alves

The cooling effects of urban parks and green areas, which form the “Park Cool Island” (PCI) can help decrease the surface temperature and mitigate the effects of urban heat islands (UHI). Therefore, the objective of this research was to know the temporal variability of PCI intensity, as well as analyze the factors that determines it and propose an equation to predict the PCI intensity in Iporá, Goiás State, Brazil. To this purpose, the PCI intensity values were obtained using the Landsat-8 satellite (band 10), and then correlated with the NDVI and the LAI, in which proposes equations through multiple linear regression to estimate the PCI intensity. The results indicated that: 1) the greater the distance of the natural area, greater the surface temperature; 2) there is a great seasonality in PCI, in which the intensity of PCI is much higher in the spring (or close to it); 3) the relationship between NDVI and LAI variables, showed good coefficients of determination; 4) the equations for the buffer of 200 and 500 m, had low RMSE with high coefficients of determination (r2 = 0.924 and r2 = 0.957 respectively). 

2014 ◽  
Vol 962-965 ◽  
pp. 2005-2017
Author(s):  
Wen Qi Lin ◽  
Xiang Qi Chang ◽  
Na Yan ◽  
Ting Yu

Cooling effects of green areas are an effective way to mitigate the urban higher temperature caused by urban heat islands. The cooling extent goes beyond a green area’s boundary and extends into its surrounding area. However, measurement of the exact cooling extent and mechanism of such effects had remained unclear. Using Landsat Enhanced Thematic Mapper Plus (ETM+) images of Beijing, we have determined the lower temperature of green cooled areas by land surface temperature, identified green areas’ cooling extents, and evaluated the relation of cooling extents to green areas’ features. Results show that the total size of extended cooled areas is larger than that of total green areas, and the cooling extents and magnitudes are statistically related to the biomass, size and shape of green areas. This study has demonstrated the calculation of cooling extents, and provided an approach to the assessment of cooling effects.


2018 ◽  
Vol 10 (12) ◽  
pp. 1965 ◽  
Author(s):  
Nguyen Thanh Hoan ◽  
Yuei-An Liou ◽  
Kim-Anh Nguyen ◽  
Ram Sharma ◽  
Duy-Phien Tran ◽  
...  

Hanoi City of Vietnam changes quickly, especially after its state implemented its Master Plan 2030 for the city’s sustainable development in 2011. Then, a number of environmental issues are brought up in response to the master plan’s implementation. Among the issues, the Urban Heat Island (UHI) effect that tends to cause negative impacts on people’s heath becomes one major problem for exploitation to seek for mitigation solutions. In this paper, we investigate the land surface thermal signatures among different land-use types in Hanoi. The surface UHI (SUHI) that characterizes the consequences of the UHI effect is also studied and quantified. Note that our SUHI is defined as the magnitude of temperature differentials between any two land-use types (a more general way than that typically proposed in the literature), including urban and suburban. Relationships between main land-use types in terms of composition, percentage coverage, surface temperature, and SUHI in inner Hanoi in the recent two years 2016 and 2017, were proposed and examined. High correlations were found between the percentage coverage of the land-use types and the land surface temperature (LST). Then, a regression model for estimating the intensity of SUHI from the Landsat 8 imagery was derived, through analyzing the correlation between land-use composition and LST for the year 2017. The model was validated successfully for the prediction of the SUHI for another hot day in 2016. For example, the transformation of a chosen area of 161 ha (1.61 km2) from vegetation to built-up between two years, 2016 and 2017, can result in enhanced thermal contrast by 3.3 °C. The function of the vegetation to lower the LST in a hot environment is evident. The results of this study suggest that the newly developed model provides an opportunity for urban planners and designers to develop measures for adjusting the LST, and for mitigating the consequent effects of UHIs by managing the land use composition and percentage coverage of the individual land-use type.


2021 ◽  
Vol 13 (11) ◽  
pp. 2111
Author(s):  
Anna Hellings ◽  
Andreas Rienow

Unsustainable development paths have reached critical levels in Europe. In recent years, in cities, urbanization has been contributing to the intensification of urban heat islands. To analyze the development of surface urban heat islands (SUHI) in Europe in the last few years, the present study combines the land surface temperature (LST) from MODIS with the urban classes of the CORINE land cover data within 617 functional urban areas (FUAs). Urban and industrial uses have significantly higher LST than green urban areas across all years (about 4 to 6 °C), as do agricultural areas within cities. Besides land cover, location also influences LST differences. While, e.g., Bolzano (Italy) shows particularly large LST differences (>6 °C) between the core and the commuting zone, this effect is hardly visible in Porto (Portugal) and Madrid (Spain) (<2.5 °C). Cities of moderate climates show increasing differences between a city and its commuting zones with rising LST (r = 0.68), i.e., less cooling effects at night.


Gaia Scientia ◽  
2016 ◽  
Vol 10 (4) ◽  
pp. 209-222
Author(s):  
Kaique Brito Silva ◽  
Neylor Alves Calasans Rego ◽  
José Wildes Barbosa Santos ◽  
Pollyanna Alves Costa

High temperature in cities appears as one more added difficulty resultant from the environmental problems. Nowadays scientists from all over the world have been addressing efforts in the sense of understanding the aspects that contribute to the increase of the urban temperature and its effects. In this way, the objective of this work was to identify heat islands in the urban area of the municipal district of Itabuna-Bahia. The used methodological procedure for identifying the heat islands was through the use of the data from the thermal sensor thermal of the satellites Landsat TM 5 and 7, being made the the necessary atmospheric corrections and conversions, allowing the surface temperature being displayed in levels of ash tones. The results showed temperature variations in the urban perimeter with identification of eight heat islands, whose places were characterized by the largest concentration of paved area and vegetation absence. It was also identified fifteen potential areas, for the implantation of green areas looking for the improvement of the temperature conditions in the identified hot points. These results can subsidize the urban planning, as support in the construction of strategies that would minimize the thermal discomfort.


Author(s):  
Boubaker Khallef ◽  
Yamina Biskri ◽  
Nabil Mouchara ◽  
Khaled Brahamia

This study aims to analyze the urban heat islands of the city of Guelma using Landsat 8 data and the geographic information system. The application of the single Chanel algorithm has been applied to extract surface temperature (LST) from Landsat 8 data. The result obtained shows that the surface temperature of August 11, 2019 in the city of Guelma varied from 36 to 47 degrees. However, the correlation between the LST, the NDVI and the NDBI allowed characterizing the effects of the green zones and the water resources thus the grounds built on the urban heat islands. The ecological assessment was performed using an urban thermal field variance index (UTFVI). The result obtained from this ecological assessment shows that 4 km2 of the surface of the city of Guelma represents a much worse ecological quality. It is therefore urgent for this city to strengthen and expand the strategies for reducing the effects of urban heat islands for preserve the quality of urban life of the inhabitants.


2019 ◽  
Vol 41 (3) ◽  
pp. 201-215 ◽  
Author(s):  
Nguyen Thanh Hoan ◽  
Nguyen Van Dung ◽  
Ho Le Thu ◽  
Hoa Thuy Quynh

It is of utmost importance to understand and monitor the impact of urban heat islands on ecosystems and overall human health in the context of climate change and global warming. This research was conducted in a tropical city, Hanoi, with a major objective of assessing the quantitative relationships between the composition of the main land-cover types and surface urban heat island phenomenon. In this research, we analyzed the correlation between land-cover composition, percentage coverage of the land cover types, and land surface temperature for different moving window sizes or urban land management units. Landsat 8 OLI (Operational Land Imager) satellite data was utilized for preparing land-cover composition datasets in inner Hanoi by employing the unsupervised image clustering method. High-resolution (30m) land surface temperature maps were generated for different days of the years 2016 and 2017 using Landsat 8 TIRS (Thermal Infrared Sensor) images. High correlations were observed between percentage coverage of the land-cover types and land surface temperature considering different window sizes. A new model for estimating the intensity of surface urban heat islands from Landsat 8 imagery is developed, through recursively analyzing the correlation between land-cover composition and land surface temperature at different moving window sizes. This land-cover composition-driven model could predict land surface temperature efficiently not only in the case of different window sizes but also on different days. The newly developed model in this research provides a wonderful opportunity for urban planners and designers to take measures for adjusting land surface temperature and the associated effects of surface urban heat islands by managing the land cover composition and percentage coverage of the individual land-cover types.


Author(s):  
Дмитрий Владимирович Сарычев ◽  
Ирина Владимировна Попова ◽  
Семен Александрович Куролап

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.


Author(s):  
Chaobin Yang ◽  
Ranghu Wang ◽  
Shuwen Zhang ◽  
Caoxiang Ji ◽  
Xie Fu

Temporal variation of urban heat island (UHI) intensity is one of the most important themes in UHI studies. However, fine-scale temporal variability of UHI with explicit spatial information is sparse in the literature. Based on the hourly air temperature from 195 meteorological stations during August 2015 in Changchun, China, hourly spatiotemporal patterns of UHI were mapped to explore the temporal variability and the effects of land use on the thermal environment using time series analysis, air temperature profiling, and spatial analysis. The results showed that: (1) high air temperature does not indicate strong UHI intensity. The nighttime UHI intensity (1.51 °C) was much stronger than that in the daytime (0.49 °C). (2) The urban area was the hottest during most of the day except the period from late morning to around 13:00 when there was about a 40% possibility for an “inverse UHI intensity” to appear. Paddy land was the coolest in the daytime, while woodland had the lowest temperature during the nighttime. (3) The rural area had higher warming and cooling rates than the urban area after sunrise and sunset. It appeared that 23 °C was the threshold at which the thermal characteristics of different land use types changed significantly.


2019 ◽  
Vol 11 (12) ◽  
pp. 1449 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet

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.


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