Available online at www.sciencedirect.com ScienceDirect Procedia Engineering 169 (2016) 80 – 87 4th International Conference on Countermeasures to Urban Heat Island (UHI) 2016 Integration of Thermal Comfort Information with Spatial Modelling in Erzurum City Center Sevgi YILMAZa*, Ahmet KOÇa, Emral MUTLUa, Nalan DEMIRCIOGLU YILDIZa a Department of Landscape Architecture, Ataturk University, Erzurum, 25240, Turkey Abstract Integration of bioclimatic conditions with GIS was planned in the present study, conducted in the centre of Dadaskent district of Erzurum In order to reduce the error ratio at the integration stage in maps, totally 12 points in the size of nearly 400x400 m were created on them SVF and simultaneous temperature and humidity measurements were conducted at each grid point in the area including district centre representing a surface area of 19.2 km2 As the result of the study, efficiency of open and shadowy areas preferred according to seasons tried to be determined © 2016 2016The TheAuthors Authors Published by Elsevier Ltd is an open access article under the CC BY-NC-ND license © Published by Elsevier Ltd This (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the organizing committee of the 4th IC2UHI2016 Peer-review under responsibility of the organizing committee of the 4th IC2UHI2016 Keywords: Urban; thermal comfort; ArcGIS, Sky view factor; Erzurum Introduction It is vitally important in urban living environments to catch thermal comfort conditions and also a requirement in especially landscape works to design comfortable areas for people Depending on global economic relationship, cities gain importance and population accumulates in cities Population movement to cities increases stresses and urbanization also increases Today, this issue is not solved through policies in several countries by reducing the effects of humans and urbanization on the subject and thÕs increasing the matter larger and larger As structures get denser, physical urban environment changes and livable environment shrinks Limited environment and increasing stresses can cause different microclimate types in cities * Corresponding author Tel.: +90 442 231 5320; fax: +90 442 231 5881 E-mail address: syilmaz_68@hotmail.com 1877-7058 © 2016 The Authors Published by Elsevier Ltd This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the organizing committee of the 4th IC2UHI2016 doi:10.1016/j.proeng.2016.10.010 Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 [1,2], which unfavorably affect human comfort [3,4,5,6] Structures have also negative impacts on urban heat distribution [7], which causes urban heat island affecting life comfort [8,9,10] and human comfort and energy balance [11] In some studies, thermal comfort and sky view factor are considered to determine the distribution of urban heat on urban geometry [12] It was stated in some studies on urban sites that even though it is weak, there is a negative relationship between SVF and UHI formation [13] Aim of present study is to evaluate effect of urbanization and urban geometry for a more livable urban climate It is a requirement to use true natural elements to decide accurately in health urbanization Therefore, planners should have a climatic template analysis to decide truly Materials and Methods As the case study area, Dadaskent district is located at the west side of the city of Erzurum which is located in eastern Turkey with an altitude of 1850 meters (39°54މ35ފN, 41°16މ32ފE) (Fig 1) It has a harsh continental climate condition which means long and extremely cold winters Measurement Dadaskent is a settlement area planned as a satellite site and located on a smooth plain with no altitude differences Measurements were conducted in this area by researchers between 11:00 and 12:00 in October-September 2015 with a time difference of to when passing from one point to another Fig Location of study area – Erzurum West Simultaneous temperature and humidity values were measured from the points Sky view factors (SVF) data were also obtained at the same points in the middle, on the right and left side of each street three times using fisheye photograph device and average of three values were accepted to be the last value Sky view factor (SVF) can be defined to be a measure (between and 1) of seeing sky from a define point [14]; which can be estimated taking hemispherical photographs through fish eye lens (on 180° image) The SVF is a dimensionless parameter between (no sky visible) and (free hemisphere) representing the geometric ratio of a given location that expresses the fraction of the overlying hemisphere occupied by sky [27] Research assistants were told how to take pictures with fish-eye lens (Nikon D5100 digital camera and Nikon 0.25 X SupertiD fisheye conversion lens) to obtain SVFs from the photos (October-September 2015) 81 82 Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 It is very important for a healthy and comfortable urbanization to determine how chosen land-uses can affect urban microclimate 12 stations have been selected to symbolize the city center Data of other 12 stations were obtained during spring period of October-September 2015 SEA using data logger measuring air temperature and relative humidity (YCOM – KMN 305 model) is 1.5 m above ground surface Cloudiness (octas) and wind speed (ws) were accepted to be the same all over the urban area and the data of these two parameters belonging to Central Meteorology station Winds and humidity were performed on data for 2015 provided from the Turkish State Meteorological Service, Electronic Data Process Center Division Inverse Distance Weighted (IDW) is a method to use for interpolating cell values considering sample data points in the neighborhood of each processing cell If the points are estimatedly closer to other points, accurate interpolation can be possible (http://webhelp.esri.com/) Weighed moving average is an approach to be used for mean interpolation Inverse Distance Weighted (IDW) is an interpolation method used to define cell values by taking the average of sample data points in the neighborhood of each processing cell [15] Varieties of different weighed functions were used but IDW was accepted to be the most common form among GIS applications IDW is an absolute value producer (interpolator) by approving values of data IDW method can be used to prepare temperature maps [16,17] In its standard version there are 12 points at minimum and sometimes radius (r) may be enlarged satisfy needs [18] Results and Discussion It was aimed to determine if there is a relationship between SVF and UHI through the measurement in urban area From the results of the analyses graphics below were obtained (Fig 2.) 4.1 Integration of data with ArcGIS Data of SVF, temperature and humidity were evaluated in ArcGIS 10.2 program in Geostatical analysis module by preparing humidity, temperature and SVF maps Fig represents measurements SVF analysis at locations 4.2 Data mapping A temperature distribution map was prepared according to measurement results and their geospatial analysis According to instant measurements, temperature ranged between 19°C and 20.4°C and when considered the temperature distribution (Fig 3.) Using geospatial analysis and simultaneous measurements humidity distribution map was prepared (Fig 4.) When considered this map, it was seen that relative humidity changed between 32% and 35%, which increased in interior part of the area The reason for this may be that since the structures are dense in this site it deteriorated urban geometry and serves as a barrier shading agent by preventing humidity caused by evaporation from going away Humidity is lower in northeast side of the area When considered temperature distribution in Fig 3, the same areas have also higher temperature degrees Humidity from evaporation can go away due to high temperature in this side It was found that it increases in the north east side of the study area The reason for this may be that prevalent wind direction is in the same way and urbanization is also seen in this side by blocking wind From this perspective, in the northeast side of the area there is a slight urban heat island Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 Fig Measurement points, SVF and data tables 83 84 Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 Fig Temperature distribution map SVF distribution map was prepared considering simultaneous measurements and geospatial analysis (Fig 4) From the map, SVF changed between 0.4 and which means that closing to shows increase in sky view [19,20,21,22] SVF values increase from South to south-east Results of the study show that the number of floors in multi-story buildings, width of streets and climate can affect comfort On humidity map, areas are humid in the rates from 32 to 35% and this rate is high in the interior part of the area caused by urban geometry in among high buildings blocking humidity to go out and shading effect of buildings in the interior part and humidity from evaporation is not allowed to go out the city SVF map shows that sky can be seen more in south east side caused by loose structuring A close relationship can be seen between humidity and temperature distribution and SVF When sky is seen more surface temperature increases and humidity is lost from evaporation by causing UHI Ketterer and Matzarakis [12] stated that rural area is cooler than urban due to the presence of high rate of wind close to ground Fig SVF distribution map Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 In literature, SVF is used together with GIS applications [23,24] In a study in Hong Kong, a relationship was constructed between urban development plan and SVF analysis was integrated with development plan In the maps from the study, it was seen that there is a close relationship between urban geometry and microclimate [20] In the present study, urban geometry, urbanization, housing density, and building length and SVF is seen to affect the distribution of temperature and humidity From the analyses, it is seen that UHI is denser in the area with densely built area, north – northeast side of the area, where SVF is poor being lower than 0.5 SVF is lower in the areas where temperature is high Relationship between temperature, humidity and SVF is given in Fig 5, which is slight between SVF and temperature and temperature and Moisture while there is no relationship between SVF and Moisture A similar result was stated in 2011 in Manchester where there is a weak and negative relationship between SVF and temperature [13] The intensity of the intra-urban differences of thermal conditions as well as of the UHI depends strongly on the sky view factor (SVF), built-up ratio (aspect ratio) and green surface ratio [25,12] Fig Relationship between temperature, humidity and SVF in urban area UHI effect is accepted to be effective on thermal performance of buildings If a surface views sky less than others, then cooling ability of this surface is also lower than others [14] SVF is accepted to be a parameter used in the measurement of UHI effect in urban canyons, which cause UHI for their lower SVF values In the morning excessive heat absorbed by canyons cannot go back into sky also in the evening causing higher temperature and also poor thermal comfort conditions and showing negative relationship with SVF [26] The urban heat island intensity tends to increase when SVF decreases A decrease in SVF means a reduction of visible sky area from the canyon [13] It is defined that there is a relationship between SVF and temperature However, more measurement points are needed in GIS analyses since such a relationship is dependent on topography, house length and density, land use, season, measurement time and point It is possible to get different values in the same settlement area due to different characteristics Conclusion According to the results from the study, urbanizing can directly affect climate Tall buildings constructed in the vertical direction of prevalent wind direction in especially summers can serve as barrier causing UHI and negatively affecting human comfort Such unfavorable effects are seen in the study area 85 86 Sevgi Yilmaz et al / Procedia Engineering 169 (2016) 80 – 87 Factors affecting comfort in urban area also tried to be determined It was stated in the study that urbanization may directly affect urban climate and by using data obtained from the studies related to climate and urban comfort healthier urbanization, urban transformation and new construction of settlements can be obtained to get more comfortable living environments Human quality of life can be increased through relocation, development and expansion of cities to comfortable areas or increasing comfort conditions in the areas with low comfortable conditions intervening them Results of such studies using climate data can contribute to the formation of more livable and comfortable cities in urban transformation and opening new areas Life quality can increase in cities by founding and developing them in comfortable areas or intervening low comfortable areas Such attempts are vitally important for human comfort It is absolutely needed to analyze topographic and climatic data for a healthy urbanization This 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the areas with low comfortable conditions intervening them Results of such studies using climate data can... formation of more livable and comfortable cities in urban transformation and opening new areas Life quality can increase in cities by founding and developing them in comfortable areas or intervening... Process Center Division Inverse Distance Weighted (IDW) is a method to use for interpolating cell values considering sample data points in the neighborhood of each processing cell If the points