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. 

In recent decades, good urban governance has been proposed as the most effective, least expensive, and most sustainable method for managing the complex and multi-level systems of modern cities. The centrality of this approach in urban management is based on democratic and egalitarian development, aiming to involve all interested and influential stakeholders in the administration of cities while addressing their diverse needs. On the other hand, women, as one of the main and most influential social groups in urban life, play a prominent role in city administration. Therefore, the purpose of this article is to examine the role of good urban governance during and after the COVID-19 pandemic, with a focus on the women’s status in Semnan. From the perspective of its objective, this research is practical, and in terms of data collection, it is descriptive-survey. A questionnaire was used to collect data and information for this study. The statistical population of the research consists of the citizens of Semnan, with a population of 185,129 people. The sample size was calculated using Cochran's formula, resulting in 383 participants. To analyze the data, single-sample t-tests and multivariate linear regression were employed. Finally, to generalize the results from the sample to the statistical population, structural equation modeling was conducted using Lisrel software. The results of the one-sample t-test showed that the t-values for each of the research variables, with averages lower than the theoretical mean, were negative. This indicates that the dimensions of good urban governance in Semnan, as well as the situation of women in the city, are not in a favorable state. Additionally, the results of structural equation modeling in Lisrel software revealed that the justice variable has the strongest and most significant relationship with good urban governance. Finally, the survey results demonstrate that it is impossible to achieve good urban governance without defining and explaining the practical role of women, who represent half of the city's population and are one of the most important and influential groups in city administration.