Modelling of the Annual Mean Urban Heat Island Pattern for Planning of Representative Urban Climate Station Network (original) (raw)
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Urban heat island research of Novi Sad (Serbia): A review
In the second part of the 20th century, urbanization accelerated and reached enormous magnitude, which results more and more people live in urbanized regions. Nowadays, about half of the human population is affected by the burdens of urban environments and furthermore the modified parameters of the urban atmosphere compared to the natural environment. Novi Sad (45°15’N, 19°50’E) is located in the northern part of Serbia, i.e. on the southern part of the Pannonian Plain and it is the second largest city in the country with a population of about 320,000 in a built-up area of approximately 80 km2. The geographical area is plain, from 80 to 86 m a.s.l., with a gentle relief, so its climate is free from orographic effects. According to Köppen-Geiger climate classification, this region is categorised as Cfa climate (temperate warm climate with a rather uniform annual distribution of precipitation). In the last 20 years, a few papers have been published considering urban heat island (UHI) investigations of Novi Sad. The first publication in 1994 is theoretically based and presents all parameters, methods and measurements, which have to be used in order to work on UHI research of Novi Sad. The next studies from 1995 and 2006 analyzed various temperature parameters based on 30–40 year long time series and used rural and urban stations in order to get urban-rural temperature differences. Based on meteorological parameters and the structure of urban area, in 2010 the necessity of defining locations of an urban climate network was showed in order to advance further UHI research. In the last two publications from 2011 a new empirical modeling method, adjusted for cities located on plains, has been used in order to determine locations for representative stations of an urban climate network in Novi Sad.
Satellite-Driven Assessment of Surface Urban Heat Islands in the City of Zagreb, Croatia
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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.
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Along with urbanization, sealing of vegetated land and evaporation surfaces by impermeable materials, lead to changes in urban climate. This phenomenon is observed as temperatures several degrees higher in densely urbanized areas compared to the rural land at the urban fringe particularly at nights, so-called Urban Heat Island. Urban Heat Island (UHI) effect is related with urban form, pattern and building materials so far as it is associated with meteorological conditions, air pollution, excess heat from cooling. UHI effect has negative influences on human health, as well as other environmental problems such as higher energy demand, air pollution, and water shortage. Urban Heat Island (UHI) effect has long been studied by observations of air temperature from thermometers. However, with the advent and proliferation of remote sensing technology, synoptic coverage and better representations of spatial variation of surface temperature became possible. This has opened new avenues for the observation capabilities and research of UHIs. In this study, "UHI effect and its relation to factors that cause it" is explored for İzmit city which has been subject to excess urbanization and industrialization during the past decades. Spatial distribution and variation of UHI effect in İzmit is analysed using Landsat 8 and ASTER day & night images of 2015 summer. Surface temperature data derived from thermal bands of the images were analysed for UHI effect. Higher temperatures were classified into 4 grades of UHIs and mapped both for day and night. Inadequate urban form, pattern, density, high buildings and paved surfaces at the expanse of soil ground and vegetation cover are the main factors that cause microclimates giving rise to spatial variations in temperatures across cities. These factors quantified as land surface/cover parameters for the study include vegetation index (NDVI), imperviousness (NDISI), albedo, solar insolation, Sky View Factor (SVF), building envelope, distance to sea, and traffic space density. These parameters that cause variation in intra-city temperatures were evaluated for their relationship with different grades of UHIs. Zonal statistics of UHI classes and variations in average value of parameters were interpreted. The outcomes that highlight local temperature peaks are proposed to the attention of the decision makers for mitigation of Urban Heat Island effect in the city at local and neighbourhood scale.
Multitemporal Analysis of Thermal Distribution Characteristics for Urban Heat Island Management
For a reliable assessment of sustainability in big cities, it is imperative to evaluate urban ecosystem conditions and the environment of the cities undergoing economic growth. Urban green spaces are valuable sources of evapotranspiration, which is generated by trees and vegetation; these spaces mitigate urban heat islands in cities. Land surface temperature (LST) is closely related to the distribution of land-use and land-cover characteristics and can be used as an indicator of urban environment conditions and development. This study evaluates the patterns of LST distribution by employing the thermal spatial distribution signature procedure using thermal infrared data obtained from Landsat-5 Thematic Mapper. A set of 18 images, between 1985 and 2010, was used to study the urban environment during summer in 47 neighbourhoods of Porto Alegre, Brazil. On a neighbourhood scale, results show a non-linear inverse correlation (R² = 0.55) between vegetation index and LST. The overall average of the LST is 300.23 K (27.8 C) with a standard deviation of 1.25 K and the maximum average difference of 2.83 K between neighbourhoods. Results show that TSDS analysis can help multi-temporal studies for the evaluation of UHI through time.
Springer, 2017
Land surface temperature (LST), land use/land cover (LU/LC) and vegetation parameters are a substantial factor in worldwide climate change studies framework. This study of investigating urban heat islands based on thermal remote sensing data. Thermal infrared remote sensing proved its capability in monitoring temperature and affecting microclimate in urban areas. In the present study have relationships among the multiple vegetation indices, land use/land cover and LST using remote sensing techniques in the Saranda forest state of Jharkhand. Normalized difference vegetation index (NDVI), Soil-adjusted vegetation index (SAVI), Ratio vegetation index (RVI) and Normalized difference built-up index (NDBI) are used in this study. The study work has been done on the correlation of the association among the different vegetation indices, land use/land cover, and land surface temperature. The result shows that the external temperature an impact on surfaces of self-heating (hot spots) areas. The relationship between LST and NDVI result shows the negative correlation. The NDVI proposes that the green land can deteriorate the effect on mining, urban heat island while we apparent the positive relationship between LST and NDBI. This study demonstrates that the growth of the active mining, the industrial area significantly decreases the vegetation areas, hence grow the surface temperature. This study also shows that the external temperature has an impact on surfaces of self-heating (hot spots) areas. Finally, the accuracy of proposed multiple indexes is evaluated by using DGPS field survey points over the study area. This analysis demonstrates the potential applicability of the methodology for climate modeling framework.
This article presents the development and application to a set of French urban agglomerations of a method for Local Climate Zones (LCZ) attribution using the open-source language R. The LCZs classify the urban fabric at high spatial scale (such as a block of houses) according to its morphological characteristicsand land use. The LCZ classification is carried out for 42 urban agglomerations and is then related to urban heat island intensity (UHII) obtained from numerical simulations at a spatial resolution of 250m. The objective is to study the adequacy of the LCZ classification to characterise the impact of urban morphology on the UHII. The variance analysis (ANOVA) carried out confirms the highly significant relationship between LCZs and the UHII for a given urban agglomeration. For all the urban agglomerations in the sample, linear regression models show a significant correlation between the percentages of surface covered by different LCZ and the mean UHII for the time periods tes...
The urban heat island in the city of Poznań as derived from Landsat 5 TM
Theoretical and Applied Climatology, 2016
To study urban heat island (UHI), Landsat 5 TM data and in situ measurements of air temperature from nine points in Poznań (Poland) for the period June 2008-May 2013 were used. Based on data from measurement points located in different types of land use, the surface urban heat island (SUHI) maps were created. All available and qualitycontrolled Landsat 5 TM images from 15 unique days were used to obtain the characteristics of land surface temperature (LST) and UHI intensity. In addition, spatial analysis of UHI was conducted on the basis of Corine Land Cover 2006 dataset. In situ measurements at a height of 2 m above ground level show that the UHI is a common occurrence in Poznań with a mean annual intensity of 1.0°C. The UHI intensity is greater during the warm half of the year. Moreover, results based on the remote sensing data and the Corine Land Cover 2006 indicate that the highest value of the mean LST anomalies (3.4°C) is attained by the continuous urban fabric, while the lowest value occurs within the broad-leaved forests (−3.1°C). To recount from LST to the air temperature at a height of 2 m above ground level (T agl), linear and non-linear regression models were created. For both models, coefficients of determination equal about 0.80, with slightly higher value for the non-linear approach, which was applied to estimate the T agl spatial variability over the city of Poznań.
The studied medium-sized cities (Szeged and Debrecen, Hungary) are located on a low and flat plain. Data were collected by mobile measurements in grid networks under different weather conditions between April 2002 and March 2003 in the time of maximum development of the urban heat island (UHI). Tasks included: (i) interpretation and comparison of the average UHI intensity fields using absolute and normalized values; (ii) classification of individual temperature patterns into generalized types by cities using normalization and cross-correlation. According to our results, spatial distribution of the annual and seasonal mean UHI intensity fields in the studied period have concentric shape with some local irregularities. The UHI pattern classification reveals that several types of the structure can be distinguished in both cities. Shifts in the shape of patterns in comparison with the centralized pattern are in connection with the prevailing wind directions.
International journal of Environmental Science and Technology, 2023
There is a relationship between spectral indices, urban morphology, and spatial patterns with land surface temperature (LST). In this paper, LST and spectral indices in Tehran have been calculated using Landsat satellite images from 2000 to 2019. LST was improved and the results were evaluated using synoptic stations in Tehran. Pearson correlation coefficient and mean root error are used to evaluate the accuracy of temperature difference. The spatial variables affecting LST are examined including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Digital Elevation Model (DEM), Building Density (BD), and Road Density (RD). The rise in the temperature of the land surface temperature, which causes the formation of heat islands, is continuously increasing over time and can be seen in some parts of the city. The findings indicate that LST relative accuracy was 0.98 and the root-mean-square error is 2.65 °C. The distance pattern based on the Pearson correlation test showed an effective relationship between LST and the examined indicators. Spots prone to heat islands were identified. Each of the heat island areas of Tehran was studied according to population centers (dense areas using residential, commercial, and industrial lands). The built-up and barren areas index had the highest correlation with surface temperature in most areas. The results showed that regions 9, 13, 18, 21, and especially region 22, which has the most barren land, have the highest surface temperature compared to the surrounding areas. The findings of this study can be used in future urban planning and policy-making.