نشریه جغرافیا و برنامه ریزی محیطی
سال سی و چهارم شماره 3 (پیاپی 91، پاییز 1402)

The most important aspect of nature-oriented tourists’ behaviors is paying attention to environmental sustainability. Much environmental research in the field of tourism has focused on the roles of values, attitudes, beliefs, and norms in shaping environmental behavior. In this study, according to the theory adopted by the majority of psychologists concerning the effect of attitude on behavior, it was used as an intermediate variable for explaining the relationship between knowledge and tourists’ environmental behaviors in the tourist areas of Tehran. This research was applied in terms of purpose and a descriptive survey in terms of data collection method. To conduct it, a researcher-made questionnaire with 75 variables was prepared and adjusted. Its reliability was confirmed by a Cronbach's alpha of 0.939 and its validity was formally confirmed. The statistical population included the tourists referring to 5 mountain tourism areas of Tehran. To estimate the sample size of 302 people from an unknown community, Cochran's formula was used. The study area included 5 mountain tourism areas of Tehran. Structural equation modeling was used to analyze the data. The analytical results of the behavioral models of the nature-oriented tourists showed a positive and significant relationship between attitude and environmental behavior and also between attitude and environmental knowledge with the factor loads of 0.68 and 0.82 at the significant level of less than 0.05, respectively. Also, the tourists’ environmental behaviors were studied based on their educational levels. According to the results, the tourists’ environmental behaviors depended on their levels of education. Thus, it could be stated that the existence of a cognitive analysis system called “tourist environmental knowledge” in combination with an emotional system would lead to the formation of their environmental attitudes, which could act as a basis for improving and optimizing their behaviors in the tourism destinations.

The city is considered a source of development, and the position of urban management plays a very important and decisive role in the process of urban development. One of the most successful models in the field of urban management is the model of urban governance, which is actually a management system in a participatory form, which consists of three institutions. Civil society, the private sector, and the government participate in all relevant decision-making. This research is descriptive in terms of its practical purpose and in terms of data collection. To collect data, according to experts, targeted sampling and snowball methods were used. Based on the findings, the accountability index has the highest impact on other indicators and the accountability index has the highest impact on other indicators. After accountability and responsibility and at a very close distance, the factors of effectiveness and efficiency are important for urban governance indicators. Based on the data of the D-R column, the rule of law index is one of the other antecedents in cause and effect relationships. On the other hand, other factors have an effective outcome, among which the specialization index is at the top. In this way, it can be concluded that accountability and responsibility indicators are closely related and are considered the most fundamental factor in the system of good governance indicators, and making constructive changes in it can lead to more serious and effective changes in improving urban governance.

Networking aims to define the principles and regulatory relationships between elements and optimize the performance of urban subsystems. Urban green networks support ecological functions and services that can help planning for the future of cities. The purpose of this research was to explain a conceptual model for the urban green network from the perspective of science according to the various perceptions of the concept of urban green network based on different scientific points of view by inferring and extracting the most important dimensions, approaches, and attitudes related to this field. By using the qualitative method and analyzing the written documents through the same lexical analysis, this research inferred and evaluated different points of view. The information was analyzed using the LCA analysis tool and SPAD software was used to analyze the relationships among the collected information by examining the effective environmental sciences. Using the VOSviewer software, the most important dimensions, approaches, and attitudes were determined. The findings of this research showed that the concept of the urban green network was directly related to the three environmental sciences of urban studies, urban geography, and ecological sciences. These sciences had a significant impact on the formation of a conceptual model to provide a clear picture of this concept in line with urban green infrastructure planning. Urban studies deal with concepts, such as protecting green spaces in cities, creating new spatial forms, etc., in urban geography, paying attention to the ecological principles in cities, meeting the ecological needs of nature and humans, etc., as the effective concepts. Ecological sciences are also mentioned as the most important research fields regarding the concept of urban green network to promote continuity in urban green spaces, create and design optimal corridors, etc. The results of this study showed that the concept of urban green network was a multi-research field. It appeared as a field supported by the urban planning method by means of decision-making tools, capable of modeling green infrastructure as an urban network formed from natural and semi-natural areas and was in line with the distribution of public services to increase the quality of life, as well as providing ecosystem services and sustainability in cities.

The present study analyzed changes in land use and its effects on the runoff of Qara Chai Watershed in Hamadan Province using the SWAT model. To this aim, Landsat OLI-TM satellite images of the years of 2001-2020 were used. First, the relevant images were obtained and the necessary pre-processing steps, including atmospheric corrections, were applied by using the FLAASH method. To increase the classification accuracy, the multispectral images were combined with the panchromatic images and the spatial resolution was enhanced up to 15 m. Then, the classification process was done by using the object-oriented method and the nearest neighbor algorithm. The SWAT model was utilized for hydrological simulation of the basin and SUFI-2 algorithm was applied in SWAT-CUP software for conducting sensitivity analysis, calibration, and validation. Due to the sensitivity of the model to the initial loss parameter, it was recalibrated based on the initial loss values. The values ​​of the coefficients for the calibration period were between 0.72 and 0.90 and the model validation results confirmed the calibration accuracy. Assessment of the efficiency of the model by using Nash Sutcliffe coefficients, p-factor, R, and r-factor indicated its high capability for simulating the related runoff.

Sustainability in the field of pavements is one of the subsets of sustainability topics in sustainable development. In the upcoming research, various supervised and object-oriented methods and fusions of satellite and drone images by using the Gram-Schmidt algorithm were used to investigate asphalt damage, including asphalt cracking and wear, in order to provide the best method for investigation. The results showed that the supervised methods of support vector machine with a kappa coefficient of 87% and overall accuracy of 90% provided the best and shortest distance method with the kappa coefficient and overall accuracy of 57% and 67%, respectively, while showing the lowest accuracy in the classification of supervised methods. Also, among the object-oriented methods, the support vector machine algorithm with a kappa coefficient of 86% and an overall accuracy of 91% had a more accurate output compared to the other studied algorithms. The lowest accuracy was related to the nearest neighbor algorithm with a kappa coefficient of 78% and an overall accuracy of 80%. In the UAV fusion output with Sentinel-2, the classification was done by using the most optimal algorithm and the support vector machine in the object-oriented method. The results showed an increase in classification accuracy up to the kappa coefficient of 91% and overall accuracy of 93%. Furthermore, the thresholding method with a Kappa coefficient of 90% showed the best result for detecting asphalt wear.

Urban heat islands could have destructive effects on the environment and increase energy consumption. The present study aimed to investigate the spatial autocorrelation of land surface temperature and its relationship with land use in Ahvaz city. Daily and Night Land surface temperature maps were extracted from the split window method for the Landsat 8 satellite image and MOD11A1 product, respectively. Land use maps of the study were extracted into five classes: Built-up area, vegetation, bare land, water, and Karun River. Based on the results, Global Moran's index on day and night was equal to 0.94 and 0.9, respectively, according to which Land Surface temperature is distributed in a cluster form. Results of Getis-ord GI statistics showed that the largest area of daily and nightly hot spots in the east of Ahvaz was obtained with 5050.53 and 8055.69 ha, respectively. The results of the Kruskal Wallis test showed that there was a statistically significant difference between the average temperature of land uses (p-value<0.05), so industrial areas and bare land had the highest temperature and the water bodies and vegetation had the lowest temperature. The results also showed that LST has a negative relationship with NDVI (r = -0.47); however, the average NDVI index in the study area was equal to 0.17 which indicated the poor quality of vegetation in Ahvaz. Therefore, it is necessary to take measures to improve the quality of vegetation and expand the urban green space and preserve water resources to adjust the land surface temperature in Ahvaz.