TY - JOUR A1 - Dizbadi, Mehran A1 - Safarzadeh, Daniyal A1 - Arastoo, Behrooz A1 - Brunn, Ansgar T1 - Predicting the Areal Development of the City of Mashhad with the Automaton Fuzzy Cell Method JF - World Academy of Science, Engineering and Technology, International Journal of Civil and Architectural Engineering N2 - Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model and perceptron neural network method with satellite data developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done. In finally our accuracy has been better compared to other researches that have been done in this field and we have slightly improved and optimize the final results approximately %92.1. KW - Urban Modeling KW - sustainable development KW - Fuzzy Cellular Automaton KW - Geo-Information System KW - Perceptron neural network KW - Landsat Y1 - 2022 UR - https://www.researchgate.net/publication/363484716_Predicting_the_areal_development_of_the_city_of_Mashhad_with_the_automaton_fuzzy_cell_method/stats VL - 16 IS - 6 ER - TY - JOUR A1 - Dizbadi, Mehran A1 - Arastoo, Behrooz A1 - Toth, Charles A1 - Brunn, Ansgar T1 - Automatic Extraction of Buildings Boundaries Using Satellite Imagery with High Spatial Resolution and Deep Learning Methods JF - FIG-Congress 2023 Y1 - 2023 CY - Orlando (USA) ER - TY - CHAP A1 - Dizbadi, Mehran A1 - Taghipour, Majid A1 - Arastoo, Behrooz A1 - Brunn, Ansgar ED - Ksibi, Prof. Mohamed T1 - Land-use changes in coastal areas of Using Multi-Time satellite data T2 - Euro-Mediterranean Journal for Environmental Integration University of Sfax, Tunisia N2 - The use of coastal lands is constantly changing due to the regression and progress of water 10 areas. This coastal Land use changes the need for continuous monitoring at regular intervals to 11 efficiently manage coastal resources. In this study, the effect of Gorgan gulf ( is location in the 12 southeastern part of the Caspian Sea in Golestan province of IRAN country ) progress and re-13 gression on land-use change in the surrounding lands has been modeled and estimated using 14 remote sensing images. For this purpose, two satellite images of Landsat 5 and Sentinel 2 were 15 taken in 1992 and 2017, respectively, and after preparing and applying the necessary prepro-16 cessing, the most similar classification and land uses of the study area were extracted. Overall 17 accuracy values of 0.94 and kappa coefficient of 0.92 indicated the appropriate accuracy of land 18 use maps. The classified images and the topographic maps, and the network of passages of the 19 study area were designated as land modeling inputs to detect land-use changes over 25 years. The 20 study results showed that the water area of the Gorgan gulf had faced a water level decline of 21 150 square kilometers, which has led to an increase in the area of wastelands. Also, agriculture 22 and garden, and rangelands have been significantly reduced during the study period 23 Keywords: Change Detection, Landsat 5, Sentinel 2, Remote Sensing, Gorgan gulf Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-44800 ER -