Saeed Varamesh; Sohrab Mohtaram Anbaran; Zahra Rouhnavaz
Abstract
Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed ...
Read More
Extended Abstract
Introduction
awareness of the type and percentage of land use and cover types is a fundamental requirement for understanding and management of a region. The growth of urbanization and increasing use of resources due to the development of the required facilities in urban life has changed the pattern of demand for resources and lands, changing the nature and quality of agricultural land, Historical and natural landscapes and surrounding urban areas through the transformation of these lands into residential areas. In recent decades, the suburban lands of cities have changed their use due to the urbanization process and the need of citizens for new residential areas and the surrounding lands, which are often high quality agricultural lands and gardens. This, along with things like industrialization and changing rainfall patterns, has destroyed the cover and natural environment of cities, and thus has posed many social and environmental challenges and endangered sustainable urban development, and as a result of this process, a lot of ecological pressure has been imposed on the natural ecosystem of the region. These changes are considered as one of the important and effective factors of social and environmental challenges. Today, remote sensing technology and GIS due to capabilities such as high monitoring power and resolution, frequent images, cost reduction, etc., To effectively identify and quantify land use changes and their effects on the environment and monitoring And rapid management of the growth and development of cities are used. In the present study, the aim is to evaluate the urban development of Ardabil in the last 30 years using remote sensing technology and satellite images.
Materials & Methods
Landsat satellite imagery was used to prepare land use maps for 1987, 2000 and 2017. In order to ensure the quality of data and bands, the images used in this research were first corrected for radiometric errors in ENVI 5.3 software environment. Then RVI, SAVI, NDVI, BI and IPVI indices were extracted. In the next step, maps related to filter texture, vegetation delineation and tasseled cap were prepared. At the end of this step, all the extracted layers were merged with the corrected image bands. Then satellite imagery using support vector machine algorithms, maximum similarity and artificial neural network with acceptable accuracy in six user classes (residential areas, covered agricultural lands, fallow, barren lands, urban forest and water) floor were classified. Then, to evaluate the classification accuracy, the overall accuracy and kappa coefficient were calculated for each of the maps.
Results & Discussion
According to the values of overall accuracy and kappa coefficient, which in 1987 for the support vector machine algorithm were 90% and 0.86, respectively, the maximum likelihood was 84.5% and 0.78, and the neural net was 90.5% and 0.87, respectively, in 2000. Overall accuracy and kappa coefficient for support vector machine algorithm 92% and 0.90, maximum likelihood 92.5% and 0.90 and neural net 92.6% and 0.90, and in 2017 overall accuracy and kappa coefficient for backup vector machine algorithm 90.6% and 0.88, maximum likelihood of 82.8% and 0.78 and for neural net were 88% and 0.85, it was found that the support vector machine algorithm has the highest accuracy compared to the other two algorithms. According to the results obtained from the study of satellite images classified by the support vector machine algorithm, the area of land built in Ardabil has increased from 20.023 square kilometers in 1987 to 41.554 square kilometers in 2017.
Conclusion
In general, it can be concluded that to evaluate the trend of urban sprawl and awareness of land use change patterns for optimal management and planning of cities, the use of satellite images, especially Landsat images is a suitable and low cost option. The results also showed that the rate of land use change to land uses is increasing and since land is the main element in urban development, so control how to use it and also calculate the real need of the city for land, to In order to provide different uses is effective. As a result, according to the findings of this study, in the absence of proper planning for this city due to favorable lands for urban development around the city, in the not too distant future, witness the destruction of agricultural lands around the city of Ardabil and conversion they will be residential areas.
Fariba Moghani Rahimi; Ahmad Mazidi; Hamid Reza Ghafarian Malamiri
Abstract
Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half ...
Read More
Abstract ExtendedIntroductionStudying land cover changes has a very long history which coincides with the beginning of human life. Following the formation of societies, primitive humans began to change the cover of wasteland to form suitable lands for agriculture and animal husbandry. More than half of the world's population recently lives in cities, urbanization and urbanism is rapidly increasing, and this trend will continue to reach its peak. Due to their extensive coverage, reproducibility, easy-access, high accuracy and reduction in necessary time and expenses, remote sensing data are generally considered a preferred method used to study land cover, vegetation, and their changes. Many researchers have shown an interest in land cover change in different cities of the world. The history of land cover studies dates back to the early nineteenth century and the studies performed by von Thünen (1826). Von Thünen have determined the economic benefits of different land covers based on their distance from the central city and found an optimal distribution for production and land cover in the form of a series of concentric circles. Land cover changes due to human activities are considered to be an important topic in regional and development planning. Since land cover changes and urban development in the study area have not been previously studied, Landsat time series satellite imagery and a combination of Landsat 7 and 8 panchromatic and multispectral bands were used to identify and detect changes in land cover and urban development in the urban areas of Abarkooh from 2000 to 2020. Materials & MethodsSatellite remote sensing data are used in the present study (Landsat 7 and 8 multi-temporal satellite images collected in 2000, 2010 and 2020). 3 images were retrieved from US Geological Survey website and used in the present study. Raw remote sensing images always contain errors in geometry and the measured pixel values. The former category is called geometric errors and the latter is called radiometric errors. Atmospheric corrections were performed for all images used, and stripping in the imagery collected in 2010 image was also corrected. For image enhancement and extraction of more information from the images, false color composites were used (5-4-3 infrared, red and green bands) for Landsat 8 and Landsat 7 (3-4-3 near infrared, red and green bands) images. Using this technique, vegetation is shown in red. Compared to other methods, Gram-Schmidt based pan sharpening method produced higher spatial resolution images of the study area and thus was used to combine the selected images. Maximum likelihood method is considered to have the highest efficiency among various supervised classification methods. Results & DiscussionThis method assumes the presence of a normal distribution for all training areas. The accuracy of this classification has to be calculated following the classification. To do so, the kappa coefficient and overall accuracy of each class were calculated in ENVI5.3. The results are shown in the error matrix. Overall accuracy is the average of classification accuracy. The kappa coefficient calculates the accuracy of classification as compared to a completely random classification. Based on the available data, spatial resolution of the images and the information researcher has access to, 5 classes of training data (urban constructed space, roads, barren lands, arable lands, and gardens) have been selected for each image. Results obtained from the maximum likelihood classification method in ENVI5.3 environment were changed into the vector format and then used as a shape file in GIS environment. After compiling the land database, land cover maps and its changes were extracted in three periods and the area of each land cover class was determined. Each of the land cover maps, 5 classes with different colors are determined and shown. To ensure the accuracy of the classification, the accuracy of the classification has been evaluated. ConclusionThe resulting kappa coefficient for 2000 and 2020 equaled 86% and overall accuracy equaled 89%, while for 2010 kappa coefficient equaled 90% and overall accuracy equaled 92%. Thus, the error rate is small and acceptable. Finally, post-classification comparison method was used to investigate the nature of changes. 13 square kilometers of land cover were investigated in the present study. To identify the exact type of land cover changes, categorized images collected in these years were compared. Total area of residential land use showed an increasing trend: a total 4.25 square kilometers in 2000 (32.69 percent of the total area under study) has reached 5.58 square kilometers (42.92 percent) in 2020. Overall area of arable land use did not change much in the period of 2000 to 2010. However, a declining trend was observed in 2020 changing a part of this land use into residential and barren lands. Results of satellite image processing and classification indicate that supervised classification and maximum probability algorithm were close to ground realities and had an acceptable accuracy. In general, results indicate that significant amounts of vegetation and agricultural lands have been converted into urban areas and thus, planning for urban growth in these areas should be in favor of preserving gardens and agricultural lands.
Ilia Laaliniyat; Mousa Kamanroudi Koujori; Tajeddin Karami
Abstract
Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, ...
Read More
Extended AbstractIntroductionThe third millennium has been called the age of urbanization and the urban population is expected to reach about 6.25 billion by 2050. The United Nations also estimates that the urban population of developing regions will grow at an average annual rate of about 2.02 percent, from 2.67 billion in 2011 to 3.92 billion in 2030. Indeed, the urbanization process is a phenomenon that has become increasingly concentrated in developing countries in recent decades. Although the pace of change varies considerably between countries and regions, in fact all developing countries are becoming increasingly urbanized. The increase in urbanization has caused many problems in urban areas. This has led to the fact that today land use management of urban infrastructure has become the main challenge of many planners and city managers. Accordingly, this study seeks to investigate the scattering around the Tehran-Eyvanekey communication axis, so Pakdasht cities with about 210 thousand people , Sharifabad with about 12,000 people and Eyvanekey with about 12,000 people, make it one of the busiest axes in the metropolitan area of Tehran. Research MethodsThe main purpose of this study is to analyze the process of space expansion and modeling in the axis of Tehran Eyvanekey between 1985 and 2020 using remote sensing data and GIS. To have a comprehensive study of spatial organization of this metropolis, a deductive or inductive approach with a practical nature has been used. The basis of the study is based on using the satellite data and images (Landsat multi-time images) related to different years. Using IDRISI, GIS and GOOGLE EARTH softwares and Fuzzy Artmap LCM, MARKOV and CA models. Discussion resultsIn this study, in order to evaluate the pattern of expansion of built areas in the corridor of Tehran to Eyvanekey, TM and ETM + images of Landsat satellite related to the years 1985, 2000, 2011, and 2020 have been used. Based on this, the amount of land use changes in the four periods is as follows: The most expansion of practical surfaces in the axis of Tehran-Eyvanekey with an area of 223250 hectares, dedicated to built areas with an increase of 30,495 hectares over the last 35 years. After identifying the urban expansion pattern of Tehran-Eyvanekey corridor, in the next stage, in order to simulate how land use changes in the axis of Tehran-Eyvanekey for the year 2031, the method of automatic cells and chains has been used. For this purpose, to simulate land use changes in the axis of Tehran Eyvanekey in 2031, land use maps in 1985 and 2020 were used. The results show that according to the trend of urban growth in the region in 2031, the land area will reach more than 50,000 hectares. Also, according to the growth rate of urban areas in this region, it can be seen that during different periods, we see a kind of exponential growth in the study area, so that for the period 1985 to 2000, about 240 hectares per year have been built. This trend of growth has expanded and in the next period, ie 2000 to 2011, this number has reached about 580 hectares, and finally in the last period, ie 2011 to 2020, we have witnessed the expansion of about 2251 hectares per year in the built lands, which can be signs of accelerative urbanization. Therefore, the strategy of increasing physical density and using related methods to guide the development of the city towards greater sustainability, should be on the agenda of planners and those in charge of urban affairs. ConclusionModeling land use changes is an effective way to obtain information about how land use changes over time as well as the factors affect it. So, in order to analyze the process of space expansion and modeling in the axis of Tehran-Eyvanekey, it was modeled over a period of 35 years. The results showed that most of the land use changes during this period are related to the built lands, which due to the location of the built areas along the main arteries has a northwest-southeast pattern that is affected by urban growth in the metropolis of Tehran. As a result, they live in these areas, which are either engaged in the urban industries of these areas or use the satellite cities in this corridor as dormitory cities. Interestingly, as we move away from the main center, the metropolis of Tehran, the rate of urban land expansion decreases, which indicates that due to the low cost of housing in satellite cities, this area is a dormitory for the metropolis of Tehran.
