مجله کاربرد سیستم اطلاعات جغرافیایی و سنجش از دور در برنامه ریزی
سال سیزدهم شماره 3 (پیاپی 49، پاییز 1401)

The concept of citizen participation is not new, but nowadays there is a greater desire to use new participatory technologies with population-based or community-based strategies, such as location-based voluntary crowdsourced collaborative software (VGIS) in making cities smarter. This research is innovative in this sense. The purpose of this research is to know the effective factors in making smart using crowdsourced, voluntary, location-based technology (VGIS) from the point of view of experts and active researchers worldwide in the field of VGIS. The statistical population of this research is experts and researchers who have research records in the field of crowdsourcing technologies, voluntary geographic information system and citizen-oriented smart city. Using non-probability and purposeful sampling, 40 international experts formed the Delphi panel of the research. The current research is one of the applied researches based on its purpose and its method is descriptive-analytical according to the subject of the research and its nature. A mixed research approach has been chosen and among various types of mixed research designs, explanatory design and exploratory design have been chosen that are more suitable for these studies and exploratory factor analysis model has been used in the analysis of the results. The results of the research will help the researchers and executive officials of intelligentization in understanding the framework of the basic model in the use of crowdsourced, voluntary, location-based technology (VGIS). The exploratory model of this research includes 6 main factors of citizens, design, environmental and contextual conditions, cost, inherent and external quality of data and technical and infrastructure factors that should be considered in the design and use of technology (VGIS).

 The purpose of this research is to identify the components of the entrepreneurial ecosystem suitable for the growth of startups in the field of smart cities. The current research is applied in terms of the target or audience and descriptive-survey in terms of data collection. To identify the key factors in the development process of startups in the field of smart city, the library method is used, that is, the review of scientific articles and texts. And the field study will be used to distribute the questionnaire in order to prioritize these factors using the best-worst method. And finally, a formula is used to calculate the inconsistency rate in order to check the validity of the relevant comparisons. The statistical population of this research is business experts and managers of knowledge-based academic companies across the country, and Cochran's limited formula was used to calculate the sample size. From the number of 215 specialists with the fuzzy Delphi method and then knowledge-based companies, which number is 138. In this study, operations research techniques were used to analyze the data. ANP and DEMATEL fuzzy multi-criteria decision-making models have been used to determine the priority of research criteria and indicators. In order to perform the calculations related to the DEMATEL technique, Excel software environment was used, and the ANP technique was also performed using the Super Decision software. The components of the current research have been examined from four aspects. The results of this research show that, in the first place (optimal portfolio composition), the second place (utilizing the opinions of experts), the third place (allocation and granting of loans), the fourth place (directing loans and facilities towards production), the fifth place (bank arrears), 6th rank (human resource management), 7th rank (startup entrepreneurial ecosystem capital market) and 8th rank (creating liquidity).

According to the geological position and diversity of various events in the northwest of Iran, East Azarbaijan province has a high potential in relation to iron mineralization. The aim of the present study is to identify hematite and magnetite miSnerals in the study area, which includes a range between the cities of Tabriz, Shabestar, Haris and Warzghan. In this research, the multispectral data of OLI sensor of Landsat 8 satellite, ASTER sensor of TERRA satellite, Sentinel-2 satellite, as well as hyperspectral data of Hyperion sensor in order to monitor hematite and magnetite minerals and existing geological maps were used for validation. Is. In this study, in order to identify hematite and magnetite minerals, multi-spectral spectral data was used and to obtain data, data related to different time spectra of these sensors were used. For all obtained data, pre-processing operations, including Atmospheric and radiometric corrections have been done in the environment of ENVI5.3 software. The methods used in this research include index-based methods (band ratio operation) and spectrum-based methods (SID), MF, SFF, LSU). Considering the geological history of East Azarbaijan province, the results of these two methods represent The presence of two minerals, hematite and magnetite, was within the scope of the study, and the comparison of the results showed that the multi-spectral data of the ASTER sensor has a high ability to distinguish and identify the two studied minerals. Since the access to Hyperion hyperspectral data is limited and also covers a limited area compared to multi-spectral data, it can be concluded that ASTER data has more advantages and efficiency in mineralogical studies than other sources of spectral data

Following the increase in population and the growth of urbanization in recent decades, natural landscapes are being transformed into human landscapes and urban open spaces are being transformed into built-up areas. The purpose of this research is the changes made in urban constructions and the excessive increase of buildings and their relationship with the surface temperature of the earth using Landsat satellite from 2005 to 2020 for the new city of Sahand. The current research is applied in terms of purpose and descriptive-analytical in terms of method, and Global Human Settlement, Built-Up (GHSL) layers related to Landsat images of OLI/TIRS sensor in Google Earth Engine system have been used. The best results for the index of built-up complications were obtained with an accuracy rate of 79.97%, which was considered as the best method for extracting construction phenomena. While in 2010, it shows 45.32%, and the lowest rate of construction development is related to 2005, which showed 16.98%. The highest average air temperature for the LST image from 2010 to 2020 shows more than 16 degrees. In this year, the highest air temperature on the surface of the earth has coincided with the peripheral areas, built buildings and the northwestern parts of the new city of Sahand.

Border areas are considered as one of the most important security bottlenecks of any country. Continuous surveillance and monitoring of these areas is one of the main priorities of the border guard forces and one of the main components of ensuring the security of these areas. With the advancements in space and aerial imaging technologies, border monitoring operations have been done more quickly and accurately. Iran is known as one of the risky border countries due to the extent of border lines and the presence of numerous terrorist groups around its borders that identifying and eliminating these potential and actual risks requires intelligence elites regarding threatening events in these areas. Based on the needs of the border guards in order to identify the passage routes of criminals and terrorist groups, in this research, a method to detect and identify the tracks of vehicles using multi-time SAR images has been presented. First, the used images were modified in terms of the required pre-processing and the errors of SAR images, and in the next step, using phase information and the Coherence Change Detection (CCD) algorithm, the track of the vehicle was identified in the images. In order to evaluate the capability of the proposed method, the usual methods of detecting changes were also applied to the images. The results of the research show the high capability of the proposed method in identifying unauthorized border crossing corridors. The results of this research can be used as one of the components of security at the borders of the country.

Iran is one of the most earthquake-prone countries in the world and its cities have suffered a lot of damage due to this natural hazard. Knowing the areas exposed to these risks is one of the first steps in risk management and development and construction planning. In this research, the aim is the zoning of earthquake risk in Bestak city using the FUZZY-AHP model. The research method was descriptive-analytical. In the descriptive discussion, the necessary data were collected using library and documentary studies, and in the analytical discussion, fault maps, earthquakes, elevations, waterways and canals network maps, slope value maps, etc. were prepared, and then with the geographic information system ( GIS) each of the factors of the layers was valued and finally the final map was obtained by overlapping with the AHP model. Bestak city is one of the subordinate cities of Hormozgan province, located between the geographical coordinates of ˝00 21 ° 54 ° to ˝ 11 22 ° 54 longitude and ˝00 11 ° 27 to ˝02 12 ° 27 latitude is located. This map was proposed based on the geomorphological and land use conditions and the areas prone to urban development. The results showed that the physical development of the city during the past decades was subject to the topographical conditions and there are many geomorphological risks and limitations in the study area. According to the results of the research on the optimal location of city development, according to the experts, the parameter of gasoline pumps in the city center has the highest weight of 0.195 and the earthquake parameter has the lowest weight of 0.01 in a pairwise comparison. Finally, the final map resulting from the overlapping of all factors was obtained. According to the maps obtained by overlaying the AHP model and applying weights to the information layers, the earthquake vulnerability classes included very low, low, medium, high and very high. The area of the classes was 11.25, 9.53, 13.17, 15.69 and 9.58, respectively. A large area of the study area is at high risk; Therefore, solutions for crisis management should be implemented when necessary.