Mehdi Asghari, Zeinab Karkehbadi, Abbas Arghan,
Volume 0, Issue 0 (3-1921)
Abstract
. All the interested and influential forces are in the administration of the cities and also respond to all the needs of these groups. On the other hand, women, as one of the main and most influential groups and social forces in the civil life of cities, today have a prominent role in the categories related to city administration. Therefore, the purpose of this article is the role of good urban governance in the corona and post-corona period, considering the position of women in Semnan. From the point of view of the goal, the present research is practical and according to the method of data collection, it is descriptive-survey. A questionnaire was used to collect the data and information of this research. The statistical population of the current research is the citizens of Semnan with a population of 185,129 people, and the sample size is calculated using Cochran's formula to be equal to 383 people. To analyze the data, single-sample t-tests and multivariate linear regression were used, and finally, to generalize the results from the sample to the statistical population, the structural equation modeling method was used by Lisrel software. The results of the one-sample t-test have shown that the t-values for each of the research variables with averages lower than the theoretical mean have been obtained as a negative number, which has determined the state of the dimensions of good urban governance in the city. Semnan and the position of women in it is not in a good position. Also, the results of structural equations in Lisrel software have shown that the justice variable has the highest and strongest relationship with good urban governance. Finally, the results of the surveys show; It is not possible to hope for the realization of good urban governance without defining and explaining the practical role of women as half of the city's citizens and one of the most important and influential groups in the administration of city affairs.
Sayed Hedayat Sheikh Ghaderi, Abdulsalam aminpour, Parviz Ziaeian Firoozabadi,
Volume 24, Issue 72 (6-2024)
Abstract
Corona and Hexagon satellite photographs with a spatial resolution of 1.8 to 9 meters are a good source for monitoring and evaluating changes in surface phenomena. The purpose of this study is to monitor the changes in Zaribar Lake in the period 1969-2019 using the data of Corona, Hexagon and Aster satellites and their ability to monitor and extract the coastline, lake boundary and water surface. In this study, to geometric correction the corona and hexagon data from Google Earth images, linear extraction algorithms, binary mask and mean shift segmentation were used to extract the coastline and lake boundary, detect lake changes and extract and monitor the water area of Zaribar Lake. The results showed that in the first step: geometric correction of corona and hexagon images was obtained using Google Earth images with RMSE of 0.3 and 0.4 pixels. In the second stage, the linear extraction algorithm for extracting the lake boundary and coastline using corona and hexagon photographs has high accuracy and has a high correlation with the topographic map of 1.50000. In the third step, the unsupervised classification of binary mask method, in order to detect lake changes using corona and hexagon photographs, acceptablely identified the altered and unchanged pixels, so that 11 hectares of lake surface had the most changes. Finally, in the fourth step, it was found that the mean shift segmentation algorithm and threshold worked better by applying the corona, hexagon, and Aster events to extract the water surface, and in the meantime, the corona image performed better due to its higher resolution. The above results showed that Zaribar Lake decreased by 6.5% from 1969 to 2019 and the findings have a high correlation with the product of the ester aquifer. In general, the findings of this study show the potential of using digital image processing methods for corona and hexagon data to monitor and detect changes in lakes.
