Urban Planning
Abolfazl Ghanbari; Mir Hossein Pourbagher
Abstract
In this study, using images of Landsat-8, Landsat-7 and Sentinel-2 satellites in the coding environment of Google Earth Engine, their uses and changes during the two periods before and after urbanization (from 2000 to 2008 and from 2008 to 2019) will be categorized and then the next five-year development ...
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In this study, using images of Landsat-8, Landsat-7 and Sentinel-2 satellites in the coding environment of Google Earth Engine, their uses and changes during the two periods before and after urbanization (from 2000 to 2008 and from 2008 to 2019) will be categorized and then the next five-year development forecast of Sahand city (until 2025) will be made. Perceptron multilayer artificial neural network (MLP) method has been used as a method for predicting spatial multi-criteria decision making (MCDM). The independent variables used in the present study in predicting the physical development of the city are land price, type of use, slope, slope direction, altitude, distance from urban areas, distance from waterway network, distance from fault, distance from network Passages (main and secondary). The results of classification of satellite images showed that the physical development of Sahand new city has been done in order to turn barren lands into urban land. In addition, physical development was built to turn cheaper land into areas. The built lands have been greatly developed and from 64,155 square meters in 2000 to 682,192 square meters in 2019. Among the image classification methods for land use extraction, the SVM method was the best method and also the Sentinel-2 satellite images had the highest accuracy. The multilayer perceptron artificial neural network was used to predict the future physical development of the new city of Sahand, which according to studies, the development is predicted in directions that are based on the cheapness of the land and the limitations. Geomorphological is like slope and altitude.
Geomorphology
Mohammad Hossein Rezaei Moghaddam; Masoumeh Rajabi; Masumeh Mousavi
Abstract
r optimal land use, it is necessary to be aware of land use changes and the type of land use; this is possible by assessing and predicting land use changes. The purpose of this study is to investigate the trend of land use change over a period of 18 years (2000-2000) and predict it using the Markov chain ...
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r optimal land use, it is necessary to be aware of land use changes and the type of land use; this is possible by assessing and predicting land use changes. The purpose of this study is to investigate the trend of land use change over a period of 18 years (2000-2000) and predict it using the Markov chain model for 2025, 2050 in the Yellow River Basin of Baghmalek city in Khuzestan province. To achieve this goal, first corrections (geometric, radiometric and atmospheric) and necessary processing were performed on Landsat satellite images of 2000, 2006, 2012, 2018; Then, land use maps for four time periods were classified into five classes: green space and gardens, barren lands, agricultural lands, water levels (sedgereh) and man-made residential areas. These changes were addressed using the Markov chain model for 2025, 2050. After making the necessary corrections on the Landsat images, the land use estimate showed that the highest percentage of the study area is barren lands and arable lands. The overall accuracy and kappa coefficient for 2000, 2006 and 2018 are above 0.80 and 0.92. .. The results of revealing the changes between the period 2000 to 2018 showed that barren lands with a rate of 823.51, green space and gardens with a decrease of 157.85 hectares. In contrast to the built-up areas of 439.59 hectares, 1356.56 hectares of arable lands and 404.94 hectares of water levels have been facing an increasing trend. Also, the results of the forecast using the CA-Markov model of land changes in the region for 2025 and 2050 showed that if the speed of land use change is the same as in previous years, in 2025 the use of built-up areas will be 1089.54, hectares of arable land. To 1154/52 hectares and surface water use will increase to 666/54; Landscaping and orchards will be reduced to 42/2012, barren land land use to 59,85279 hectares and in 2050 landscaping and orchards land use to be reduced to 192.62 hectares, barren land land use to be reduced to 8438.69 hectares, arable land land use Increase to 1243.73 hectares and surface water use increase to 8959.59 hectares of built-up areas to 1671/98 hectares. By examining land use change, valuable information can be obtained about man-made changes and natural factors. On the other hand, the prediction map derived from the Markov chain model is very important to provide an overview for better management of natural resources.
Climatology
Soodabheh Namdari; Ali Hajibaglou; GholamReza Abazari
Abstract
IntroductionAtmospheric mineral dust particles play a key role in the radiation budget of the atmosphere and the hydrological cycle, and have an important effect on public health by disrupting climate systems and air pollution. Due to Iran’s location in the arid and semi-arid belt of the world, ...
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IntroductionAtmospheric mineral dust particles play a key role in the radiation budget of the atmosphere and the hydrological cycle, and have an important effect on public health by disrupting climate systems and air pollution. Due to Iran’s location in the arid and semi-arid belt of the world, Iran is constantly exposed to local and regional dust systems. Considering the importance of the negative effects of dust storms and their increasing trend in some dust sources, the study of these changes in the last two decades show the importance of the dust storms in recent years. Moreover, spatial-temporal identification and analysis of the properties of these dust particles is very important in order to manage this crisis and prevent the harmful effects of dust particles. In Iran, due to desert conditions, the presence of dust hotspots has always caused air pollution and reduced the quality of life of people. In recent years, some dust hotspots have been ambiguous about increasing the intensity of dust emission. In this study, using the AOD product of MODIS, which compute the dust intensity, and based on the annual frequency and averages of dusty days, the location of dust hotspots were identified and then the trend of dust intensity in each hotspots were examine. The results showed that despite the relatively similar climate, the trend of changes in these dust hotspots does not follow the same pattern and complex human activities and natural changes.Data and Method In this study AOD product from MODIS with the resolution of 10 km was used to extract dust information then the frequencies of days with AOD greater than 0.6 per year were extracted. In addition to correctly calculating the average of AODs, calculating the number of days without data is also important in the results. The spatial and temporal distribution of the study period, were identified in three periods, 2000-2006, 2007-2012 and 2013-2018. The percentage of changes in each of the dust sources compared in different periods. The standard deviation was extracted to identify the areas most vulnerable to dust storms. Finally, to detect the quantitative distribution, the trend of AOD changes in the extracted dust hotspots was used to investigate the changes in the dust intensity trends.Results and DiscussionThe map of dust hotspots in the first period shows the main dust sources are in the north of Sistan and Baluchestan (Zabol) and south of Sistan and Baluchestan (Chahbahar), in the southeast of Semnan (Dasht Kavir), Damghan, Garmsar, Jazmourian, southwest of Hormozgan, (Bandar Lengeh area), south and southwest of Khuzestan, southwest of Yazd (Nayer), as well as parts of Qom, Ilam (Mehran), Isfahan, and south of Fars provinces. In the second period of study, many dust centers have become more intense and extensive. According to the map of dust centers in the third period of studies, compared to the first and second periods, the area of dust centers has decreased.According to the results, about half of the areas without emission has been turned into areas with dust with different frequencies in second period, and also about half of the area of very high-frequency hotspots has been turned into other dust sources with less intensity in the third period. Also, the most fluctuations in dust intensity have occurred in Sistan, Jazmorian, southeast of Semnan, East Azerbaijan, Zanjan and Khuzestan provinces. The results of trend analysis of dust intensity in different dust hotspots show that despite the relatively uniform climate, the dust sources trends in different dust sources do not follow the same pattern.ConclusionDue to the geographical location of Iran and the existence of vast deserts, the wethear has always affected by dust sources of inside and outside of the country. In this study, using satellite data with appropriate resolution, the location of dust sources in three time periods were extracted. The changes of each dust intensity class in the second and third periods were compared with the first period so that regardless of location, changes in dust intensity can be evaluated in general. Then, using the standard deviation method, the dust hotspots with the highest percentage of changes were identified. Finally, the trend of changes was calculated by examining the trends of changes in 24 main dust centers. According to the results of the present study, many changes have been observed in some dust sources and the intensity of dust in many dust sources has decreased. While some sources such as Isfahan, and Khuzestan province due to the role of human factors such as agricultural activities as well as the reduction of surface and ground water and as a result of drought and changes in soil texture have an increasing in trend of dust intensity. Since a decreasing trend is observed in most of dust sources, eastern and southern parts of Iran, the results of this study indicate the key role of climatic factors in changes and fluctuations in dust emission in Iran. Because climatic factor can be the only factor which has a relatively uniform effect on the dust emission on a large scale of Iran.
Urban Planning
Akbar Rahimi
Abstract
Introduction In recent decades, research on land use/land cover change has become an important aspect of global change, or global warming studies, since land use/land cover change is a major factor for global change because of its interactions with climate, ecosystem processes, biogeochemical cycles, ...
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Introduction In recent decades, research on land use/land cover change has become an important aspect of global change, or global warming studies, since land use/land cover change is a major factor for global change because of its interactions with climate, ecosystem processes, biogeochemical cycles, biodiversity, and, even more important, human activities. Dynamic urban change processes, especially the tremendous worldwide expansion of urban population and urbanized area, affect natural and human systems at all geographic scales. Todays, the rapid growth of urban areas has led to complex problems, including traffic congestion, environmental pollution, reduced open space, the deterioration of old downtown centers, and unplanned or poorly planned land development. Urbanization both in population and spatial extent, transforms the landscape from the natural cover types to impervious urban lands. This phenomenon is one of the most important factors that changes land surface leading to modification of receiving environments which are usually composed of natural cover. Rapid urbanization in recent decades and land use changes in urban periphery especially in big cities are the fundamental challenges of sustainable development in the world. Increasing of urbanization tendency and rural – urban migration, unsuitable management of urban development caused that the green spaces and gardens in urban periphery and in inner areas changed to urban profitable land use and especially residential areas. In this research urban expansion and rapid urbanized areas and effect of these challenges in urban green spaces are analyzed. Methodology To address these urban problems and to identify approaches for sustainable development, many researchers have focused on evaluation urban land-use changes. In this research, we selected Tabriz City for analyzing as a case study. Urban green spaces changes in Tabriz analyzed using Landsat satellite images for past decades. Satellite remote sensing provides an important source of land use/land cover data and can be utilized to monitor the changes in these data efficiently. In the first, we were made geo reference and necessary correction for satellite images and then we classified images using Erdas imaging 2014 software. For Quantitative assessment, the maps export to Arc GIS 10. 3.1 Software and finally, the green spaces land use maps and tables are produced. For analyzing green areas in future, green spaces changings in 1410 are modeled using Artificial Neural Network (ANN) base of past changes pattern. Artificial neural networks are able to approximate accurately complicated nonlinear input–output relationships. Like their physics-based numerical model counterparts, ANNs require training or calibration. After training, each application of the trained ANN is an estimation of a simple algebraic expression with known coefficients and is executed practically instantaneously. The ANN technique is flexible enough to accommodate additional constraints that may arise in the application. Results and discussion Result show that, urban expansions to per-urban and especially in green areas and orchards have been made major changes in urban green spaces. Evaluation of green space areas from 1355 to 1385 show that the green areas are decreased from 5916.53 to 4373.96 hectares. In 30 years periods, 1542 hectares of green areas destroyed and percent of green areas in Tabriz limit, reduced from 23.31 to 17.23. The land use changing in this period has been slowly. But, the green rate damages, in last decade is too fast and urban green areas in 1395 is 1709.02 hectares that contain 6.73 percent of city limit (25000 hectares city limit). In last decade, 2664 hectares in Tabriz green spaces, change to other land use and especially in 1385 to 1390 the rate of changing was faster and most of 50 percent of green areas in this period are demolished. In ANN modeling results, Tabriz will lose 1076 hectares of green areas from 1395 to 1410. Conclusions Therefore, the results indicate that the lack of proper planning of Tabriz's urban development in the last half century and especially in the past decade has caused irreparable damage to the green spaces of Tabriz, and will continue the trend in the coming years will threaten sustainable urban development and ecological balance of Tabriz city
