Remote Sensing (RS)
Raheleh Ostadhashemi; Khosrow Mirakhorlou; Jamshid Yarahmadi; Mohamad Reza Najibzadeh
Abstract
Extended AbstractIntroductionNowadays, natural resources are exploited for the purpose of economical development in developing countries. Expansion of agricultural lands, supply of charcoal and fuel wood and wood production play an important role in forest degradation which affects biodiversity, ...
Read More
Extended AbstractIntroductionNowadays, natural resources are exploited for the purpose of economical development in developing countries. Expansion of agricultural lands, supply of charcoal and fuel wood and wood production play an important role in forest degradation which affects biodiversity, soil conservation, the quantity and quality of water and the global climate conducted to the importance of forest conservation and reforestation. Therefore quantitative assessment of forests is required for conservation programs and forest monitoring is defined as a tool for sustainable forest management.Today, remote sensing techniques and satellite images can widely provide functional information in environmental studies. In this work, sentinel-2 satellite images with high spatial, temporal and spectral resolution were applied to determine the area, distribution and density of the Arasbaran forestsas well as other land use classes in the area.Materials and MethodsArasbaran area is located in Qaradagh mountainous region inthe north of East Azerbaijan province between 38°25′ 59 " N- 39°20′ 7.7 " N latitude and 46°09′ 18 " E- 47°16′ 5.3 " E longitude which covers an area of 551211 hectares and the deciduous forests of this area are known as the 11th Biosphere Reserved in Iran. The altitude varies from ca. 256 m tomore than 2000 m. the importance of the area is in having a rich flora (about 1334plant species) and unique vegetation among the vegetation of the country.For the first time, the Sentinel-2 images with a combination of high spatial and temporal resolution were used to classify the land use of the area.The best band combination was found for bands 2, 3, 6, 12 and NDVI index. Land use classification included dense, semi -dense, sparse and very sparse forests as well as rangeland, agriculture, residential area-bare soil, garden and water was implemented using 9 different algorithms in a pilot area to find the best algorithm. 280 training sample points were collected from all different land use classes in the area.Consequently, supervised classification technique and Maximum Likelihood algorithm with the Kappa coefficient of 0.886 and anoverall accuracy of 89.6% was identified as the best classification method for the Arasbaran area.Accuracy assessment of the final map was done using ground control points and Google earth images with a total accuracy of 95%.Finally creating an error matrix with 880 ground reference test pixels revealed the accuracy indices.ResultsThe final land use map of the Arasbaran area based onthe Supervisedclassification technique and Maximum Likelihood algorithm was created.Based on the results, the accuracy assessment of the final map showed that the Kappa coefficient and the overall accuracy of the classified map were 0.88 and 89.8% respectively.The forest distribution and canopy cover density map were extracted from the land use area map. The total area of forests with a canopy cover of more than 5%, obtained 131019 ha consisting of 39% dense forest, 36% semi -dense forest, 17% sparse forest and 8% very sparse forest. In addition, the largest type of land use accounted for rangeland with 270000, forest with 131019, agriculture with 101974, residential area-bare soil with 30028, garden with 15434 and water with 2756 hectares respectively. Based on the error matrix table and correct classified points as well as total ground control points, the highest user’s and producer’s accuracy belonged to the densed forest class as well as the lowest user’s accuracy and lowest producer’s accuracy belonged to garden and agriculture classes respectively.ConclusionThe results conducted supervised pixel-based image classification based on the Maximum Likelihood algorithms an acceptable method. It can be because of well -distributed training sample points, the high spatial resolution of sentinel-2 images or Environmental heterogeneity of the area. According to the results, dense forests declined(from 56910 to 50628 ha)however semi -dense and sparse forests have increased (from 35280 to 47930 ha)with respect tothe last forest survey project in the Arasbaran area in 2003.In addition, the results revealed an overlap between agriculture and garden as well as rangeland and residential area-bare soil classes because of multi culture of crops and fruit trees together as well as dried or low vegetation cover of rangelands in the area. These results can provide useful information for decision- making and sustainable forest management for reducing forest degradation and it seems to be an important next step to manage these forests based on conservation policies.
Geographic Information System (GIS)
Sakine Koohi; Asghar Azizian
Abstract
Extended AbstractIntroductionDue to the high costs of land surveying, remotely sensed digital elevation models (DEMs) are a common method used to demonstrate topographic variations of the land surface. Generally, these DEM datasets are freely accessible to engineers and researchers covering most parts ...
Read More
Extended AbstractIntroductionDue to the high costs of land surveying, remotely sensed digital elevation models (DEMs) are a common method used to demonstrate topographic variations of the land surface. Generally, these DEM datasets are freely accessible to engineers and researchers covering most parts of the world in different spatial resolutions. DEMs can be classified into two categories of high (small pixel size) and low (large pixel size) resolution DEMs. Several studies have addressed the vertical accuracy of different digital elevation datasets especially in countries lacking access to high quality ground-based data. Despite the widespread application of these products, vertical accuracy of these datasets in different land uses has not been addressed in Iran and most engineering studies use 1:1000 and 1:2000 topographic maps which are very expensive and time-consuming to obtain. The present study seeks to assess vertical accuracy of different resolution DEM datasets used to estimate elevation in various land uses in two Iranian provinces of Qazvin (urban, agricultural lands, garden, and forest, mountainous areas, plains, and rivers) and Mazandaran (urban, agricultural, forest/mountain, plains, and rivers). Materials & MethodsASTER and SRTM DEMs with a resolution of 30-meter and SRTM DEM with a resolution of 90 m resolution were collected in the present study to investigate their vertical accuracy in various land uses of Qazvin and Mazandaran provinces. Several topographic maps and GPS based datasets of the study areas were also investigated for a better assessment of these DEM datasets. Finally, common statistical measures such as standard deviation (SD), mean absolute difference (MAD) and root mean square error (RMSE) were used to compare remotely sensed DEMs with ground-based observations. Results & DiscussionFindings indicated that 30m SRTM DEMs showed a better agreement with ground-based observations in both study areas. RMSE of this dataset in Qazvin and Mazandaran provinces equaled 3.8m and 5.8 m, respectively. Results also indicated that in 30m SRTM DEM, 87% of points in Qazvin and 79.7% of points in Mazandaran provinces showed a lower than 5m mean absolute difference (MAD), while in the case of 30m ASTER DEM 79% of points in Qazvin and 53% of points in Mazandaran showed a lower than 5m mean absolute difference (MAD). For 90m STRM DEM, around 29% of points in Qazvin and 74% of points in Mazandaran showed a lower than 5m mean absolute difference (MAD). Although 90m SRTM DEM did not work efficiently in Qazvin province, its result in Mazandaran province was almost as efficient as 30m SRTM dataset. Assessing the vertical accuracy of different elevation datasets in different land uses indicated that 30m SRTM showed an acceptable result in most land uses except for mountainous areas and forests. This was mainly due to forest canopies blocking the radio waves penetrating such areas and low density of points generated by STRM sensors. Moreover, 30m ASTER did not show an acceptable result in most land uses except for plains in Qazvin along with urban and agricultural land uses in Mazandaran. Despite having a lower resolution, 90m SRTM worked better than 30m ASTER. However, 90m SRTM showed considerable errors in mountainous, urban and forest land uses, and therefore it shall not be used in such areas. ConclusionResults indicated that 30m STRM DEM is a valuable resource which makes elevation estimation for areas lacking ground-based information possible. Moreover, the type of land cover has a significant effect on the vertical accuracy of elevation datasets and thus, increased vegetation results in decreased accuracy of DEM datasets. Therefore depending on the land cover type in the study area, ground control points can be used along with remotely sensed DEMs to decrease errors.
Geographic Data
Yaser Moarrab; Esmaiel Salehi; Mohammad Javad Amiri; Hassan Hoveidi
Abstract
Extended AbstractIntroductionThe global rise in urbanization and settlement of the majority of the world’s population in urban areas create opportunities and challenges for improving the quality and sustainability of life. Potential of cities for meeting the basic needs of people has become an ...
Read More
Extended AbstractIntroductionThe global rise in urbanization and settlement of the majority of the world’s population in urban areas create opportunities and challenges for improving the quality and sustainability of life. Potential of cities for meeting the basic needs of people has become an important part of recent scientific and political debates. Covering only a small area of land, cities are responsible for many global environmental problems such as carbon emissions, energy and resource consumption, biodiversity degradation, and ecosystem degradation. They also convert natural forests to human settlements, farms, roads, gardens, and other human-made land uses, leaving many direct and indirect effects on natural conditions and ecological functions of upstream and downstream in forests (such as changes in quantity and quality of water, changes in water flow in rivers, changes in climatic condition and habitat quality). These structural and functional changes undermine environmental services provided by ecological infrastructure and threaten the environmental security of cities and their sustainable development. Therefore, urban managers and experts have always sought a suitable way for urban planning to regulate the structure of cities, support the stability of ecosystem and its performance, and maintain the ecological security of cities. Case studyLavasanat is a district in Shemiranat County in Tehran province of Iran, which is located in the northeast of Tehran. MethodsThe present study analyzes temporal-spatial changes of land use / land cover and then, uses InVEST 3.7.0 model to evaluate temporal-spatial changes of land uses. Results & DiscussionChanges occurring in the reference period were depicted in maps prepared for various land cover / land use classes. Validation of image classification shows a total accuracy of 95.72%, 96.26% and 95.32% and a Kappa coefficient of 0.948, 0.943 and 0.936 for classifications in 2000, 2010 and 2020, respectively, which is acceptable and indicates the compatibility of classified land uses and reality. Classification of images using maximum likelihood algorithm showed the presence of five classes of residential areas (urban area, villages, industries and roads), barren lands, pastures, water bodies and green space in the region.Land use maps and information derived from satellite images indicate that residential areas have experienced a growing trend due to increasing population, demand for land and consequent growth of urbanism, while green space had a decreasing trend during the reference period. Development of residential areas and reduction in green space are quite evident between 2010 and 2020. According to the present trend of land use change, there will be a sharp decline in green space in the coming years. Pastures experienced a decreasing trend from 2000 to 2010. However, it faces an increasing trend from 2010 to 2020 since more green areas were converted into pastures. Barren lands experienced a decreasing trend from 2000 to 2020. ConclusionThe present paper offers the results of modeling water production services in Lavasanat Basin in different decades. Results indicate that the water production in the entire Lavasanat basin equals 2641734.816 cubic meters in 2000, 3318950.915 cubic meters in 2010 and 7737201.215 cubic meters in 2020. Of these volumes, 1677926.367 cubic meters in 2000, 2287145.055 cubic meters in 2010, and 4908786.651 cubic meters in 2020 belonged to residential areas. This class contained an area of 4820578.505 square meters in 2000, 6885513.787 square meters in 2010 and 10407948.705 square meters in 2020 in the whole basin.The results obtained from InVEST scenario building model and water production model showed that the increasing trend of human-made land uses in the study area has a significant impact on increasing water production and, consequently, increases runoff. In fact, water production has experienced a growth rate of 1.25 or 125% from 2000 to 2010, and a growth rate of 2.33 or 233% from 2010 to 2020. Thus in 20 years, water production has increased by 2.92 (292%). The volume of water production in residential areas has increased by 1.36 times (136 %) from 2000 to 2010, 2.14 times (214 %) from 2010 to 2020 and 2.92 times (292%) in 20 years. Also, the total area covered by residential land use has grown 1.42 times from 2000 to 2010 (142 %), and 1.51 times (151%) from 2010 to 2020. Therefore, an increase of 2.15 or 215% was observed in residential areas over this 20 year period.
Mehrdad Hadipour; Hamid Darabi; Aliakbar Davudirad
Abstract
Extended Abstract Introduction With the development of urbanization, a large part of agricultural areas and forests have been replaced by residential areas, industrial centers, and other infrastructures. This is due to human life style and his endeavor to reach sustainable urbanization. A series of changes ...
Read More
Extended Abstract Introduction With the development of urbanization, a large part of agricultural areas and forests have been replaced by residential areas, industrial centers, and other infrastructures. This is due to human life style and his endeavor to reach sustainable urbanization. A series of changes in the reflection of light from different material’s surface, heat storage and heat transfer, have changednatural and artificial landscape orsignificantly affected local climate. Therefore, public concerns about urban sprawl, increasing urban population and quality of urban environmental have motivated planners to seek better perspectives for development of urban areas. Increasing temperature of urban areas is considered to be one of the most important environmental problem in cities. This increasing temperature results in creation of Urban Heat Islands (UHI) in some parts of urban areas, which are significantly warmer than surrounding urban environment. Therefore,a new and successful method of urban planning should be introduced with respect to spatial distribution of land surface temperature (LST) to achieve better urbanization and reduce environmental impacts on cities. Materials & Methods The present study takes advantage of Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) thematic maps to investigate therelationship between air pollution, and two indexes of NDBI and NDVI with land surface temperature (LST) and Urban Heat Islands (UHI) in urban areas. Satellite imageries of Arak (an industrial city in Iran) has been chosen for the case study. Urban and natural areas and impermeable surfaces such as roads, buildings and other constructions are rapidly developing in this city. In the first step of research methodology, necessary pre-processing programs such as radiometric corrections were performed on the satellite imageries. Then satellite imageries were transformed toatmospheric images to produce NDBI and NDVI indexes. Finally,land surface temperature maps wereproduced using the method of Landsat Project Science Institute in Arc GIS 10.3. To classify satellite images, seven land use classes were identified as poor pastures, averagepastures, rich pastures, bare lands, Lake’s Shore, agricultural lands and residential lands.Then, training images classification method was used to collect samples from the study area and classification was performed using maximum likelihood method for monitoring. In order to analyze LST parameter using NDBI and NDVI indexes, air quality data,and statistical methods like Kolmogorov-Smirnov test, paired t test and Pearson correlation test were used. The results of Kolmogorov-Smirnov test indicated that data used in this study was normally distributed. The results of t test, temperature recorded by synoptic stations in Arak and remotely sensed data indicated that the accuracy of the test is more than 5%. Thus, the difference between residential land use and other urban land uses was not statistically significant. Moreover, results indicate that there is a more than 99 percent correlation between temperature recorded by the synoptic stations in Arak and data collected from satellite imageries. Results of correlation with remotely sensed data indicatedthatthere is a significant correlation between99 percent of results and less than 5 micron particles. Results & Discussion Correlation between air pollution data andremotely sensed data (LST) indicated that LST and less than 5.2 micronparticlesare significantly correlated with 99% accuracy. Urban heat island usually occurs in metropolitan area and its surroundings. Due to climate changes, urban heat islands are constantly developing. This results in increased energy consumption for air conditioning systems. Thus, reducing the effects of urban heat islands has become an important global issue. The present study has successfully explained the effects of urban heat islands and their environmental problems on normal life. Detailed program of related measures and policies should reduce the intensityof urban heat island. Final development of the cities should be based on land surface temperatures in surrounding areas in a way that cities can reach a lower surface temperature as compared to the temperature before urban development. Conclusion Following strategies are suggested for a more comprehensive consideration of urban green spaces in urban planning and future development of cities: Paying attention to architecturalcriteria and urban land use, and alsopaying attention to soil and water management parametersbased on the principles of green architecture, paying attention to standards of anthropogenic temperature rise caused by human activities, and the problem of urban heat islands. Moreover, it is crucially important to prepare the necessary situation for the community to reach a good physical and mental health.
Mohsen Shaterian; Seyed Hojjat Mousavi; Zahra Momenbeik
Abstract
Extended Abstract Introduction Knowing type and percentage of each land use and land cover are considered to be a fundamental need for understanding and managing an area. Given the ever-increasing changes in land use, managers and experts need to be aware of past changes and developments. This is because, ...
Read More
Extended Abstract Introduction Knowing type and percentage of each land use and land cover are considered to be a fundamental need for understanding and managing an area. Given the ever-increasing changes in land use, managers and experts need to be aware of past changes and developments. This is because, policy making and solving existing problems require detecting changes and determining the trend of changes over time. Satellite data is one of the quickest and least expensive methods available based on which researchers can produce different land use map. In this regard, Landsat Satellite imageries are one of the most important data sources used to study different types of land use and land cover changes, such as deforestation, agricultural expansion and urban growth. Extracting information from satellite imagery through classification is one of the most widely used methods. One of the most important applications of remote sensing data is for investigating and discovering changes in phenomena with a spatial-temporal nature (i.e. phenomena whose position and status changes over time). In fact, change detection is the process of identifying and determining the type and extent of land cover or land use in a given period of time based on remote sensing images. The present study seeks to monitor land use changes in Shahr-e Kord during the period of 1985 to 2017, and to prepare land use maps of the area using Landsat satellite imageries. Materials & Methods In the present study, satellite imageries received from TM, ETM+, and OLI sensors of Landsat satellites in 1985, 2000, 2015, and 2017 were extracted from the United States Geological Survey (www.usgs.gov) and analyzed using different remote sensing software and geographical information systems like ENVI 4.7 and ArcGIS 10.4. In order to produce land use changes map, error correction was first performed. Then, images were processed using supervised classification method and maximum likelihood algorithm, which based on previous studies have a higher accuracy compared to other algorithms. In order to classify land use/land covers, a training sample was produced for each land use based on field observations, topographic maps (1:25000) produced by Iran National Cartographic Center, Google Earth imageries, and visual study of the imageries. Then, classification results were corrected using auxiliary data, visual interpretation, experiential knowledge, and GIS techniques. Prior familiarity with the region, visual study of imageries, previous experience and field operations revealed that following land uses exist in the region and are detachable on the images as well: a) urban, b) agricultural, c) industrial, d) meadow, e) airport, and c) other land uses (including pasture, rocky areas and areas without any specific land cover). Confusion or error matrix –including overall accuracy, producer’s accuracy, user accuracy and kappa coefficient- was also used to evaluate the accuracy of the classification. Also, urban land use changes were monitored using image differentiation functions. Results & Discussion After production of land use maps based on imageries received in 1985, 2000, 2015, and 2017, area of the six land cover classes was obtained. Results indicate that during these four periods (1985 to 2000), urban, industrial, agricultural and airport land uses have increased to 13, 111.7, 5.2 and 3.4 km2 (1.26, 10.16, 0.51 and 0.4 % increase) respectively, while meadows and other land uses have faced a decreasing trend. In other words, it can be concluded that most changes during this 15-year period occurred in meadows and other land uses. Since development of the airport have resulted in destruction of a large part of meadows, this land use have faced more severe changes. Land use changes from 1985 to 2017 indicate that 7.8 km2 of agricultural lands were transformed into urban land use, 1.4 km2 to industrial land use, 1.08 km2 to airport and 7.7 km2 to other land uses. Also, 20.5 km2 of other land uses were transformed into urban land use, 203.1 km2 to agricultural land use, 0.03 km2 to dried meadows, 0.17 km2 to airport and 14.5 km2 to industrial land use. 2.8 km2 of meadows were also transformed into agricultural land use, 0.05 km2 to industrial land use and 2.04 km2 to airport. During this period, urban and industrial land uses have remained unchanged. Conclusion Generally, results indicate that urban, industrial and agricultural land uses have developed over time, and these land uses have always had a positive increasing trend. While meadows and other land uses have had a decreasing and negative trend. This is due to the construction of Shahr-e Kord Airport, uncontrolled exploitations, digging wells and drought phenomena, which have led to a decrease in the level of water in aquifers and destruction of natural ecosystem in this region. In this way, previous meadows have turned into the source of intense dust generation in the city, which is a sign of desertification and ecosystem destruction. Due to drought and water scarcity in recent years, new deep wells have been dug with the aim of supplying water. This have occurred despite the critical condition of the meadows, and thus, have resulted in repeated protests by farmers and livestock farmers. Dramatic decrease in other land uses, including pastures, can also be attributed to recent droughts in Iran and intense dust generation. Increased population, increased human pressure on natural resources and also development of agricultural lands are among other causes of the present situation. Based on existing maps and satellite imageries, Shahr-e Kord is developing towards North and North West. In some areas, this development has occurred in pastures. Therefore, due to very high population density in the region which is still increasing, and also ongoing migration of villagers to the city, supplying appropriate accommodation and occupation for this population requires finding new suitable locations for urban and industrial development of the city. This development process should happen with correct management and according to the goals of sustainable development.
Sayyad asghari Saraskanrood; behrooz khodabandelo; Ahmad Naseri; Ali moradi
Abstract
Extended Abstract Introduction Currently, two general methods are used for classification of digital satellite images: pixel-based and object-oriented processing. Unlike pixel-based Methods, object-oriented techniques employ different geometric, spatial, spectral, and form-based algorithms, and selecting ...
Read More
Extended Abstract Introduction Currently, two general methods are used for classification of digital satellite images: pixel-based and object-oriented processing. Unlike pixel-based Methods, object-oriented techniques employ different geometric, spatial, spectral, and form-based algorithms, and selecting the most efficient algorithm in this process requires a lot of experience in image processing. In addition, multiple algorithms usually offer different results and this in many cases makes the selection of efficient algorithms difficult. In general, pixel-based classification includes supervised and unsupervised methods. Examples of these methods include maximum likelihood, neural network and support vector machine. Maximum likelihood method is one of the most effective methods used for image classification. Object-oriented methods take advantage of knowledge-based algorithms, and thus overcome problems pixel-based method faces because of not using geometric and textual information. In order to achieve high classification accuracy, two methods of pixel-based and object-oriented classification are compared in this research. On the one hand, integrated planning and management of urban areas, and on the other hand, collecting reliable information regarding land use makes this kinds of studies indispensable. Materials&Methods Present study seeks to extract urban land use map. Thus, necessary data was received from Sentinel-2. Moreover, ENVI 5.3, eCognation 9, SNAP, ArcGIS 10.3, Google Earth, and land-use data were also used to process images and analyze data. In SNAP, atmospheric correction process was performed on images collected from the study area using SEN2COR plug-in. Samples collected from each class of Sentinel-2 satellite image were mapped on the image area. Pixel classification algorithms, support vector machines, maximum likelihood, artificial neural network, Minimum Distance to Mean (MDM), parallelepiped and Mahalanobis distance were used. Finally, land use classes (residential, gardens and green spaces, wastelands and passageways) in the study area were mapped using different classification algorithms. For object-oriented classification using nearest neighbor algorithm, the satellite image was first segmented in eCognation software using the Multiresolution Segmentation Algorithm. Parameters such as scale, shape and compactness were also studied in the image segmentation stage. Through trial and error, an appropriate value was selected for parameters used in segmentation. For practical comparison of the results, the same educational data was used in both object-oriented and pixel-based classification methods. Then, the most important methods for assessing accuracy including overall precision and kappa coefficient were extracted. Results & Discussion As one of the most important methods used for extracting information from remotely sensed images, classification allows users to produce various types of information such as coverage maps, and land-use maps. Classification of satellite data includes segregation of similar spectral sets and classification of sets with the same spectral behavior. Regarding the resolution of images used (10 m) in this study, only 4 land-use classes possessed the required resolution capability for pixel-based classification of Sentinel-2 satellite images. These classes include built-up (residential) area, waste land, urban green space and street network. In this regard, support vector machine, maximum likelihood, artificial neural network, Minimum Distance to Mean, parallelepiped and Mahalanobis distance were used for classification. Classification results indicate that compared to other pixel-based methods, maximum likelihood method and Minimum Distance to Mean method show a precision of 85% or higher. In present study, geometric properties of land use classes (including scale, shape, and compactness) were used for segmentation and this process was performed by multiresolution method. For this purpose, results of image segmentation process were analyzed based on different parameters (with different scales) and spatial resolution of the image. In this way, appropriate values for segmentation were selected based on the specific features of the study area (an urban environment) through trial and error. Then, the proper image segmentation was selected and prepared for the classification stage using the above mentioned parameters. In the next step, 20 effective parameters including statistical indices, mean score of bands, NDVI index, standard deviation of the bands and geometric index were used for classification. Conclusion The present study took advantage of six pixel-based methods (Support Vector Machine, Maximum Likelihood, Neural Network, Minimum Distance to Mean, Parallelepiped, and Mahalanobis) along with object-oriented classification method to produce a land-use map for Zanjan city. The accuracy of classification in different methods were compared and statistically analyzed using overall accuracy coefficient, kappa coefficient, user’s accuracy, and producer’s accuracy. The results of statistical analysis of the accuracy coefficients indicated that Minimum Distance to Mean and Maximum Likelihood method -with a Kappa coefficient of 90% and 85% respectively- are acceptable methods for land use mapping. Moreover, comparing pixel-based and object-oriented methods, it is possible to conclude that object-oriented approach with a Kappa coefficient of 0.95% and overall accuracy of 97.9% shows a higher potentiality. Nearest Neighbor algorithm is one of the most important reasons for achieving this high accuracy in object-oriented classification. In addition to the spectral information, this method uses information collected about issues like texture, form, position, and content for the classification process. Methods used in this study prove the accuracy of objective-oriented technique by employing effective parameters and developing rules to modify the initial classification of object-oriented technique. Another advantage of object-oriented method (as compared to pixel-based methods) is that apart from spectral information and statistical data, it is possible to apply several other indicators such as shape, texture, color, dimensions and altitude of the phenomena in the final land use map produced by this method. Finally, it should be noted that object-oriented classification has been developed for high resolution spatial data.
Hamid Ebrahimy; Aliakbar Rasuly; Ahmad Ahmadpour
Abstract
Extended Abstract
Introduction
Land use is one of the most important indicators of economic and social development in urban areas, and has resulted in extensive changes in available structures and procedures of these areas. Therefore, human activities are known as one of the main principles and components ...
Read More
Extended Abstract
Introduction
Land use is one of the most important indicators of economic and social development in urban areas, and has resulted in extensive changes in available structures and procedures of these areas. Therefore, human activities are known as one of the main principles and components of change in land use. Generally, land use changes are inevitable product of interactions between human activities and environmental elements. Remote sensing technology with capabilities such as providing update and reliable information about natural and urban areas, digital processing of satellite imageries, providing the possibility of temporal and spatial comparing of different phenomena, diversity of products, and etc. is considered to be a powerful tool in improving the efficiency of urban management. Consequently, remote sensing data are used to determine type, quantity and location of land use changes. Moreover, remote sensing technology is used extensively in land use maps all over the world. Many models have been applied to predict land use changes, which due to the complex, dynamic, and non-linear nature of the issue gained little attention. However, CA-Markov model, which is a combination of Markov chain and cellular automata, is commonly considered to be an appropriate and good method for spatial-temporal modelling of land use changes. In the present study, land use changes were investigated for a 15-year period in Shiraz using object- based image analysis. Then, a land use map was produced using cellular automata-Markov (CA-Markov) model to predict land use changes in the study area in 2020.
Material & Methods
The present study includes two main phases. In the first phase, land use map of Shiraz was produced using Fuzzy object based analysis of satellite imageries. In the second phase, modeling and predicting of land use changes in 2020 were performed. Landsat imageries of the study area in 2005, 2010 & 2015 were used in this research. After preprocessing and preparing the imageries, segmentation procedure was performed as the first stage of object based classification using multiresolution segmentation algorithm. The nearest neighbor algorithm was used for object based classification of satellite imageries. Classification conditions were defined in accordance with each class properties, and classification was performed based on fuzzy operators of the classification operation. In CA-Markov model, the possibility of changing from one class of land use to another was calculated using transfer matrix table. Then, land use map of future years will be predictable in accordance with the transfer probability matrix, and desired time interval.
Result & Discussion
In this study, scale parameter of 10, shape index of 0.4, and compactness index of 0.2 were extracted as the optimum conditions for segmentation. Apart from spectral data, information regarding the location, context, texture, normalized difference vegetation index, enhanced vegetation index, and digital elevation model were also used to improve the efficiency of classification phase. The results of model validation shows an overall accuracy of 89% and kappa coefficient of 0.87. Therefore, the results of CA-Markov model shows a very good potential for predicting land use changes in Shiraz. Thus with the adjustment and calibration of model parameters and based on land use maps of 2010 and 2015, Shiraz land use in 2020 was predicted.
Conclusion
Due to the complexity of modeling dynamic changes in urban land use, utilizing efficient and update methods of data analysis is crucial. Therefore, satellite imageries and object based image analysis techniques were used to prepare land use map of Shiraz based on the data collected over a 15 year period. By considering the defined land use classes (residential area, barren lands, street network and urban green space), optimum image segmentation parameters were found. Then, classification conditions were defined for each class using the nearest neighbor algorithm and fuzzy operators. In this way, image classification was performed. By analyzing land use changes during the 20-year period, we understand that residential area has increased from 38 square kilometers in 2005 to 142 square kilometer in 2020. Additionally, green space area faced a reduction of 4 km in the first 5 years of the period, while in the next 15 years green space area shows an increasing trend.
Kamran Karimi; Gholamreza Zehtabian; Marzban Faramarzi; Hassan Khosravi
Abstract
Extended Abstract Introduction Land use changes is a widespread and accelerating process, mainly driven by natural phenomena and anthropogenic activities, which in turn drive changes that would impact natural ecosystem. Because of the human population growth and its impacts, land-use patterns are changing ...
Read More
Extended Abstract Introduction Land use changes is a widespread and accelerating process, mainly driven by natural phenomena and anthropogenic activities, which in turn drive changes that would impact natural ecosystem. Because of the human population growth and its impacts, land-use patterns are changing very fast. Most of the population in Iran depends on agriculture, so the land use changes are mostly linked to agricultural developments. In recent decades, rapid land use changes have been associated with the degradation of natural resources, especially in sensitive ecosystems. On the other hand, like many other developing countries in the world, significant land-cover changes have been occurred in Iran within two last centuries. These changes were primarily due to human activities in connection with the population increase, which forced people to clear forest for cultivation and other activities. This study tries to present the effect of irrigation systems on land use changes since over three decades. Methodology Abbas plain with a surface area of 34104 ha, is located in Ilam province near the Iran’s western border. The average of annual precipitation and temperature are 207mm and 26.1o respectively. Karkheh dam, one of the largest soil dams in the world and the largest soil dam in Iran and the Middle East, located 15 km east of Abbas plain. The Karkheh Dam is designed to irrigate 320,000 hectares of downstream land including Abbas plain. The water transfer project to the Abbas plain was launched in May 2005. In the present study area, changes in land cover were evaluated in the pre and after- exploitation period of irrigation networks of Karkheh dam to the Abbas plain in Ilam province, Iran. To obtain more accurate results, Landsat sensors imagery of TM, ETM + and OLI were used for the years of 1989, 2003 and 2013, as well as topographic maps, Google Earth images and area coverage. To classify the land use changes, supervised classification method with maximum likelihood algorithm was applied in the ENVI4.8 software. Images of all three periods were classified into five classes: rangelands, agricultural land, residential land, river bed and barren lands and hill moor. In order to determine more precisely changes, areas were obtained for two other periods. Results The classification accuracy results showed that the Kappa line was more than 87% for every three years and the overall accuracy obtained were 90.43%, 92.28% and 94.76% respectively for these years. The results also showed that barren lands and hill moor class has covered the largest area of this study place during the two periods (pre and after- exploitation), so that, it was 12344.1 hectares in the first period and 17370.5 hectares in the second one. In both study periods, the rangeland class has been destroyed, but in the second period 13.8% was destroyed more than the first one. Due to the exploitation of irrigation systems by farmers in the second period, more changes in land use have been converted to agricultural use, so that, 3671.8 hectares (55%) have been added to these lands during 10 years. The growth of residential areas was 0.27% of the study area after channelling, which was estimated 1.6 times higher than the first one. The area increase average in this class is 10.2 hectares per year. The most frequent conversion to farm use was barren lands and hill moor class. These lands have undergone a change by residents of the region due to their location between agricultural lands and a short distance from irrigation systems. A large number of land use changes can be prevented by defining the scope for agricultural land. Conclusion and Discussion In the present study area, irrigation has been in practice since over 25 years ago. Significant land-use changes have occurred in the study area in response to the Karkheh Dam from time to time affecting agricultural productivity leading to land-use changes. Unfortunately, some parts of these changes are out of schedule and unskillful and, that is significant for planners to know about these. All in all, for providing management activities and environmental programmes, accurate data on land use changes are essential. Satellite images and maximum likelihood algorithm provide the baseline data essential for proper understanding on the land-use patterns in the past and its impacts. It is also proper to understand the past land use changes ratio, and the physical and socio-economic factors behind.
Saeed Amanpour; Mohammad Javad Kamelifar; Hojjat Bahmani
Abstract
Abstract[1]
One of the main challenges in the urban development process in developing countries is their accelerated growth, which, if this growth issporadic and unplanned,it will pose a lot of problems to the urban management process and planning.The city of Ahwaz is one of the cities in our country ...
Read More
Abstract[1]
One of the main challenges in the urban development process in developing countries is their accelerated growth, which, if this growth issporadic and unplanned,it will pose a lot of problems to the urban management process and planning.The city of Ahwaz is one of the cities in our country that has witnessed arapid and scattered growth in urban land development in recent years. According to the status map of the urban land development, this trend has been intensifying year by year and has led to challenges in providing services and infrastructural resources in the city. In this regard, due to the necessity of the issue, in the present study, we tried to use a descriptive-analytical method to evaluate land use changes in the metropolis of Ahwaz between 1989 and 2013. Data collection in descriptive section was done through the study of library documents, and in the analytical part of the research, by extraction of satellite images TM (Thematic Mapper) for the years of 1985 and 2013 from Ahwaz city. Envi 4.8 and Arc GIS 10.2 software have been used to perform statistical and visual analyzes on satellite imagery. The results show that during the years 1989 to 2013 about 23 percent of the share of barren and agricultural lands have decreased and on the other side the share of built-up lands has increasedfrom 16.35 to 34.55, most of which are related to the Southern and Eastern parts of Ahwaz (Parts of areas 4, 5 and 6 of the municipality).
[1] - به دلیل کیفیت نامناسب متن چکیده مبسوط انگلیسیِ ارائه شده توسط نویسنده مسئول مقاله، نشریه به ناچار اقدام به ترجمه مجدد متن چکیده فارسی و انتشار آن به جای چکیده مبسوط انگلیسی نموده است.
Iman Ghalandarian Golekhatmi
Volume 23, Issue 89 , May 2014, , Pages 102-105
Abstract
Different elements are involved in user’s transportation choice. Land use is one of these influential elements. The present article investigates the impact of different urban land use factors (like density, local access, street connections, composition of the land uses, pedestrian-center) on traveling ...
Read More
Different elements are involved in user’s transportation choice. Land use is one of these influential elements. The present article investigates the impact of different urban land use factors (like density, local access, street connections, composition of the land uses, pedestrian-center) on traveling behaviors (like using personal car, transportation without car). This information is especially appropriate for evaluating transportation policies and their influences. Policies like intelligent growth, new urbanism and access management help in realizing plans of transportation planning.
Siamak Taghizadeh ghaleh jooghi; Manuchehr Masumi
Volume 21, SEPEHR , February 2013, , Pages 59-65
Abstract
Land forms are always changing because of human activities and natural phenomena. In urban environment, these changes happen with more diversity and speed. As a result, understanding land use changes is essential for optimal urban management. Thus, accessing information regarding land use and its changes ...
Read More
Land forms are always changing because of human activities and natural phenomena. In urban environment, these changes happen with more diversity and speed. As a result, understanding land use changes is essential for optimal urban management. Thus, accessing information regarding land use and its changes over time are among important issues in urban management. Population growth and overusing the earth potential have increased the pressure on environment. Therefore, controlling the trend of urban development is necessary.
Using the new and precise tool of GIS and RS sciences and techniques, satellite images and aerial photos, scholars, researchers and planners can investigate and study environmental and physical changes of the city in different time periods, exploit and analyze data, control and predict urban development trend.
In order to determine level of land use changes in Naqade during 1964-1999, the present article investigate and analyze aerial photos and satellite images in different land uses and land covers in five different classes like residential classes, roads, vegetation, jungles, and surface water. Results were determined and digitalized in different layers for the sake of comparing and analyzing the changes.
Majid Vali Shari'at Panahi; Seyyed Rahim Moshiri; Alireza Este'laji; Shokrollah Mohammadi; Jamileh Fotouhi
Volume 19, Issue 73 , May 2010, , Pages 48-52
Abstract
The main purpose of this research is the importance of land use changes in Gorgan city using remote sensing data. In fact, remote sensing has vast applications in many fields of science and research. Possibility of regular periodic imaging and uninterrupted transmission of satellite images are two very ...
Read More
The main purpose of this research is the importance of land use changes in Gorgan city using remote sensing data. In fact, remote sensing has vast applications in many fields of science and research. Possibility of regular periodic imaging and uninterrupted transmission of satellite images are two very important factors in the use of satellite data. These advantages will help experts in diverse fields to be able to use satellite imagery and information in studies such as periodic variations in the Earth’s surface, changing features and phenomena and natural disasters. In fact, one of the essential needs of researchers, managers and planners is to have accurate and timely information. Land use maps represent human activities concerning exploitation of land, for example, industrial and residential areas, agricultural fields, and so on.
Mas'oud Taghvaei; Elham Amirhajlou
Volume 17, Issue 65 , May 2008, , Pages 52-59
Abstract
It has been proved today that efficient urban management is not practical without utilizing up-to-date information on land uses and trends of their changes, the type and extent of activities, physical growth of the city, and so on. Hence a need for various information equipment in this regard has been ...
Read More
It has been proved today that efficient urban management is not practical without utilizing up-to-date information on land uses and trends of their changes, the type and extent of activities, physical growth of the city, and so on. Hence a need for various information equipment in this regard has been developed, and the amount of up-to-date information has increased in organizations associated with urban affairs. The Global Positioning System (GPS), as one of the most important and reliable positioning technologies and the Geographic Information System (GIS) as a reference system of reception and optimal management of positional information, plays an important role in position-based analyses. The combination of these two systems provides new and comprehensive capabilities in position-based management.
Ali Shakur; Raf'at Shokri; Morteza Zera'ati
Volume 16, Issue 64 , February 2008, , Pages 19-24
Abstract
City is considered as one of the human-made phenomena in the environment, created with the aims of settlement, livelihood provision, social and economic relations and so on, but these are not considered as urban aims. The man has provided his own environment and has begun to live in it. Cities should ...
Read More
City is considered as one of the human-made phenomena in the environment, created with the aims of settlement, livelihood provision, social and economic relations and so on, but these are not considered as urban aims. The man has provided his own environment and has begun to live in it. Cities should be based on the role and responsibilities they have in their region, and be developed in all aspects in a manner that minimizes their negative effects. Therefore, urban planning needs to be implemented in such a way that settlements and organizational patterns and the type of human activities be looked upon as a large community. Therefore, the main goal is based on the principle that urban planning be coherent. The urban hierarchy, according to a definition, is the classification of cities located in a geographical area based on population indices and the importance of their official functions, so that they can be categorized into different groups by calculation and measurable order. As we know, urban hierarchy is uneven in many provinces of our country, and there are many differences between cities in terms of ranking according to indicators. The cities of Fars province do not have regular hierarchies, and certain causes and factors have lead these hierarchies to be problematic. In this research, the urban hierarchy of Fars province has been studied based on three different patterns, the results have been compared with each other, and its hierarchy has been determined and some strategies to improve its ranking have been presented.
Abbas Alimohammadi; Hadi Akbari
Volume 15, Issue 57 , May 2006, , Pages 30-33
Abstract
All phenomena in the universe are undergoing change and transformation. Certainly, we can say that there is no phenomenon on the planet that does not undergo metamorphosis. The difference between the phenomena in terms of change is the difference in the rate of change. In studies on land and natural ...
Read More
All phenomena in the universe are undergoing change and transformation. Certainly, we can say that there is no phenomenon on the planet that does not undergo metamorphosis. The difference between the phenomena in terms of change is the difference in the rate of change. In studies on land and natural resources, phenomena in general can be classified in terms of the rate of change into three categories: high speed (flood, earthquake, storm, climate change), average speed (land use, urban development) and slow (topographic changes, etc.) phenomena. Remote sensing has made it possible to study average and high speed changes. With the availability of images for two different times, changes can be assessed. In this regard, using images of the years 1988 and 1998 from the city of Tehran, changes in land use in this city have been retrieved and determined.
