Investigation of the relationship between bioclimatic comfort and land use by using GIS and RS techniques in Trabzon

Analysis of the summer thermal comfort indices in İstanbul

Thermal indices and thermal comfort maps have great importance in developing health-minded climate action strategies and livable urban layouts. Especially in cities where vulnerability to heatwaves is high, it is necessary to detect the most appropriate indicators for the regional characteristics and action planning with respect to thermal comfort. The aim of the study is to examine thermal indices as indicators of regional climate characteristics by relating to meteorological parameters and spatial features. Atmospheric variables including air temperature, wind speed, cloud cover, and relative humidity data were obtained from 30 meteorological stations located in districts having different climatic features. Heat stress levels for apparent temperature (AT), heat index (HI), wet bulb globe temperature (WBGT), physiological equivalent temperature (PET), universal thermal climate index (UTCI), and perceived temperature (PT) indices were calculated and associated with meteorological parameters. Thermal comfort maps have been created with the daily mean and maximum values of all indices. As a result, the meteorological parameters with the strongest correlation with all thermal indices are air temperature (Ta) with r = 0.89 ± 0.01 and mean radiant temperature (Tmrt) with r = 0.75 ± 0.16. The differences in thermal stress levels over the city have been distinctively observed in the ATmax, PETmax, and PTmax maps, which are generated by the daily maximum values of the indices. Çatalca, where forests cover large areas compared to highly urbanized districts, has the lowest heat stress defined by all indices.

A two-branch cloud detection algorithm based on the fusion of a feature enhancement module and Gaussian mixture model

Accurate cloud detection is an important step to improve the utilization rate of remote sensing (RS). However, existing cloud detection algorithms have difficulty in identifying edge clouds and broken clouds. Therefore, based on the channel data of the Himawari-8 satellite, this work proposes a method that combines the feature enhancement module with the Gaussian mixture model (GMM). First, statistical analysis using the probability density functions (PDFs) of spectral data from clouds and underlying surface pixels was conducted, selecting cluster features suitable for daytime and nighttime. Then, in this work, the Laplacian operator is introduced to enhance the spectral features of cloud edges and broken clouds. Additionally, enhanced spectral features are input into the debugged GMM model for cloud detection. Validation against visual interpretation shows promising consistency, with the proposed algorithm outperforming other methods such as RF, KNN and GMM in accuracy metrics, demonstrating its potential for high-precision cloud detection in RS images.

Land suitability analysis of urban agriculture for different investment scenarios: Evidence from fuzhou of China

Urban agriculture provides a new strategic idea for solving the problem of urban food demand. The main objective of this study is to develop a spatial model for land suitability evaluation of urban agricultural development under different investment demands (urban agriculture 1.0 and 2.0), based on prospect theory and using GIS and TOPSIS analysis techniques. As a whole, we have developed a land suitability evaluation system for urban agricultural development under different investment needs (urban agriculture 1.0 and 2.0). We constructed a land suitability evaluation system for urban agriculture including ecological environment, social demand and investment cost. The results of the land suitability analysis for urban agriculture 1.0 show that the most suitable area is located in Changle. Compared with urban agriculture 1.0, the most suitable area for urban agriculture 2.0 is in Gulou. It is worth noting that Cangshan ranks second in both scenarios and can be used as a potential solution to balance the ecological environment, social demand and investment cost. Determining appropriate land suitability priorities for urban agriculture will facilitate future agricultural investment management and land use planning.

Evaluation of UTFVI index effect on climate change in terms of urbanization

Urban heat island density and occurrence are closely related to land use/land cover and land surface temperature variation. The effect of UHI can be described quantitatively with the urban thermal area variance index. This study aims to evaluate the UHI effect of the city of Samsun with the UTFVI index. LST data from 2000 ETM + and 2020 OLI/TIRS Landsat images were used to analyze UHI. The results showed that the UHI effect increased in Samsun's coastline band in 20 years. As a result of the field analysis made from the UTFVI maps created, in 20 years, 84% decrease in the none slice, 104% increase in the weak slice, 10% decrease in the middle slice, 15% decrease in the strong slice, 8% increase in the stronger slice, and 179% increase in the strongest slice are observed. The slice with the most intense increase is in the strongest slice and reveals the UHI effect.

A new method for estimating ore grade based on sample length weighting

Estimation of ore grade is very important for the value evaluation of ore deposits, and it directly affects the development of mineral resources. To improve the accuracy of the inverse distance weighting (IDW) method in ore grade estimation and reduce the smoothing effect of the IDW method in grade estimation, the weight calculation method involved in the IDW method was improved. The length parameter of the ore sample was used to calculate the weight of the IDW method. The length of the ore samples was used as a new factor of the weighting calculation. A new method of IDW integrated with sample length weighting (IDWW) was proposed. The grade estimation of Li, Al, and Fe in porcelain clay ore was used as a case study. A comparative protocol for grade estimation via the IDWW method was designed and implemented. The number of samples involved in the estimation, sample combination, sample grade distribution, and other factors affecting the grade estimation were considered in the experimental scheme. The grade estimation results of the IDWW and the IDW methods were used for comparative analysis of grades of the original and combined samples. The estimated results of the IDWW method were also compared with those of the IDW method. The deviation analysis of the estimated grade mainly included the minimum, maximum, mean, and coefficient of variation of the ore grade. The estimation effect of IDWW method was verified. The minimum deviations of the estimated grade of Li, Al, and Fe were between 9.129% and 59.554%. The maximum deviations were between 4.210 and 22.375%. The mean deviations were between - 1.068 and 7.187%. The deviations in the coefficient of variation were between 3.076 and 36.186%. The deviations in the maximum, minimum, mean, and coefficients of variation of the IDWW were consistent with those of the IDW, demonstrating the accuracy and stability of the IDWW method. The more the samples involved in the estimation, the greater the estimation deviations of IDW and IDWW methods. The estimated deviations of Li, Al, and Fe were affected by the shape of the grade distribution, when the same estimation parameters were used. The grade distribution pattern of the samples significantly influenced the grade estimation results. The IDWW method offers significant theoretical advantages and addresses the adverse effects of uneven sample lengths on the estimates. The IDWW method can effectively reduce the smoothing effect and improves the utilization efficiency of the original samples.

How can the floor area types of a university campus mitigate the increase of urban air temperature?

The urban heat island (UHI) under the current climate change scenario could have a major impact on the lives of urban residents. The presence of green areas undoubtedly mitigates the UHI, and modifies some selected anthropized surfaces with particular characteristics (e.g., albedo). Here, we use a university campus as a good template of the urban context to analyze the mitigation effect of different surface types on the air temperature warming. This study provides some of the best practices for the future management of land surface types in urban areas. Through the development of a simple air temperature mitigation index (ATMI) that uses the temperature, water content (WC), and albedo of the investigated surface types, we find the green and anthropized surfaces according to their areal distribution and mitigation effects. The findings address the importance of poorly managed green areas (few annual mowings) and anthropized materials that permit a good balance between water retention capacity and high albedo. In the case of impervious surfaces, priority should be given to light-colored materials with reduced pavement units (blocks or slabs) to reduce the UHI.

A geographic information systems and remote sensing-based approach to assess urban micro-climate change and its impact on human health in Bartin, Turkey

Increasing land surface temperature (LST) is one of the major urban climatology problems arising in urban development. In this paper, the impact of vegetation and built-up areas on the LST and impact of LST on human health are assessed using the Landsat thermal data in Bartin, Turkey. The results show that there is a constant change in the share of vegetation and built-up areas due to rapid urbanization in Bartin. Strong positive correlation has been found between NDBI and LST while strong negative correlation has been found between NDVI and LST, suggesting their strong impacts on land surface temperatures. Similarly, a strong positive correlation has been observed between LST, sleep deprivation, and heat stress. This study provides precise information on effects of urbanization and man-made activities, which cause major changes in micro-climate and human health in the city. This study can assist decision-makers or planners to plan future developments sustainably.

Determining the suitable settlement areas in Alanya with GIS-based site selection analyses

Urbanization, which is defined as an irreversible global-scale problem nowadays, necessitates the foundation of new settlement areas. In general, no sufficient scientific assessment and analysis were performed during these processes, and thus, various natural disasters cost the loss of many lives and properties every year. Nevertheless, considering the areas that are risky in terms of natural disasters during the selection of settlement areas might prevent a large-scale loss of lives and properties because of natural disasters. Within the scope of this study, it was aimed to determine suitable settlement areas in the Alanya district, which is one of the significant points of interest for tourists in our country and has a large population and new settlement areas because of this increasing population. Within this scope, besides the risks of flood and landslide that are the most important natural disasters in the region, and a forest fire that is among the most significant risks for the region, also the biocomfort zones were included in the assessments. As a result of the study, it was determined that the most important natural disaster risk was flooding in a large portion of the region and that only 6.72% of the study area was suitable for settlement in terms of all the criteria examined in the present study.

The change in biocomfort zones in the area of Muğla province in near future due to the global climate change scenarios

It is inevitable that the global climate change, which has important effects on the climate throughout the world, would have significant effects on the biocomfort zones. Hence, how global climate change will change the biocomfort zones should be determined and the data to be obtained should be used in urban planning projects. In the current study, SSPs 245 and SSPs 585 scenarios were taken as a basis, and the potential effects of global climate change on the biocomfort zones in Muğla province, Türkiye were investigated. Within the scope of the present study, the current status of biocomfort zones in Muğla and their possible conditions in years 2040, 2060, 2080, and 2100 were compared using DI and ETv methods. At the end of the study, it was estimated that, according DI method, 14.13% of Muğla province are in cold zone, 31.96% in cool zone, and 53.71% in comfortable zone. According to the SSPs 585 scenario, together with the increase in temperature, the cold and cool zones will totally disappear in year 2100, comfortable zones will decrease to 31.22%, and approx. 68.78% of the province will be in hot zone. According to the calculations made using ETv method, Muğla province currently consists of moderately cold zones by 2%, quite cold zones by 13.16%, slightly cold zones by 57.06%, and mild zones by 27.79%. Based on the SSPs 585 scenario for the year 2100, it is projected that Muğla will consist of slightly cool zones by 1.41%, mild zones by 14.42%, and comfortable zones by 68.06%, besides warm zones by 16.11% which are not present at this moment. This finding suggests that especially the cooling costs will increase and the air-conditioning systems to be used will negatively affect the global climate change through the energy consumption and the gases used.

The effects of climate on land use/cover: a case study in Turkey by using remote sensing data

Economic and industrial development results in worldwide population concentration in cities, leading to increases in impervious surfaces. Thus, the surface temperatures increase and cities are exposed to the urban heat island effect. This study analyzed the changes in the urban heat island effect in the 30 years (from 1990 to 2021) in the central district of Bartin. In this sense, there were two primary goals. Firstly, land use/land cover change, land surface temperature (LST), normalized difference built-up index (NDBI), and normalized difference vegetation index (NDVI) were analyzed by using remote sensing methods between 1990 and 2021. Secondly, a linear regression analysis was conducted to determine the factors associated with LST, NDVI, and NDBI. The study results revealed increases in urban surfaces and the average land surface temperature values in the past 30 years and showed a decline in the vegetation. Regression analysis results indicated a strong negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. It was also found a robust negative relationship between NDBI and NDVI. In light of the findings, it was stated that the amount of open and green areas should be increased in order to prevent the negative effects of the urban heat island in the central district of Bartin. For this purpose, it has been proposed to encourage green roof systems throughout the city, to create city parks and to create a green belt system. In addition, as a result of the study, the importance of preventing forest destruction caused by over settlement in the Mountains, which is one of the rare habitats of the world with different plant species, was emphasized. In this sense, legal sanctions should be employed to protect those areas and prevent construction.

Spatial distribution and temporal variation of biomass burning and surface black carbon concentrations during summer (2015‒2021) in India

Historical biomass burning in summer season (April‒June, during 2015‒2021) was assessed by studying active fire spot data recorded by the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard NASA/NOAA Suomi NPP satellite and mapping the same over Indian landmass. The fire spots often formed regional clusters and most profusely covered the states of Odisha, Chhattisgarh, Andhra Pradesh, Telengana, Madhya Pradesh, Maharashtra, Jharkhand, Karnataka, Punjab, Uttar Pradesh, Haryana, Gujarat, Tamil Nadu, Manipur, Nagaland, and Mizoram during April but their number decreased conspicuously in May and further in June. Forward movements of air masses potentially carrying fire-induced air pollutants from five principal fire cluster regions (northern, south eastern, western, north-eastern, and central) of India during April and May in 2021 were traced by 6-day forward airtrajectory modelling. It was observed that many parts of India were the recipients of air coming from the above principal fire clusters. In each year, the surface mass concentration of black carbon (BC), one of the most prominent markers of biomass burning, was higher in April over May and June in the affected regions, commensurate with the most active period of fire. The BC surface mass concentrations progressively declined thereafter in May and June with decreasing number of active fire spots along with declining average monthly height of the planetary boundary layer (PBL), indicating integral connection of surface BC levels with biomass burning. The study suggests that in spite of more favourable meteorological conditions in summer, extensive biomass burning may have had a crucial role to play in perturbing local and regional air quality over India by generating BC and other air pollutants.

Reconstruction and application of the temperature-vegetation-precipitation drought index in mainland China based on remote sensing datasets and a spatial distance model

In recent years, remote sensing drought monitoring indices have been gradually developed and have been widely used for global or regional drought monitoring due to their strong drought-monitoring capabilities and easy implementation advantages. However, some defects of remote sensing drought indices stand to be improved due to certain errors in the inversion of surface characteristics by remote sensing datasets. The temperature-vegetation-precipitation drought index (TVPDI) was taken as the research object, and the leaf area index (LAI), the difference between the land surface temperature (LST) and monthly average temperature, and Global Precipitation Measurement (GPM) precipitation data were selected instead of the normalized difference vegetation index (NDVI), LST and tropical rainfall measuring mission (TRMM) data to improve TVPDI. The improved remote sensing drought index was named the improved temperature-vegetation-precipitation drought index (iTVPDI). The drought-monitoring accuracy of iTVPDI was verified by the gross primary productivity (GPP), soil moisture, and crop yield per unit. The drought-monitoring ability of iTVPDI was verified with traditional drought indices, including the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI), temperature-vegetation drought index (TVDI), drought severity index (DSI) and crop water stress index (CWSI). The drought-monitoring accuracy of iTVPDI was verified by selecting sample areas. iTVPDI was applied to monitor drought in mainland China over the 2001-2020 period and obtained four main results. First, the correlation analyses of iTVPDI and TVPDI with GPP, crop yield per unit area, and soil moisture showed that iTVPDI had a stronger monitoring ability in Northeast, North, and Southwest China; the R² value obtained with soil moisture was 0.62 (p < 0.05), and this value was higher than that of TVPDI. Then, the correlation analyses of iTVPDI and TVPDI with SPI, SPEI, PDSI, CWSI, DSI and TVDI showed that the correlation coefficients of iTVPDI and TVPDI with these six indicators were basically consistent, which indicated that the drought-monitoring capability of iTVPDI was consistent with that of TVPDI. In local areas such as the Qinghai-Tibet Plateau in China, the monitoring ability of iTVPDI was stronger than that of TVPDI. Third, through the sample area analysis, iTVPDI was found to moderate the NDVI-characterized vegetation factors in TVPDI in low-vegetation-cover areas affected by soil disturbances and in high-vegetation-cover areas affected by oversaturation. Finally, the results obtained from the application of iTVPDI in mainland China showed that during the warm-dry to warm-wet climate transition between 2001 and 2021, in 2010 and 2018, and in other special drought years, iTVPDI had the best response.

The assessment of the thermal behavior of an urban park surface in a dense urban area for planning decisions

The new summer index (SSI) which was established to determine climate comfort was classified according to the index. Climatic comfort areas will increase and thus raising the quality of living in areas. The temperature values felt in the study were calculated with the SSI formula, and then the maps of the study area were classified. The study area was the Hayal Park and its surroundings in the Toros Quarter of Cukurova District, which is surrounded by multi-story and dense buildings in the north of Adana. Although the vertical construction is very high, it is richer in terms of green areas compared to other large central districts. Cukurova, which is one of the largest districts of Adana (according to population), has Seyhan dam lake in the north and Seyhan district in the south. The study area is on the border of Seyhan district and is adjacent to Yüreğir and Sarıçam districts. With the portable Smart SENSOR AS 847 measuring device, temperature and relative humidity were measured at 1.5 m above the ground on Tuesday, August 20 at 07.00, at 14.00, and 21.00. Bioclimatic comfort areas were determined by measuring temperature and relative humidity at 25 points with different textures in the study area. In this study, measured instantaneous temperature (°C) and relative humidity (%) data were transferred to GIS medium by ArcGIS 10.6 program and then modeled with the Kriging method, which is one of the interpolation methods, and temperature and relative humidity maps were created. The temperature map created in degrees Celsius (°C) by the Kriging method and was converted to Fahrenheit degrees (°F) in the Raster Calculator. The reason for this change is that SSI is calculated with the formula Fahrenheit (°F). These maps were then calculated on the Raster Calculator using the SSI formula, and sensed temperature values were obtained The SSI, which normally has 8 classes, has 3 classes in the study area. These classes are 83 ≤ SSI < 91 slightly hot, 91 ≤ SSI < 100 hot, and 100 ≤ SSI < 112 very hot. When we look at the maps, the places outside of Hayal Park are in the hot class at 07.00 in the morning, and we can see that the green spaces have a positive effect on the bioclimatic comfort areas. The small area is in a very hot class. When we look at 14.00 h, it is a totally hot class. Normally, the temperature is the highest of these times and also coincides with the multi-story buildings in the study area; asphalt and concrete areas increased the temperature. As a result, there is a very hot air in the study area. It was determined that the maps identified non-comfortable areas. Since urban form and settlement affect climate comfort values, the urban plan should be revised, and the area should be brought to the bioclimatic comfort value range. For reducing the effect of temperature in the working area and creating comfortable areas is increasing the density of green areas compared to asphalt and concrete areas. Considering that the Cukurova district will grow further, urban planning should be done very well to reach the comfort range in the following settlements.

Geostatistical surfaces of climatological normals of mean air temperature in Minas Gerais

Air temperature, a vital component for the terrestrial environment sustainability, can be used as an indicator and an important factor used in short- and long-term meteorological modeling at different scales. Temperature must be monitored on spatial and temporal scale with high precision. Terrain elevation can be used as the main influence factor depending on the measurement scale. In small and medium scales, factors related to local relief were modeled with geostatistics including external variables in temperature modeling. We aimed to evaluate the use of universal kriging in the modeling of air temperature in order to create temperature surfaces at each km[Formula: see text] in Minas Gerais State, Brazil using altitude, longitude and latitude covariates. The organized mean air temperature data of climatological normals of the National Institute of Meteorology were submitted to summary statistics, statistical regression and geostatistical analysis. Monthly and annual normals of the mean air temperature compensated for the period 1981 to 2010 were modeled using temperature as dependent variable and altitude, longitude and latitude as co-variables. Multiple regression modeling performed on temperature using altitude, longitude and latitude covariates determined significant parameters for monthly and annual mean air temperature global prediction. Relief and coordinates were used as external drift on variography and universal kriging with block for local temperature interpolation and prediction in order to generate 1-km moderate resolution surfaces of monthly and annual mean air temperature. Universal kriging determined smoothing effect of standard deviation of geospatial variation with prediction errors varying between 0.6 and [Formula: see text]C. Higher prediction error values were observed between June and August. Mean air temperature local prediction presented greater errors mainly in the lower altitude regions and in the colder months. In both monthly and annual temperature predictions, universal kriging with external drift enabled to circumvent the problem of performing spatial prediction from sparse punctual attribute data, conferring a temperature downscaling effect in Minas Gerais.

Impact of land cover transformation on urban heat islands in Harbin, China

At the local and regional climate scale, one of the most studied environmental issues is urban heat island (UHI). UHI is a thermal anomaly caused by temperature differences between urban and rural settings, which adds heat to the atmosphere and makes people feel uncomfortable. This study explores the influence of new land-cover data on UHI simulations using the high-resolution Weather Research and Forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM) in the city of Harbin. A comparison was performed between the new Tsinghua University (TU) land cover dataset with the default United States Geological Survey (USGS) and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover datasets. The results of this study revealed that the new TU land cover data had better representation and more realistic land cover changes than the default datasets. The diurnal, seasonal, and long-term nighttime UHIs of air and surface temperatures were higher than the daytime UHIs for both downtown Harbin and the satellite towns. We discovered that coal-burning during winter had a significant influence on UHI in Harbin. Moreover, the results from our buffer revealed a rapid increase in the UHIs of satellite towns, thus revealing the need to focus on the effects of UHI in satellite towns in the future. Therefore, the timely updating of land cover datasets in the WRF model and implementing mitigation strategies will help improve the urban climatic comfort.

GIS-based multicriteria decision analysis for settlement areas: a case study in Canik

In addition to global population growth due to migration from rural areas to urban areas, population density is constantly increasing in certain regions, thereby necessitating the introduction of new settlements in these regions. However, in the selection of settlement areas, no sufficient preliminary examinations have been conducted; consequently, various natural disasters may cause significant life and property losses. Herein, the most suitable settlement areas were determined using GIS (geographic information systems) in Canik District, where the population is continuously increasing. Therefore, this study aimed to incorporate a new perspective into studies on this subject. Within the scope of the study, landslide and flood risks, which are among the most important natural disasters in the region, were primarily evaluated, and high-risk areas were determined. Elevation, slope, aspect, curvature, lithology, topographic humidity index (TWI), and proximity to river parameters were used to produce flood susceptibility maps. A digital elevation model (DEM) of the study area was produced using contours on the 1/25,000 scaled topographic map. The elevation, slope, aspect, curvature, and TWI parameters were produced from the DEM using the relevant analysis routines of ArcGIS software. The raster map of each parameter was divided into 5 subclasses using the natural breaks classification method. In the reclassified raster maps, the most flood-sensitive or flood-prone subclasses were assigned a value of 5, and the least sensitive subclasses were assigned a value of 1. Then, the reclassified maps of the 7 parameters were collected using the "map algebra" function of ArcGIS 10.5 software, and the flood susceptibility index (FSI) map of the study area was obtained. The flood susceptibility map of the study area was obtained by dividing the FSI into 5 subclasses (very low, low, moderate, high, and very high) according to the natural breaks classification method. Thereafter, suitable and unsuitable areas in terms of biocomfort, which affects people's health, peace, comfort, and psychology and is significant in terms of energy efficiency, were determined. At the last stage of the study, the most suitable settlement areas that were suitable in terms of both biocomfort and low levels of landslide and flood risks were determined. The calculated proportion of such areas to the total study area was only 2.1%. Therefore, because these areas were insufficient for the establishment of new settlements, areas that had low landslide and flood risks but were unsuitable for biocomfort were secondarily determined; the ratio of these areas was calculated as 56.8%. The remaining areas were inconvenient for the establishment of settlements due to the risk of landslides and floods; the ratio of these areas was calculated as 41.1%. This study is exemplary in that the priority for the selection of settlement areas was specified, and this method can be applied for selecting new settlements for each region considering different criteria. Due to the risk of landslides or flooding in the study area, the areas unsuitable for establishing a settlement covered approximately 41.1% of the total study area. The areas that had low flood and landslide risks but were suitable for biocomfort constituted only 2.1% of the study area. In approximately 56.8% of the study area, the risk of landslides or floods was low, and these areas were unsuitable in terms of biocomfort. Therefore, these areas were secondarily preferred as settlement areas. The most suitable areas for settlements constituted only 0.19% of the total study area, and these areas will not be able to meet the increasing demand for settlement area. Therefore, it is recommended to select areas that do not have the risk of landslides and floods but are unsuitable for biocomfort. This study reveals that grading should be performed in the selection of settlement areas. When choosing a settlement area in any region, possible natural disasters in the region should be identified first, and these disasters should be ordered in terms of their threat potential. Moreover, biocomfort areas suitable for settlements should be considered. In the next stages of settlement area selection, the criteria that affect the peace and comfort of people, such as distance to pollution sources, distance to noise sources, and proximity to natural areas, should also be evaluated. Thus, a priority order should be created for the selection of settlement areas using various other criteria.

Climate suitability assessment on the Qinghai-Tibet Plateau

Climate is an important factor that affects livability, but the climate comfort model used for low altitudes is not applicable to high altitudes, and further study on climate suitability in high-altitude areas is needed. In response to the absence of high-altitude characteristics in the current climate comfort assessment methods, this study adds oxygen content and solar radiation as plateau characteristic indicators. We use the consulting graded method (CGM), least squares method (LSM) and questionnaire survey method (QSM) to obtain comprehensive weights for oxygen content, solar radiation and comfort index to build the Climate Suitability Index of Plateau (CSIP) and assess climate suitability on the Qinghai-Tibet Plateau. The CSIP decreases obviously as elevation increases from southeast to northwest on the Qinghai-Tibet Plateau, which means that the climate becomes increasingly unsuitable from southeast to northwest. The Qinghai-Tibet Plateau is divided into four regions-"very unsuitable" (83.8 × 10⁴ km², 32.4%), "unsuitable" (81.5 × 10⁴ km², 31.6%), "suitable" (67.9 × 10⁴ km², 26.3%), and "very suitable" (24.9 × 10⁴ km², 9.6%)-by the natural break method according to the CSIP. According to the different degrees of response of population density to CSIP, we plot the climate suitability line of the Qinghai-Tibet Plateau to provide basic theoretical support for regional planning in the Qinghai-Tibet region. The CSIP developed in this study provides a new climate suitability assessment method for high-altitude regions and a method for planning human activities on the Qinghai-Tibet Plateau from a climate-focused perspective.

An integrated approach of logistic-MCE-CA-Markov to predict the land use structure and their micro-spatial characteristics analysis in Wuhan metropolitan area, Central China

As human interference with the natural environment accelerates, land use has undergone great changes. However, to realize rational land development in the rural-urban ecotone, the micro-spatial (MS) unit is the best scale for the management and planning of sustainable land use. Taking Wuhan metropolitan area as research area, the integrated logistic-multi-criteria evaluation (MCE)-cellular automata (CA)-Markov model was used to simulate land use pattern for 2025. In addition, the 1 km×1 km, 2 km×2 km, 3 km×3 km, and 4 km×4 km and typical sample belt were built to reveal the spatial microcosmic expression of land use structure. The results showed that the kappa coefficient and figure of merit (FoM) were 88.01% and 26.86%, respectively, indicating the integration model has high prediction accuracy. In 2005-2025, the diversification of land use in the Wuhan metropolitan area will be generally above the medium level, and the types of land combinations will be relatively abundant. As human activities increase, the land use degree will show increases continuously, it will expand outward from Wuhan, and there is a positive correlation between cultivated land-rural residential land and urban land-cultivated land. The spatial distribution of land use structure presents regional scale characteristics, and different regions have micro-spatial scale dependence. The selection of MS scales based on local conditions can be a good way to reflect land use internal structure and provide a better reference for the compilation of regional land use optimization.

Possibilities of disposing silica fume and waste glass powder, which are environmental wastes, by using as a substitute for Portland cement

In this study, the possibilities of disposal of environmental waste, silica fume, and waste glass powder as substitutes in the mortar samples in Portland cement were investigated. For this purpose, Portland cement (CEM I), silica fume (SF), waste glass powder (WGP), CEN standard sand, and water were used in mortar production. Additive cements were obtained by using the SF, WGP, and SFWGP substitution methods in Portland cement at the rates of 10, 20, 30, and 40%. The flexural strength, compressive strength, radiation permeability (determination of linear absorption coefficient), high temperature, and alkali-silica reaction (ASR) effect on SF, WGP, and SFWGP were examined and compared with the control PC 42.5R samples. Mortar samples of 40 × 40 × 160 mm size were obtained with the grouts/mortars produced, and the samples were exposed to five temperature effects, namely, 20, 150, 300, 700, and 1000 ° C. Samples kept at 20 ° C are accepted as baseline. A total of 429 samples were studied, including the cooling process in the air (spontaneously in the laboratory, 20 ° C ± 2). After the samples achieved room temperature, flexural and compressive strength tests were carried out at 28 and 90 days. Test results demonstrate that SF, WGP, and SFWGP, which are environmental wastes, can be disposed both as a pozzolanic additive material both alone and together in cement mortars, can be utilized in buildings with high fire hazard, and the sample with the highest linear absorption coefficient is the sample obtained with SFWGP, and also, the expansion values ​​that occur in SF and WGP are less than the control sample.

Solar Climate Features Taking into Account the Morphometric Conditions of the Area and the Possibility of Using Them in Heliotherapy on the Example of the Cieplice and Kołobrzeg Health Resorts (Poland)

Global solar radiation is an important atmospheric stimulus affecting the human body and has been used in heliotherapy for years. In addition to environmental factors, the effectiveness of global solar radiation is increasingly influenced by human activity. This research was based on the use of heliographic and actinometric data (1996–2015) and the model distribution of global solar radiation to determine the possibility of heliotherapy with the example of two health resorts: Cieplice and Kołobrzeg (Poland). The solar features of health resorts (sunshine duration and global solar radiation) were characterized, and they were correlated with the spatial distribution of global solar radiation data obtained with the use of remote sensing techniques (System for Automated Geoscientific Analyzes-SAGA), including COoRdination and INformation on the Environment (CORINE) land cover (CLC) data. Using the maximum entropy model (MaxEnt), a qualitative and quantitative relationship between morphometric parameters and solar climate features was demonstrated for individual land cover types. Studies have shown that the period of late spring and summer, due to the climate’s solar features, is advisable for the use of heliotherapy. The human activity that determines the land cover is the main element influencing the spatial differentiation of the possibilities of using this form of health treatment. It also affects topographic indicators shown as significant in the MaxEnt predictive model. In general, areas with high openness were shown as predisposed for health treatment using global solar radiation, which is not consistent with areas commonly used for heliotherapy. The conducted research has shown the need for an interdisciplinary approach to the issue of heliotherapy, which will contribute to the optimization of the use of this form of health treatment from the perspective of climate change and human pressure.

Influence of climatic factor of changes in forest fire danger and fire season length in Turkey

In contrast to the expectations of an increase in annual fire activity and the severity of fire season due to climate change and large fires, which have been occurring in recent years, a downtrend has been identified in fire activity in many studies conducted for the whole of Europe in recent years. Similarly, in Turkey, according to the General Directorate of Forestry statistics, while there is an increase in the number of annual fires, the burnt area has a downtrend pattern. In this study, fire activity and climate data statistics for Turkey were examined along with the fire season length and severity. The results obtained conform with the studies conducted in places from Spain at the westernmost part of Mediterranean Europe to Israel at the easternmost part of the Mediterranean. Considering the changes in temperatures, temperature rise of 2 to 3 °C was detected at all stations in the study area. No decrease was observed in the average temperatures at any of the stations within the study period between 1940 and 2018. On the other hand, the precipitation trend varied according to the stations. Although there have been increases in precipitation in Fethiye, Isparta, and Marmaris since 1960, the decrease in precipitation by 132 mm in Afyon since 1970 and the decrease in precipitation by 137 mm in Bodrum since 1940 are attention-grabbing. These stations are followed by Izmir station with 66 mm and Cesme station with 37 mm of decrease, despite being smaller decreases. In the study, the long-term (1940-2018) data of the meteorological stations discussed within the study, the Canadian Fire Weather Index (FWI) and the Fine Fuel Moisture Code (FFMC) values were calculated. According to the FWI results used in determining the severity and length of fire season on the coastline of Turkey from the northern Aegean to Antalya, the likelihood of large fires decreased by about 52% in 2018 compared to 1970. This decrease in FWI value indicates that the fire severity is reduced. The specified decrease in fire severity also explains the reason of the decrease in the burnt area that occurred over the years in Turkey. No significant change was observed in the FFMC values indicating the possibility of human-induced fires between 1970 and 2018.

Site selection by using the multi-criteria technique-a case study of Bafra, Turkey

Population growth, which is the main source of the biggest problems of the world today, combined with migration from rural areas to urban centers, causes the urban centers to be even more concentrated. This necessitates the opening of new residential areas in many city centers, but new residential areas are mostly determined by the decisions of local authorities, who may not base their decisions on scientific data. With the wrong area selection, ordinary natural events can be potentially catastrophic. Such events can result in large numbers of casualties and material damage every year. In this study, an example of applying a method for location selection using various parameters has been realized. The study focuses on Bafra, Turkey (the study area). Risk maps were created in terms of floods and overflows; maps of regions and high-voltage power transmission lines that enjoy a protected area status; and maps of regions in terms of biocomfort suitability. As a result of the evaluation made according to these criteria, it is calculated that only 1.96% of the total working area is suitable for use as a residential area. In relevant literature studies, it was observed that the studies related to the selection of residential areas were carried out only depending on a single standard or criterion. Some suggested biocomfort, and others used vulnerability to risks such as landslide, flood, and earthquakes as their main principle. Studies based on multi-criteria were generally used for purposes such as solid waste site selection and determination of the road routes. The study aims to shed light on the multi-criteria method in an attempt to standardize it in regional planning studies and to inspire similar studies in which different criteria can be used to achieve the maximum efficiency.