Investigation of Ground Surface Temperature Increases in Urban Textures with Different Characteristics: The Case of Denizli City

Abstract

Today, urban areas have started to grow and expand with the urbanization and industrialization processes brought about by rapid population growth. The increase in urban density brought about by this growth process has led to the destruction of natural areas and created surfaces such as concrete, asphalt, etc., that absorb solar energy. The expansion/proliferation of impervious surfaces in the city has changed the urban climate in the direction of temperature increase compared to the surrounding rural areas. When this change is combined with the temperature increases due to global climate change, it creates urban heat islands, especially in high density areas, and directly affects land surface temperatures. In this study, ground surface temperature analysis for the years 2012–2022 was carried out in order to determine the temperature changes in Denizli city. As a result of the analysis, eight urban textures with different characteristics with very high and high temperature increase were determined. Analyses were made in the context of urban heat island criteria in the determined textures, and the effect of the settlement pattern on urban heat island formation was examined by making use of the analysis results and related literature findings.

1. Introduction

One of the most widespread consequences of climate change on a global scale is temperature increase, which has direct impacts on urban areas. Temperature increase leads to many negative consequences such as reduction in water resources, difficulty in accessing clean water, increase in the amount of energy consumption, deterioration of biodiversity, etc. The Intergovernmental Panel on Climate Change (IPCC), in its special report on the effects of global warming, stated that human-induced warming reached about 1 °C above pre-industrial levels in 2017 and will increase by 0.2 °C per decade. In addition, according to the IPCC 6th Assessment Report (AR6), global average surface temperatures caused by human activities increased by 1.1 °C in the 2011–2020 period compared to the 1850s. According to the future scenarios of the report, if greenhouse gas emissions continue to increase at the current rate, global warming is projected to exceed 1.5 °C between 2030 and 2052 [1].

Due to its geographical location, Turkey is located in regions that will be directly affected by temperature increases and the average annual temperature is expected to increase by 2–3 °C by 2100 and summer temperatures are expected to rise by 6 °C in the western half of the country [2]. Cities that are directly affected by temperature increases have higher temperature values compared to the surrounding rural areas, forming urban heat islands. The urban heat island is directly related to the way the city is built and the lack of natural areas in cities that allow the absorption of solar energy, and this situation is directly related to land use and construction patterns. The urban heat island effect is a widely observed phenomenon characterized by higher outdoor temperatures in urban areas than in rural areas. This effect is primarily caused by urban structures such as heat-absorbing materials such as asphalt and concrete, inadequate vegetation, and anthropogenic heat emissions [3].

In this context, when the literature examining the relationship between urban heat island effect and construction is examined, studies are mainly addressing urban geometry, urban growth and expansion, plant density, landscape, and blue–green infrastructure design and land use/land cover data [4,5,6,7]. In studies linking the urban heat island effect with urban geometry, the heat island was found to be high at points with low sky clearance [8]. In this context, the importance of urban design in reducing urban heat island effects is emphasized and it is stated that the albedo effect and urban geometry should be taken into consideration [9]. Canan and Geyikli [10] state that the sky visibility factor value changes according to urban density in areas with different urban texture and geometry and has an effect on heat island formation. In addition, urban heat island is associated with Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values, building height, sky visibility and building density, including urban form and building conditions [11,12]. Studies in urban areas have focused on examining the relationships between human activities, land use changes, and their environmental consequences, with an emphasis on sustainable land use. In the context of land use and cover change (LUCC), the main factors contributing to the UHI effect are the proliferation of impervious surfaces and the decline of natural urban vegetation. The occurrence of the UHI effect is not solely associated with land use types; other factors also play important roles. The researchers note several factors, including anthropogenic heat release, solar radiation capture in urban structures, scarcity of green spaces, and inadequate air circulation in urban canyons [13]. In studies that associate the urban heat island effect with urban growth and expansion, it is stated that surface temperatures increase with the spatial expansion of the city and the transformation of permeable surfaces into impermeable surfaces. In addition, when the relationship between the growth pattern/motif of cities and heat island is established, it is stated that sprawling cities are exposed to heat island effects more than compact cities [14,15]. In studies addressing the urban heat island effect with plant density values calculated through satellite images, cities are classified according to various common characteristics and vegetation values (Normalized Vegetation Index (NDVI) and Land Surface Temperature (LST) are calculated). In this context, it is stated that surface temperatures increase as a result of the decrease in plant density with urban development [16,17]. In studies addressing the urban heat island effect with landscape elements and blue–green infrastructure, architectural design and green infrastructure are considered important. In this context, the increase in surface temperatures was associated with the decrease in green space and evaporation surfaces due to urbanization, and it was determined that temperatures increased at points where the amount of green space decreased [18,19]. Recent research has demonstrated the role of tree canopy cover in mitigating UHI effects. Large and small green spaces contribute to cooling and can span approximately half the width of a park due to street geometry [20]. Remote sensing methods are the most commonly used methods for urban surface heat island studies. Unlike satellite data, remotely sensed airborne thermal data provide a much higher level of detail and allow for the study of micro-scale variations in LST across different elements of the urban landscape [21]. In addition, it is stated that surface temperatures are affected by the design of vegetation cover and blue–green infrastructure and that designs should be made at different scales (micro and meso) for urban cooling [22].

As another factor, surface temperatures were calculated through satellite images and associated with the urban heat island through land use/land cover data. In this context, it is stated that urban areas with hard and impermeable surfaces and industrial areas have higher temperature values compared to wetlands and other natural and green area [23,24,25,26]. Advances in remote sensing technology have significantly facilitated the better understanding of the spatiotemporal characteristics of UHI research. In this context, a dramatic increase in remote sensing-based studies worldwide has been noted since 2010 [27].

In this study, ground surface temperature (GST) maps were created in Denizli city with thermal remote sensing methods, temporal changes in temperatures were calculated, and urban textures with very high and high temperature increase were determined. These textures have different land use functions (residential, industrial, commercial, etc.) and different characteristics in terms of building layout, height, and Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values. In these selected textures, texture analysis was carried out in the context of the criteria (sky visibility factor, building height/street-width, etc.) included in the studies examining the urban heat island effect in the literature. In this context, the effect of different uses and building layout on surface temperatures according to the form/pattern of construction was analyzed and measures to provide urban cooling by reducing the urban heat island effect were developed.

2. Materials and Methods

2.1. Study Area

A recorded border study window is created by drawing approximately 200–300 m. from the rectangular area perimeters within the borders of the central districts of Denizli province (Merkezefendi and Pamukkale) with the Google Earth program. The study area border recorded with this ability is expressed as “Denizli city” and its surface area is approximately 161 km² (Figure 1).

Denizli province, where the study area is located, is located in the east of the Aegean Region, at the intersection of the Aegean–Central Anatolia and Mediterranean Regions. Burdur and Afyonkarahisar are in the east of the province, Aydın and Manisa are in the west, Uşak is in the north, and Muğla is in the south. According to the 2024 TÜİK Address Based Population Registration System data, the total population of the province is 1,061,371 people [28] (Türkiye Statistical Institute). The population of the central districts is Pamukkale 345,850, Merkezefendi 345,933 people. In terms of administrative division, the province has 19 district municipalities, including the central districts, a metropolitan municipality, and 622 neighborhoods. With Denizli becoming a metropolitan municipality in 2012, the entire provincial border was determined as the metropolitan municipality border and all rural settlements gained neighborhood status.

The city of Denizli is located within the main Aegean section of the Aegean Region. Located within the Mediterranean climate zone, Denizli exhibits all the characteristics of this climate type: hot, dry, and sunny summers, and mild, moderately rainy winters. Between 1970 and 2022, Denizli’s average temperatures reached their highest levels in the summer months and remained below freezing in the winter months. According to these figures, temperatures in the city begin to decline from mid-September, with the average temperature of 22.9 °C dropping by 5.8 °C to 17.1 °C in October (

Table 1. Denizli city average temperatures (1970–2022).

J	F	M	A	M	J	J	A	S	O	N	D
5.9	7.3	10.2	14.8	19.8	24.5	27.6	27.2	22.9	17.1	11.5	7.4

J: January, F: February, M: March, A: April, M: May, J: June, J: July, A: August, S: September, O: October, N: November, D: December.

).

Denizli’s average annual temperature between 1970 and 2022 was 16.3 °C. When looking at the average monthly high temperatures between these years, the highest value was seen in July at 27.6 °C and August at 27.2 °C, while the lowest value was seen in January at 5.9 °C. When looking at the city’s average temperatures between 2012 and 2022, which are the reference years, an increase in winter temperatures and changes in the warmer months of the year were observed. This study covers the city of Denizli where the construction is dense. According to the outputs of the RCP4.5 and RCP8.5 scenarios prepared with the HadGEM2-ES model within the scope of the Denizli Climate Change Action Plan, it is expected that the average temperature increases will be greatest in the summer months (over 4 °C) and the annual average temperature will increase by 1.8–2 °C in the 2015–2044 period and by 2.6–3.4 °C in the 2045–2074 period (Figure 2) [29].

According to the average temperature data for 2022 obtained from the General Directorate of Meteorology, temperatures increase in the central districts and decrease towards the periphery. ArcGIS 10.8 program and Landsat 5 TM and Landsat 8 OLI/TIRS satellite data published by the United States Geological Survey (USGS) were used in this study. In this context, August, the month with the warmest and lowest cloud cover, was selected to analyze annual temperature changes, and a reference period with a ten-year interval was established. Landstat Collection 2 Level 1 (1 August 2012) and Landstat Collection 2 Level 1 (1 August 2022) images were used in accordance with the specified date. By using the warmest month data in the study, the effect of seasonal temperature differences on surface temperature changes was ignored. A single month was chosen as the representative month because it is the warmest and lowest humidity month in Denizli. Multispectral bands with a spatial resolution of 30 m from the satellite images provided for the study were limited to the study area (

Table 2. Characteristics of satellite images.

Landsat 8 Satellite Images
Date	1 August 2012	1 August 2022
Time	08.42	08.40
Wrs_Path	179	179
Wrs_Row	34	34
Cloud Cover	1.17	0.80

).

Maps were prepared using OLI Band 4, Band 5, and TIRS Bands 10 and 11, from August’s metadata files of the Landsat 8 satellite covering the city of Denizli. The NDVI (Normalized Difference Vegetation Index) was determined using the Band 4 and Band 5 images, and the spectral radiance value was determined using the pixel values of the thermal bands, Bands 10 and 11. The brightness temperature map of the region was created using the obtained spectral radiance value. The K1 and K2 variables required for the creation of this map were obtained from the satellite metadata and included in the process. Since the BT value is in Kelvin, the values were converted to Celsius using a formula. PV (vegetation cover ratio) was determined using the NDVI data obtained from Bands 4 and 5. The PV values were then converted to LSE (emissivity) values. Finally, the LSE and BT values were processed to create earth surface temperature maps and were repeated for 2022.

2.2. Production of Earth Surface Temperature Maps

Surface temperature analysis is completed within a certain row. In the first stage, the satellite data obtained were converted to the format that image processing programs may recognize. The purpose of the image pre-processing is to improve the image and/or to obtain useful information from the image through certain operations. In this study, the geometric corrections were limited to remain within the city of Denizli and a pre-processing procedure was performed in this way. In this study, a single window algorithm was applied to Landsat 4 and 5 TM images. According to Qin et al. [30], using the Landsat 5 TM images of the single window algorithm, earth surface temperature can be calculated. This algorithm requires three main parameters. The others are atmospheric permeability and average atmospheric temperature. In order to obtain these data with the help of a number of equations, temperature and humidity data were received from the General Directorate of Meteorology at the dates of these images and analyses were performed.

In order to determine the ground surface temperature values, thermal image band values must be converted into spectral radiance values. For this purpose, the band values (Band 10 and Band 11) of the thermal images were converted into radiance values using the data in the MTL extension files in the metadata folder obtained with satellite images. In this context, the formula used for Landsat 8 OLI is expressed by Equation (1) [31].

L_λ = M_L × Q_cal + A_L

(1)

In the formula, L_λ: radiance value, M_L: radiance multiplicative scaling factor, Q_cal: pixel value of the satellite image, A_L: radiance scaling factor, and the M_L and A_L values in the formula are located in the metadata folder. The radiance value was calculated using the formula via ArcGIS 10.8 program Spatial Analysts Tools-Map Algebra-Raster Calculator in the ArcGIS program. The formula used to convert the calculated radiance values to temperature values is expressed by Equation (2) [32].

$$\mathrm{Tb}={\displaystyle \frac{\mathrm{K}2}{\ln \left(\frac{\mathrm{K}1}{{\mathrm{L}}_{\mathsf{\lambda }}}+1\right)}}-273.15$$

(2)

In the formula, Tb: sensor brightness temperature value in Kelvin, K1 and K2: calibration constants in Kelvin, and these values are located in the metadata folder. L_λ represents the radiance values calculated in the previous step. The value 273.15 in the formula is used for conversion from the Kelvin (K) temperature unit to Celsius (°C). Spectral radiance values were converted to temperature values using thermal conversion constants (K1 and K2) via Spatial Analysts Tools-Map Algebra-Raster Calculator in ArcGIS 10.8 program.

In determining surface temperatures, the vegetation cover ratio is a parameter used to measure ground surface emissivity. In order to determine this ratio, the Normalized Vegetation Index (NDVI) should be calculated. In this context, Band 4 and Band 5 values are used. NDVI value was calculated by using the formula through Spatial Analysts Tools-Map Algebra-Raster Calculator-Float in ArcGIS 10.8 program. The formula used for this is expressed in Equation (3) [33,34].

$$\mathrm{NDVI}={\displaystyle \frac{\left(\mathrm{Band} 5-\mathrm{Band} 4\right)}{\left(\mathrm{Band} 5+\mathrm{Band} 4\right)}}$$

(3)

In the formula, Band 5 means near infrared for Landsat 5 TM satellite and Band 4 means the red band for the Landsat 5 TM satellite. Then, using the NDVI value, the vegetation cover ratio (PV) was calculated by using the formula through Spatial Analysts Tools-Map Algebra-Raster Calculator-Square in ArcGIS program. The formula used for this is expressed by Equation (4) [35].

$$\mathrm{PV}=\left({\displaystyle \frac{\left(\mathrm{NDVI}-{ \mathrm{NDVI}}_{\min }\right)}{\left({\mathrm{NDVI}}_{\max }-{ \mathrm{NDVI}}_{\min }\right)}}\right)2$$

(4)

In the formula, PV: vegetation cover ratio and NDVI_min and NDVI_max means the minimum and maximum values of NDVI values, respectively. After calculating the PV value, the emission rate (ε), which is related to PV, was calculated in ArcGIS program through Spatial Analysts Tools-Map Algebra-Raster Calculator. The formula used for this is expressed by Equation (5) [35].

ε = 0.004 × PV + 0.986

(5)

In the formula, ε: diffusivity (radiation) value and PV: vegetation cover ratio. After determining the irradiance value, the values representing the actual surface temperature were calculated by correcting this value for ground surface irradiance [36,37]. The formula used for this is expressed by Equation (6) [38].

$$\mathrm{LST}={\displaystyle \frac{\mathrm{T}}{\left(1+\left(\frac{\mathrm{w}.\mathrm{T}}{\mathsf{\rho }}\right)\times \ln \left(\mathsf{\epsilon }\right)\right)}}$$

(6)

In the formula, LST: ground surface temperature value, T: satellite temperature value, w: average wavelength value of the thermal band (10.9 μm), ρ: constant value, and ε: emissivity (radiation) value. The values determined in the previous steps and the constant values were substituted in the formula and calculated for Band 10 and Band 11 in the ArcGIS program via Spatial Analysts Tools-Map Algebra-Raster Calculator. All processes were repeated with the data of 2012 and the ground surface temperature maps of the reference years in Figure 3 were created.

According to the values calculated as a result of the analysis, ground surface temperatures were divided into five classes. The colors visualized on the map include specific numerical ranges to define temperature classifications. In this context, blue (very low), green (low), yellow (medium), orange (high), and red represents very high. The analysis determined that the highest values were between 36.1 and 40 °C in 2012 and 38.1 and 41 °C in 2022. The lowest values were between 18 and 22 °C in 2012 and 24 and 28 °C in 2022. While average temperatures were 26.8 °C in 2012, they reached 31.2 °C in 2022. In this context, it was determined that ground surface temperatures increased by an average of 0.2 °C per year.

When we look at the changes in surface temperatures, it is seen that they are high in areas where construction is dense and development is directed. In general terms, temperatures in the study area increase from the south to the north of the city. After the creation of ground surface temperature maps, textures were identified in areas where the temperature increase was determined to be very high and high. The textures identified at this stage are located in Denizli city center, the Kaleiçi region containing the old city texture, and in the regions containing industrial and storage areas and TOKI residences in the north of the city.

2.3. Urban Fabric Analysis in Areas with Very High and High Temperature Rise

In Denizli, meteorological data, scenarios prepared as part of the climate change action plan, and ground surface temperature analysis have identified areas at risk of temperature increase. To conduct spatial analyses in areas with “very high and high” temperature increases, patterns with different characteristics were selected. The selected patterns’ spatial functions within the city’s spatial structure vary, including residential, commercial, historical, and industrial areas. According to the results of the surface temperature maps, the relationship between the urban heat island and the construction order in the areas where the temperature increase is very high (38.1–41 °C) and high (35.1–38 °C) was examined and urban texture analysis was conducted. In this context, 8 urban textures were selected in Denizli city, including mass housing areas (2 textures), industrial and storage areas (1 texture), high-rise/residence type housing (1 texture), adjacent 7–8 story apartment buildings in the city center (2 textures), commercial function buildings in the historical texture (1 texture), and villa type housing (1 texture). The locations of the selected textures in Denizli city are given in Figure 4.

In selecting the areas for which texture analysis was conducted, attention was paid to ensuring that they were located in areas with the highest temperature increases as a result of the analysis and that they differed in terms of building layout, height, and BCR-FAR parameters. Therefore, areas containing building blocks and roads of varying sizes were selected. Consequently, the analyzed textures were designed as areas with significant functional areas within the spatial structure of the city or areas that contain different functions.

Information on the method used to obtain data by establishing the relationship between the evaluation criteria addressed within the scope of tissue analysis and the literature findings is given in Table 3.

In the sheets used in the analysis of the identified urban textures, its location in Denizli city, its location with its immediate surroundings on the satellite image, and its status in the implementation zoning plan are included. In addition, attempts were made for the texture features to be reflective of the photographs taken on site. In the following analyses:

In the park/green area (m²) parameter, the sizes of parks and green areas identified during on-site observations were calculated through Google Earth and TKGM Parcel Query application. In the wooded area (m²) parameter, wooded/shrubby areas outside the parks, wooded areas located in residential gardens in the parcel, and areas scattered in the city or within the site were calculated through Google Earth and TKGM Parcel Query application, and trees were counted during observations. In the parameter of water surface (Present/Absent) (m²), water surfaces in the examined areas were examined as present/absent, and if present, their areas were calculated via Google Earth. In the road/pavement material parameter, in determining the permeable and impermeable surfaces on roads and pavements, the surfaces covered with vegetation such as grass, shrubs, trees, etc., that allow surface water drainage and the surfaces covered with soil and key paving surfaces are classified as permeable; the surfaces covered with hard materials such as concrete, asphalt, etc., are classified as impermeable. In the building material parameter, the materials used in the buildings were examined in on-site observations and the material and albedo value ranges in [39] were used. In this context, it was determined that materials with a value close to 1 have high reflectivity. In the average building height/street-width (m) parameter, the average building height was calculated by dividing the height of all buildings in the parcel by the number of buildings. The street-width was determined with reference to the road that the buildings face. In this context, building heights and street/street widths were determined by making measurements on laser meter and current map. The sky visibility factor (SVF) parameter has a value between 0 and 1 and the closer it is to 1, the better the sky visibility of that point. In this context, fisheye photography lens was used in the areas where the buildings meet the sky. In taking the photographs, the sky opening was determined with reference to the buildings positioned opposite each other. The sky visibility in the photographs taken with this lens was determined by separating the sky and non-sky areas and focusing on the open areas in the Rayman 1.2 program. In the building order parameter, building layouts were determined as Separate, Adjacent, and Block layout. In the average building height (m) parameter, it is stated that high-rise buildings reduce wind speed, increase the temperature by preventing heat loss, and if the building heights on both sides of the road are the same, the temperature is distributed more evenly [40,41]. In this context, building heights were measured using a laser meter and the average value was determined by dividing the sum of the measured values by the number of buildings. In the prevailing wind direction/positioning of buildings parameter, according to the data obtained from the General Directorate of Meteorology, the dominant wind direction of Denizli city is southeast. The orientation of the buildings was determined by comparing photographs and satellite images. In the parameter of construction condition, calculations were made through TKGM Parcel Query and Denizli City Information System applications, Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values were determined according to the existing constructions, and the situation in the application zoning plan was included.

Table 3. The literature findings on the risk of temperature increase, criteria, and data supply.

Literature Findings	Criteria	Data Acquisition Method
Depending on the size of the park/green areas, the temperature reduction effect varies. A wooded area of 50–100 m2 decreases the temperature of the city by up to 1.5 °C, while this amount increases as the area increases. It has also been observed that the average cooling effect of a 0.15 hectare park is 1.5 °C and reaches 3 °C at midday [42].	Size of parks and green areas	Observation in the field Photo shoot Google Earth Pro
On a sunny day, one tree cools with a power equivalent to 20–30 kW, which is equivalent to about 10 air conditioning units [43].	Outside the park wooded areas	Observation in the field Photo shoot Google Earth
Water surfaces are a mitigating factor for the urban heat island effect and a wetland with a 30–35 m. spread provides a cooling effect of 1–3 °C [44].	Water surface	Observation in the field Photo shoot Google Earth
Pavement materials such as asphalt and concrete absorb 60–95% of the solar energy incident on surfaces and reflect 5–40% [45].	Road and sidewalk coating material	Observation in the field Photo shoot
Dark, dull, and rough surfaces of building materials in cities absorb and store heat; light and bright colored objects do not heat up much because they reflect light [46].	Building cladding material	Observation in the field Photo shoot
Urban street layout has an impact on heat dissipation and there is a natural cooling effect in areas where the ratio (height/width) is close to 0.5 [47].	Building height street/ street width	Observation in the field Measurement with laser meter Current map
Streets with low sky visibility (between 0 and 1) do not heat up much in winter and cool down very late in summer [40].	Visibility of the sky between buildings	Observation in the field Photography with fisheye lens
Large surface areas in urban areas store more heat. Less heat is stored with compact (contiguous) buildings [43].	Building layout	Observation in the field Photo shoot Current map
High-rise buildings in urban areas cause a decrease in wind speed, prevent heat loss, and increase the temperature. In this context, wind speed decreases as building height increases [40].	Building height	Observation in the field Photo shoot Measurement with laser meter
When buildings are located parallel to the prevailing wind direction, they intercept the air and prevent it from reaching urban areas. Perpendicular positioning of buildings effectively directs the air flow [48].	Prevailing wind direction and building location	Observation in the field Photo shoot Meteorological data
Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values for urban ventilation increase the efficiency of the building and the building island [49].	Building Coverage Ratio (BCR) Floor Area Ratio (FAR)	TKGM Parcel Query Denizli Address Information System

Table 3. The literature findings on the risk of temperature increase, criteria, and data supply.

Literature Findings	Criteria	Data Acquisition Method
Depending on the size of the park/green areas, the temperature reduction effect varies. A wooded area of 50–100 m2 decreases the temperature of the city by up to 1.5 °C, while this amount increases as the area increases. It has also been observed that the average cooling effect of a 0.15 hectare park is 1.5 °C and reaches 3 °C at midday [42].	Size of parks and green areas	Observation in the field Photo shoot Google Earth Pro
On a sunny day, one tree cools with a power equivalent to 20–30 kW, which is equivalent to about 10 air conditioning units [43].	Outside the park wooded areas	Observation in the field Photo shoot Google Earth
Water surfaces are a mitigating factor for the urban heat island effect and a wetland with a 30–35 m. spread provides a cooling effect of 1–3 °C [44].	Water surface	Observation in the field Photo shoot Google Earth
Pavement materials such as asphalt and concrete absorb 60–95% of the solar energy incident on surfaces and reflect 5–40% [45].	Road and sidewalk coating material	Observation in the field Photo shoot
Dark, dull, and rough surfaces of building materials in cities absorb and store heat; light and bright colored objects do not heat up much because they reflect light [46].	Building cladding material	Observation in the field Photo shoot
Urban street layout has an impact on heat dissipation and there is a natural cooling effect in areas where the ratio (height/width) is close to 0.5 [47].	Building height street/ street width	Observation in the field Measurement with laser meter Current map
Streets with low sky visibility (between 0 and 1) do not heat up much in winter and cool down very late in summer [40].	Visibility of the sky between buildings	Observation in the field Photography with fisheye lens
Large surface areas in urban areas store more heat. Less heat is stored with compact (contiguous) buildings [43].	Building layout	Observation in the field Photo shoot Current map
High-rise buildings in urban areas cause a decrease in wind speed, prevent heat loss, and increase the temperature. In this context, wind speed decreases as building height increases [40].	Building height	Observation in the field Photo shoot Measurement with laser meter
When buildings are located parallel to the prevailing wind direction, they intercept the air and prevent it from reaching urban areas. Perpendicular positioning of buildings effectively directs the air flow [48].	Prevailing wind direction and building location	Observation in the field Photo shoot Meteorological data
Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values for urban ventilation increase the efficiency of the building and the building island [49].	Building Coverage Ratio (BCR) Floor Area Ratio (FAR)	TKGM Parcel Query Denizli Address Information System

3. Findings

The outputs of this study carried out in accordance with the relevant parameters within the scope of urban texture analysis are given below.

1. Texture: It includes TOKİ residences located in Merkezefendi district, Kayaköy neighborhood, 8185 Block-1 Parcel, 8186 Block-1 Parcel, 8190 Block-1 Parcel, 8191 Block-1 Parcel, 8189 Block-2 Parcel. As a result of the analysis, the following points were discovered (

Table 4. 1. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	Park: 240 m2	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	5550 m2	Decrease
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	110 units	Decrease
Water Surface	m2	30–35 m water surface	1–3 °C reduction	No	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.86–1.92 m	Increase
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.08–0.49	Increase
Building Order	Adjacent	-	Stores heat	-
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	19.2 m	Increase
		20–30 m >30 m	Increases 3 °C	23.3 m	Increase
Prevailing Wind Direction	SE	Parallel	Stores heat	NW, N	Increase
		Upright	Disperses heat	-
Structuring Condition		BCR	Stores heat	-
		FAR	Disperses heat	FAR: 1.40	Decrease

):

• When the amount of wooded and vegetated area in the parks is evaluated in terms of heat island effect, the ratio of hard and soft ground is not homogeneously distributed;
• There are wide openings in terms of wooded areas and number of trees to provide sufficient cooling effect;
• That there is no natural or artificial water surface;
• The use of impermeable materials including hard materials on roads/sidewalks;
• Albedo values remain in the range of 0.10–0.35 with reinforced concrete building material;
• The average building height (BH)/street-width (SW) ratio varies between 0.86 and 1.92;
• Sky Vision Factor (SVF) value ranged between 0.08 and 0.490;
• The settlement type is a housing estate and includes split-layout buildings;
• The average building height varies between 19.2 and 23.3 m;
• The buildings are generally oriented northwest and north, parallel to the prevailing wind direction;
• It was determined that the Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values are in compliance with the zoning plan to a great extent, but the lack of any construction in the vicinity increases the surface temperature (Figure 5).

2. Texture: It includes TOKI houses located in Merkezefendi district, Kayaköy neighborhood, 8196 Block-2 Parcel, 8195 Block-1 Parcel, 8194 Block-2 Parcel and is located on the front of Üçler Boulevard which connects to Denizli Ring Road (

Table 5. 2. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	Park: 900 m2	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	7850 m2	Decrease
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	45 units	Decrease
Water Surface	m2	30–35 m water surface	1–3 °C reduction	No	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.5 m	Decrease
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.240–0.290	Increase
Building Order	Adjacent	-	Stores heat	-
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	20 m	Increase
		20–30 m >30 m	Increases 3 °C	21.5 m	Increase
Prevailing Wind Direction	SE	Parallel	Stores heat	NW	Increase
		Upright	Disperses heat	-
Structuring Condition		BCR	Stores heat	-
		FAR	Disperses heat	FAR:1.40	Decrease

). As a result of the analysis, the following points were discovered:

• Parking areas are not homogeneously distributed and the ratio of soft to hard surfaces is not balanced;
• In terms of wooded areas and number of trees, there are wide openings that will provide a cooling effect;
• That there is no natural or artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• Albedo values remain in the range of 0.10–0.35 with reinforced concrete building material;
• Average building height/street-to-street width ratio of 0.5;
• SVF value ranged between 0.240 and 0.290;
• The settlement type is a housing estate and includes split-layout buildings;
• The average building height varies between 20 and 21.5 m;
• The buildings are generally oriented northwest and parallel to the prevailing wind direction;
• It was determined that the Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values are in compliance with the zoning plan to a great extent, but the lack of any construction in the vicinity increases the surface temperature (Figure 6).

3. Texture: It includes the factory building and warehouse areas located on 209 Block-11 Parcel, 209 Block-20 Parcel, 209 Block-19 Parcel in Bozburun Neighborhood, Merkezefendi District (

Table 6. 3. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	-	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	-	Increase
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	-	Increase
Water Surface	m2	30–35 m water surface	1–3 °C reduction	No	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.40–0.52 m	Increase
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.240–0.290	Increase
Building Order	Adjacent	-	Stores heat	-
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	10.5–12 m	Increase
		20–30 m >30 m	Increases 3 °C
Prevailing Wind Direction	SE	Parallel	Stores heat	NW	Increase
		Upright	Disperses heat	-
Structuring Condition		BCR	Stores heat	-
		FAR	Disperses heat	FAR: 1.40	Decrease

). As a result of the analyses, the following points were discovered:

• Lack of parks/green areas and wooded areas;
• That there is no natural or artificial water surface;
• The use of impermeable materials such as asphalt and pressed concrete, which include hard materials, on roads and sidewalks;
• Albedo values between 0.10 and 0.35 and 0.10 and 0.13 with the use of reinforced concrete and brick as building materials;
• The average building height/street-width ratio varies between 0.40 and 0.52;
• The SVF value could not be calculated since the factories and warehouses are not mutually located;
• In the area where the factory building and warehouses are located, the buildings are located together in separate and adjacent order;
• The average building height varies between 10.5 and 12 m;
• The buildings are generally oriented northeast and perpendicular to the prevailing wind direction;
• It was determined that the Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values were in compliance with the zoning plan, but the dense construction compared to its surroundings increased the surface temperature (Figure 7).

4. Texture: Merkezefendi district, Kayalar neighborhood, 556 Island-10 Parcel, 556 Island-11 Parcel, 556 Island-4 Parcel, which includes trade + residential areas and commercial areas and residence type residential areas and SINPAS Aquacity Houses and Aquamall Shopping Mall (

Table 7. 4. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	Park: 17,426 m2	Decrease
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	-	Increase
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	-	Increase
Water Surface	m2	30–35 m water surface	1–3 °C reduction	7.022 m2	Decrease
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.13–1.68 m	Increase
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.240–0.290	Increase
Building Order	Adjacent	-	Stores heat	-
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	6.5 m	Decrease
		20–30 m >30 m	Increases 3 °C	47–84 m	Increase
Prevailing Wind Direction	SE	Parallel	Stores heat	-
		Upright	Disperses heat	NE	Decrease
Structuring Condition		BCR	Stores heat	-
		FAR	Disperses heat	FAR: 0.50	Decrease

). As a result of the analysis, the following points were discovered:

• Parking areas are only within the site and not evenly distributed;
• There are no large gaps in terms of wooded areas and number of trees;
• Artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• Albedo values between 0.10 and 0.35 with the use of reinforced concrete and brick as building materials;
• The average building height/street-width ratio varies between 0.13 and 1.68;
• SVF value ranged between 0.600 and 0.640;
• The settlement type is a housing estate and includes split-layout buildings;
• The average building height varies between 47 and 84 m. in the residential and shopping center and drops to 6.50 m. in the surrounding commercial area;
• The buildings are generally oriented northeast, perpendicular to the prevailing wind direction, and the Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values are higher than the surrounding buildings (Figure 8).

5. Texture: It is located in the Kaleiçi district of Merkezefendi district, Saraylar Neighborhood, where old residential and commercial areas are located and the historical texture is intensely observed (

Table 8. 5. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	-	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	-	Increase
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	3	Increase
Water Surface	m2	30–35 m water surface	1–3 °C reduction	-	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	1.70–1.75 m	Increase
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.240–0.290	Increase
Building Order	Adjacent	-	Stores heat	Adjacent	Increase
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	-
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	8.5–10.5 m	Increase
		20–30 m >30 m	Increases 3 °C
Prevailing Wind Direction	SE	Parallel	Stores heat	-
		Upright	Disperses heat	SW	Decrease
Structuring Condition		BCR	Stores heat	BCR (Adj.-3)	Increase
		FAR	Disperses heat

). As a result of the analyses, the following points were discovered:

• There are no parks/green areas, and the number of trees is very low;
• That there is no natural or artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• With the use of reinforced concrete as a building material, albedo values remain between 0.10 and 0.35;
• The average building height/street-width ratio varies between 1.70 and 1.75;
• SVF value of 0.100;
• The type of construction includes adjoining commercial areas and the fact that it is covered causes the heat to remain inside;
• The average building height varies between 8.5 and 10.5 m;
• The buildings are generally oriented southwest and perpendicular to the prevailing wind direction;
• It has been determined that the construction conditions are largely in compliance with the zoning plan, but the adjacent buildings do not allow heat dissipation (Figure 9).

6. Texture: Saraylar Neighborhood, Merkezefendi District, Saraylar Neighborhood, 222 Island-1 Parcel, 222 Island-2 Parcels, which includes housing estate type housing areas (

Table 9. 6. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	Park: 400 m2 Green Space: -	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	6.450 m2	Decrease
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	-	Increase
Water Surface	m2	30–35 m water surface	1–3 °C reduction	-	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35 0.50–0.90	Increase Decrease
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.60 m	Decrease
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.280	Increase
Building Order	Adjacent	-	Stores heat	-
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C	18.5 m	Increase
		20–30 m >30 m	Increases 3 °C	-
Prevailing Wind Direction	SE	Parallel	Stores heat	-
		Upright	Disperses heat	N, NW	Increase
Structuring Condition		BCR	Stores heat
		FAR	Disperses heat	FAR: 0.90	Decrease

). As a result of the analysis, the following points were discovered:

• Parking areas are homogeneously distributed in terms of soft and hard ground within the site;
• Large openings in terms of wooded areas and number of trees;
• That there is no natural or artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• With the use of reinforced concrete and siding as building materials, albedo values remain between 0.10 and 0.35 and 0.50 and 0.90;
• The average building height/street-width ratio is 0.60;
• SVF value was 0.280;
• The settlement type is a housing estate and includes split-layout buildings;
• The average building height is 18.5 m and buildings with different heights are located opposite each other;
• The buildings are generally oriented northwest and north, parallel to the prevailing wind direction;
• It was found that the BCR and FAR values were largely in compliance with the zoning plan, but the parcel planned as a children’s garden in the plan was used as a parking lot (Figure 10).

7. Texture: Pamukkale district, Topraklık Neighborhood, 334 Block-8, 9, 10, 11, 12 Parcel, 280 Block-9, 10, 20, 21 Parcel, 279 Block-10, 11, 12, 13, 14, 26, 27 Parcel, which are located in the city center and include adjacent residential areas (

Table 10. 7. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	-	Increase
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	-	Increase
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	28	Decrease
Water Surface	m2	30–35 m water surface	1–3 °C reduction	-	Increase
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	1.50–1.75 m	Decrease
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.07	Increase
Building Order	Adjacent	-	Stores heat	Adjacent	Increase
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	-
Average Building Height	m	<10 m 10–20 m	Increases 1 °C
		20–30 m >30 m	Increases 3 °C	21–21.4 m	Increase
Prevailing Wind Direction	SE	Parallel	Stores heat	-
		Upright	Disperses heat	NE	Increase
Structuring Condition		BCR	Stores heat	BCR: 0.50	Increase
		FAR	Disperses heat

). As a result of the analysis, the following points were discovered:

• Lack of parks/green areas;
• The cooling effect is not sufficient in terms of wooded area and number of trees;
• That there is no natural or artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• Albedo values remain in the range of 0.10–0.35 with reinforced concrete building material;
• The average building height/street-width ratio varies between 1.50 and 1.75;
• SVF value is 0.070;
• The construction type is adjoining order;
• The average building height varies between 21 and 24.5 m. and buildings with different heights are located opposite each other;
• The buildings are generally oriented northeast and perpendicular to the prevailing wind direction;
• BCR and FAR values are largely in line with the zoning plan, but the areas planned as commercial areas contain commercial + residential areas (Figure 11).

8. Texture: It includes villa type residential areas located in Pamukkale district, Zeytinköy neighborhood, Block 2722, Parcel 4 (

Table 11. 8. Texture result values.

Parameter	Unit	Reference Value	Effect on Temperature	Conclusion	Heat Island Effect
Park/Green Space	m2	1500 m2 park	1.5 °C reduction	550 m2	Decrease
Wooded Area	m2	100 m2 wooded area	1.5 °C reduction	1200 m2	Decrease
	unit	1 tree (10 m diameter)	1–1.5 °C reduction	-	Decrease
Water Surface	m2	30–35 m water surface	1–3 °C reduction	130 m2	Decrease
Road Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Pavement Material		Permeable/Impermeable	Disperses heat/ warehouses	Impermeable	Increase
Building Material	Albedo	0–1	Decreases as it approaches 1	0.10–0.35	Increase
Average BH/SW	m	0–0.5	Decreases as it approaches 0.5	0.75 m	Increase
Sky Vision Factor	SVF	0–1	Decreases as it approaches 1	0.122	Increase
Building Order	Adjacent	-	Stores heat	-	Increase
	Block	-	Stores heat	-
	Discrete	-	Disperses heat	-Discrete	Decrease
Average Building Height	m	<10 m 10–20 m	Increases 1 °C
		20–30 m >30 m	Increases 3 °C	7.5 m	Increase
Prevailing Wind Direction	SE	Parallel	Stores heat	-
		Upright	Disperses heat	NE	Increase
Structuring Condition		BCR	Stores heat	-
		FAR	Disperses heat	FAR: 0.80	Decrease

). As a result of the analysis, the following points were discovered:

• 550 m² parking area, where there are areas that will provide cooling effect in terms of wooded areas;
• There is an artificial water surface;
• The use of impermeable materials including hard materials on roads and sidewalks;
• Albedo values remain in the range of 0.10–0.35 with reinforced concrete building material;
• The average building height/street-width ratio is 0.75;
• The SVF value was 0.122;
• The type of construction is split-layout as villa type residences;
• The average building height is 7.5 m, but it has a decreasing effect on wind speed compared to the surrounding open spaces;
• The buildings are generally oriented northwest and parallel to the prevailing wind direction;
• It was determined that the BCR and FAR values are in compliance with the zoning plan to a great extent, but the lack of any construction in the vicinity increases the surface temperature (Figure 12).

4. Results

In this study, we aimed to examine the effect of different land use functions and settlement patterns on surface temperatures in the urban area. For this purpose, ground surface temperature maps were prepared from Landsat 8 OLI satellite images of 2012 and 2022 for Denizli city, and temperature changes were determined. According to the results obtained from the maps, high temperatures were found in areas with high urban density and in the direction of urban development. In the 10-year period analyzed within the scope of the analysis, the annual average temperature increase of the city was determined as 0.2 °C. This increase is thought to be related to the concentration of construction in the city center and the growth of the city by spreading.

Texture analyses conducted to examine the factors influencing urban heat island formation have determined that heat island formation in different textures is due to different factors. In this context, eight different textures selected from the texture analyses have direct or indirect effects on temperature formation. In this context, a comparison of heat island formation parameters was conducted across the eight textures examined (

Table 12. Comparison of texture analysis findings.

Parameter	Texture Analysis Results
	1	2	3	4	5	6	7	8
Park/Green Space	↑	↑	↑	↓	↑	↑	↑	↓
Wooded Area	↓	↓	↑	↑	↑	↓	↑	↓
Water Surface	↑	↑	↑	↓	↑	↑	↑	↓
Road Material	↑	↑	↑	↑	↑	↑	↑	↑
Pavement Material	↑	↑	↑	↑	↑	↑	↑	↑
Building Material	↑	↑	↑	↑	↑	↑↓	↑	↑
Average BH/SW	↑	↑	↓	↑	↑	↓	↑	↓
Sky Vision Factor	↑	↑	↑	↑	↑	↑	↑	↑
Building Order	↓	↓	↓	↓	↑	↓	↑	↓
Average Building Height	↑	↑	↑	↑↓	↑	↑	↑	↑
Prevailing Wind Direction	↑	↑	↑	↓	↓	↑	↓	↑
Structuring Condition	↓	↓	↓	↑	↑	↓	↑	↓

↑ Increases. ↓ Decreases.

). The results indicate that the maximum heat island effect is greatest in urban areas with low skylights and high impermeable surfaces. The urban heat island effect occurs due to numerous controllable and uncontrollable variables, and based on the results of texture analyses, it is clear that the effect levels vary in different textures.

The growth and development processes of cities are carried out by ignoring local climatic parameters in the plans made according to the zoning legislation. In this context, Article 8, paragraph 10 of the Spatial Plans Making Regulation paragraph (Amended: Official Gazette-7/6/2024-32569) was written: “If deemed necessary, urban risk analyses or disaster avoidance planning studies are carried out for settlements or built urban environment where natural disaster hazards such as earthquake, flood, mass movement (landslide, avalanche, rock fall, sinkhole and similar), tsunami, fire and similar natural disaster hazards and climate change-induced risks and other urban risks such as human-induced mass migration, industrial/chemical accidents and similar urban risks are high.” However, urban risk analysis due to climate change in cities is not considered as an obligation.

In the analysis conducted in urban textures where the ground surface temperatures are very high and high, evaluations were made in the context of the parameters related to the urban heat island. According to the results of the evaluation, it has been determined that there is a relationship between the type/layout of construction and the urban heat island effect; more precisely, in textures with low sky clearance, contiguous layout, average building height at medium and high values and high Building Coverage Ratio (BCR) and Floor Area Ratio (FAR) values, the construction conditions increase the urban heat island effect. In addition, it was determined that the heat island effect is high where the amount of green space is low and the amount of impermeable surface in road/sidewalk materials is high.

In the literature [4,5,6,7,25], it is seen that planning and design principles such as designing green infrastructures in the form of networks and corridors, increasing the diversity and density of existing green areas in urban centers, creating a cooling effect with green and wooded areas, providing a cooling effect by creating shade on building surfaces, etc., are recommended. In this context, suggestions for reducing the heat island effect in urban tissues with high surface temperature in Denizli city can be listed as follows.

In textures that include public housing areas,

• In urban development areas, preference should be given to split-layout settlements in order to make the most use of Denizli’s hot-humid climate air flow;
• Consider the cooling effect in open and green space planning in Bozburun and Aktepe Neighborhood mass housing areas where urban transformation projects are ongoing.

In textures containing industrial and warehousing areas,

• Determining a ratio in the plan notes within the scope of hard ground and wooded area in the industrial area located in Kayaköy and Bozburun Neighborhoods.
• The use of travertine, the local stone of the region, which has a permeable/porous structure, for flooring in open areas.

In the textures containing high-rise residential buildings/residences,

• Since the sunbathing direction of the city is in the east–west direction, the buildings should be located in this direction in an elongated form.
• Using light colors such as white with high reflectivity in accordance with Denizli climate on the facades of the buildings.

In the city center, in tissues containing contiguous residential areas,

• Designs to reduce the formation of urban heat islands (permeable ground, reflective materials, tree planting, etc.) to the extent permitted by the uses of the backyards of adjacent buildings with revision plans and transformations in the city center.
• Increasing the amount of wooded areas along the road in the gardens of residences and public institutions in Saraylar, İlbade, and Gültepe Neighborhoods.

In the historic fabric, including areas with commercial functions,

• Planning permeable infrastructure systems and increasing open and green areas in the areas between Kaleiçi, Bayramyeri and Hal.
• Use of permeable materials on the ground in Bayramyeri and Çınar squares.

In textures that include villa-type residential areas,

• Designing walking and pedestrian paths and seating/rest areas with landscape elements that will provide sun in winter and shade in summer;
• Creating green space connections between neighboring parcels, designing horizontal and vertical green facades.

With these suggestions developed, the current plans of Denizli city have been analyzed. In this context, the master zoning plan in force has a scale of 1/25,000 and includes the whole province and the expression “mitigation of disaster damages” is included in the planning principles and principles in the context of risks related to climate change. However, the objectives and strategies within the scope of the plan do not include any statement in this regard. In the plan decisions, under the title of Development of Open Space Uses, green areas are classified as passive, semi-active, and active according to their level of use, and no recommendations are made. The city’s implementation zoning plans are not holistic but are prepared in a fragmented manner on the basis of neighborhoods according to districts, and no decisions are made for the city as a whole. In this context, the plans, which are the continuation of the upper-scale plans, only include standards to meet the requirements of the legislation and do not include scale-based analyses. In the current plans, it is seen that an expansionist approach is followed in urban growth. As urban growth expands horizontally depending on the macroform of the city, the risk caused by temperature increases is likely to increase. When the plan decisions and analyses are analyzed in this context, it is seen that the studies are a continuation of the upper scale and do not include detailed studies related to climate change, and only the current climatic parameters are included.

In Denizli in 2019, “Denizli Climate Change Action Plan (2016–2030)” was prepared within the scope of the “Power to Change for Climate Action” project. In this context, the vision of the plan is defined as “Making Denizli a Low Carbon and Resilient City to Climate Change”. In order to achieve this vision, a participatory approach has been developed to determine greenhouse gas mitigation, adaptation, and risk actions. However, it is seen that the local government, which has an awareness of climate change with the prepared plan, is insufficient in terms of implementing the actions. These actions need to be integrated into spatial plans and include detailed studies on the basis of each possible risk in the city.

In this context, in the case of revising the current master and implementation zoning plans of Denizli city and in urban transformation projects, in determining the direction of development or urban macroform of the city, in plan decisions regarding transportation and green infrastructure, in landscaping of open-green areas, in creating construction conditions, in plan provisions/notes regarding garden, building facade, roof, floor material, etc., it should be taken into consideration that planning, design, and implementation decisions targeting urban cooling effect should be taken. While the relationship between “climate change and urban planning” in Turkey’s zoning legislation is deemed inadequate in many respects (such as definitions, research and analysis, principles and guidelines for planning, and urban social and technical infrastructure standards), numerous updates have been made with the amendment published in the Official Gazette dated 7 June 2024 and numbered 32569. However, there is currently no definition of climate change and urban mitigation–adaptation strategies. Risk analyses determined within this scope should be clearly linked to climatic changes, and any situations not mandated by the phrase “if applicable” should be included as mandatory. An “Open and Green Space Design Guide” should be created in master and implementation zoning plans, including specific details about urban green spaces. Mixed-use areas should be separated into different scales and detailed to the level of detail required by the scale.

Based on the research and analysis results examined within the scope of this study, it has been determined that the urban heat island affects cities to a greater or lesser extent. In this context, the need to analyze the urban heat island effect and the parameters that increase or decrease this effect within different urban fabrics emerges. Urban planning strategies must be developed to mitigate the negative impacts of the urban heat island, one of the greatest environmental problems causing climate change. However, inadequate planning and design cooperation and limited spatial measures constitute a significant shortcoming. Priority should be given to determining/limiting the direction of urban development. In urban planning, inadequacies in prioritizing the results of climate change risk analyses, land use location selection, and risk levels in determining residential density should be addressed. While this can initially be implemented through climate change-sensitive city managers and urban planners, it should be noted that it can only be implemented through the participation of all actors in the city and the cooperation and coordination of relevant municipal units and institutions.