Showing 5 results for Afifi
Dr Mohammad Ebrahim Afifi,
Volume 20, Issue 56 (3-2020)
Abstract
Land use maps are considered as the most important sources of information in natural resource management. The purpose of this research is to review, model, and predict landslide changes in the 30-year period by LCM model in Shiraz. In this research, TM Landsat 4, 5 and OLI Landsat 8 images were used for 1985, 2000 and 2015 respectively, as well as topographic maps and area coverage. Subsequent validation and detection of changes were made using the prediction model of variation The use of LCM markov and the model of user change approach. The images were classified into four classes of Bayer, garden, urban lands, and arable land for each of the three periods. According to the results, aquaculture is the most dynamic user in the area, which has led to an upward trend during 1985-2015, so that the amount (4337 ha, 12.7%) has been added to this area. The Bayer user change trend was also a downward trend during 1985 to 2015, reducing the 99.1995 hectares of this class. The results of the change in the 1985 changes with a kappa coefficient of 0.88, in the 2000 period with a CAAP of 0.77, and in the period 2015 with a Kappa coefficient of 0.92. The results of the change detection in 2030 are such that if the current trend continues in the region, 20.33% will be added to the crop category, so that in 2030, agricultural cropping will be 95.60% of the area of the area Gets In the Bayer and Garden uses 21.22% and 0.21% of the total area of each user has been reduced and has been added to the urban area. The prediction map derived from the Markov chain model is very important for providing a general view for better management of natural resources.
Sepideh Raeisi Qanavati, Marzieh Moghli, Mohammad Ebrahim Afifi,
Volume 23, Issue 71 (12-2023)
Abstract
With the increasing expansion of urbanization and the increase in the population of urban dwellers and the resulting problems, it is becoming increasingly necessary to provide facilities for the well-being of citizens. Today, the importance and role of urban furniture in urban service and beautification is not hidden from anyone, and urban furniture is one of the essential and inseparable components of cities. The purpose of this study is to investigate the role of urban furniture in improving the quality of urban environment, Bandar Abbas city, which has been done by descriptive-analytical method. Data collection has been done using two methods of library and field (questionnaire). The statistical population of this study consists of citizens of Bandar Abbas, 384 of whom were selected using Cochran's formula and research questionnaire by simple random method. Distributed among them. The research questionnaire was created by a researcher whose validity was confirmed by experts in a formal and superficial manner. And its reliability was confirmed using Cronbach's alpha coefficient. In order to achieve the objectives of the research, single-sample T-test and simple linear regression were used in SPSS25 software environment. The research findings showed that the urban furniture of Bandar Abbas is not in a good condition in terms of fitness and beauty, optimal distribution and citizens' satisfaction with the furniture of Bandar Abbas. The study of research hypotheses showed that urban furniture has a positive and significant effect on the quality of urban environment and its components, ie beautifying the environment, creating a suitable environment for social activities and increasing the vitality of the urban environment.
Dr Mohammad Ebrahim Afifi,
Volume 24, Issue 75 (12-2024)
Abstract
Among the natural hazards, without a doubt, the flood is known as a natural disaster. In this research, Shannon entropy model was used to prepare a flood sensitivity map. First, 34 flood watersheds were selected from Firoozabad basin, and then these 34 points were classified into two groups. With 22 points, 65 percent of the points for training and modeling, and 12 points, 35 percent of the locations that were not used in modeling were used for validation. First, a map of the status of the floods was developed and Then, 10 factors, slope, tilt, lithology, land use, NDVI, SPI, TWI, altitudes, rainfall and distances from the river were selected as flood factors in Firoozabad basin. Prioritizing the effective factors in the occurrence of flood by Shannon entropy index showed that the NDVI layers (2.03), rainfall (0.00), distance from the river (1.89), SPI (385.1), elevation classes (999 (0/19), gradient with weight (0,932), lithology (478/0), TWI (379/0), and land use (280/0), respectively (0/184) have the highest and the least impact Flood events. Based on the results of the ROC curve, the predicted surface area under the curve with 35% of the validation data is equal (91.42%) and for the success rate with 65% of the equal education data (92.53%).
Mr Milad Khayat, Ms Atefeh Bosak, Dr Zahra Hejazizadeh, Dr. Ebrahim Afifi,
Volume 25, Issue 76 (3-2025)
Abstract
By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.
Mr Milad Khayat, Ms Atefeh Bosak, Dr Zahra Hejazizadeh, Dr. Ebrahim Afifi,
Volume 25, Issue 76 (3-2025)
Abstract
By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.
