mohammad amin ghannadi; Hamid Enayati; Elaheh Khesali
Abstract
Extended Abstract Introduction A Digital Elevation Model or DEM is a physical representation of terrain and topography that is modeled by a digital 3D model. DEMs have various applications in many fields. Today, with respect to improvements in technology and importance of generating DEM from every region ...
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Extended Abstract Introduction A Digital Elevation Model or DEM is a physical representation of terrain and topography that is modeled by a digital 3D model. DEMs have various applications in many fields. Today, with respect to improvements in technology and importance of generating DEM from every region in our country, the importance of satellite remote sensing is more sensible. One of the main topics in satellite remote sensing is radar remote sensing. In recent years, a number of satellites have been launched to capture SAR information from the surface of the Earth. The last project is Sentinel, and Sentinel-1generates SAR data. It generates images with medium spatial resolution from the Earth every 12 days. DEMs are generated through multiple methods, one of which is SAR interferometry. Material and Methods The area under study in this research for conducting experiments and generating the DEM is Iran and the city of Tehran. Tehran is located in the north of the country and south of the Alborz Mountains, 112 kilometers south of the Caspian Sea. Its elevation ranges from 2000 meters in the highest points of the north to1200 meters in the center and 1050 meters in the south. In this paper, the Sentinel-1 stereo images are used to generate DEM. Tehran is located on part of these images. These images are shown in Figure (1). In order to evaluate the digital model generated by these images, a reference digital model which has been prepared from the city of Tehran with an accuracy of 1 meter is used. This elevation data was collected using terrestrial surveying and aerial photogrammetry. In this paper, radar interferometry was used to generate digital elevation model from the Sentinel-1 images. In SAR interferometry, the phase of images taken from various imaging positions or various imaging times is compared pixel by pixel. The new image is produced by differentiating between these values which is called interferogram. Interferogram is a Fringe interference pattern. Fringes are lines with the equal phase differences similar to contours in topographic maps. The phase difference obtained from SAR interferometry is affected by several components. Some of the most important components are orbital paths, topographic, displacement and atmospheric components. By eliminating the major part of the orbital component (and calculating the effect of other components or assuming their insignificance effects comparing with orbital and topographic components), since the topographic radar observes the Earth from two different points, the stereoscopic effect is revealed. This topographic component leads to fringes which encompasses the topography like contours. These patterns are called topographic fringes. Results and Discussion In order to conduct the experiments considered in this paper, two mountainous and flat areas in Tehran are picked out and separated from the main image. The mountainous area is selected from the north and the flat one from the south of Tehran. The aforementioned technique is implemented and executed on these images. The generated DEM in these two areas is shown in Figure (2). After generating the Earth DEM using the Sentinel-1 images, and comparing it with the reference DEM having an elevation accuracy of 1 meter, the accuracy of the generated DEM was determined. As expected, the results in the flat area were more desirable compared to the mountainous area. The accuracy of the generated DEM was evaluated by creating a network with the dimensions of 138761 points from the flat area and a network with the dimensions of 78196 points from the mountainous area, from both generated and reference DEMs and comparing the corresponding elevations of the network points. Digital numbers of images represent the magnitude of error occurring in the generation of DEM. After testing the 3 error (blunder detection) and eliminating large errors occurred in DEM, a standard deviation error of 1.26 meters for the flat area (South of Tehran), and 10.32 meters for the mountainous area (North of Tehran) were obtained. Conclusion Considering the development of technology and the launch of new satellite imagery projects from the Earth and the importance of the existence of a digital elevation model from the country, it is possible to recognize the importance of studying these images more and more. One of the latest satellite remote sensing projects is the Sentinel project. The Sentinel-1 radar images with medium spatial resolution capabilities provide the possibility of generating a Digital Elevation Model (DEM) from the country. This research is the first study on the accuracy of Digital Elevation Model resulted from the Sentinel-1 radar images in Iran. An elevation accuracy of 10.32 meters in the mountainous area, and 1.26 meters in the flat area were obtained. The results show that these satellite images have the capability of generating a relatively optimal DEM, particularly in non-mountainous area.
Hamed Amini Amirkolaee; Hamid Enayati; Maryam Veisi
Abstract
Extended Abstract
The Digital Terrain Model (DTM) is a statistical presentation of the earth surface using some points with predefined 3D coordinates. Extracting the DTM as an important product of photogrammetry and remote sensing that is the basis of many practical projects, has always been considered ...
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Extended Abstract
The Digital Terrain Model (DTM) is a statistical presentation of the earth surface using some points with predefined 3D coordinates. Extracting the DTM as an important product of photogrammetry and remote sensing that is the basis of many practical projects, has always been considered by experts. LiDAR is a powerful equipment that can provide 3D point cloud with high accuracy from the earth. Nowadays, advances in technology make the generating 3D point cloud from the digital aerial images by dense matching feasible. These point clouds represents an approximate Digital Surface Model (DSM) of the earth. The DSM contains both terrain points and off-terrain points, but the DTM contains only the terrain points. In other words, the DTM presents a bare earth without any natural and artificial objects. Generating the DTM using the DSM is a challenging topic in photogrammetry and remote sensing. In this paper, an algorithm with two independent approaches is proposed. Before beginning the process, the irregular point clouds was gridded, interpolate and convert to the image by specifying a point interval.
The first proposed approach was a progressive morphological filter that detects the off-terrain points from the DSM. This approachused the simple morphological filter in a specific procedure with four steps. In the first step, a minimal surface was generated by identifying the points which have minimum elevation in predefined scan windows. The structural element of the morphological filters should be determined. As it is a progressive filter, a vector that contains the structural elements sizes was determined in the second step. In the third step, a morphological opening was applied on the point cloud with a structural element in accordance with the produced vector in step1. For each window size in the vector, an elevation threshold was calculated by multiplying the interval distance and supplied slope parameter. Then, the difference between initial surface and the result of applying the morphological opening was computed. The points with the difference values of more than the calculated elevation threshold were selected as off-terrain points.
In the second approach, an iterative procedure was designed which was based on morphological filters. The geodesic dilation was a combination of traditional morphological filter. Although the morphological filters operated based on the image and structural element, geodesic dilation operated with two images including the mask and the marker. In geodesic dilation of size one, the marker image was dilated by an elementary isotropic structural element and the resulting image was forced to remain below the mask image. In other words, the mask image acts as a limitation for the dilated marker image. Image reconstructing by using geodesic dilation on an image was done by performing some successive geodesic dilations on the image. The results of geodesic dilation was depending on the elevation value. If this value was low, only the building ridge line was extracted andoff-ground. Moreover, if the elevation value was high, some of the bare earth was cut as off-terrain, wrongly. Hence, an iterative procedure was proposed to make the extracting of the most of the object possible. In this way, the probability of error was reduced. In each loop, the elevation value was increased and some objects was extracted using geodesic dilation. Among the extracted parcels in each loop, the parcels which have local range variation more than a threshold were selected and the others were removed. The local range variation for each point was computed by specifying a window and calculating the difference between maximum and minimum elevation value in that window. This procedure was repeated utill analyzing all of the elevation values.
Finally, the results of detecting the off-terrain points using both of approaches were accumulated to acquire the final class of off-terrain points. Then, this points were removed and the cubic interpolation was employed in order to retrieve the elevation of the lost points and to generate the DTM.
In order to analyze the performance of the proposed algorithm, 7 test areas were used. The point cloud of the areas 1, 2 and 3 were produced using dense matching of digital aerial images (Ultracam) by National GeographyOrganization of Iran. The point spacing of these areas is about 0.5 meter. The point cloud of the areas 4, 5, 6 and 7 were captured using LiDAR by International Society for Photogrammetry and Remote Sensing. The point spacing of these areas were 3, 1, 2.5 and3meters respectively. The data set covered the most of the features such as steep slopes, mixture of vegetation and buildings, bridge underpasses, roads and buildings with various roof shapes. Evaluating the performance of proposed algorithm represented the 4.85% error for extracting the off-terrain points and 0.68 meter error for generated DTM in all test areas, averagely. The evaluation results clarify the ability of proposed practical algorithm in generating the DTM using the DSM.
Vahid Sadeghi; Hamid Enayati; Hamid Ebadi
Abstract
Analyzing multi-temporal remotelysensed images is an effective technique for detecting land useand land cover changes in urban areas. Apart from thetechnique used to detect the changes, the features space has an enormous impact on the accuracy of the results. Achieving satisfactory results in detecting ...
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Analyzing multi-temporal remotelysensed images is an effective technique for detecting land useand land cover changes in urban areas. Apart from thetechnique used to detect the changes, the features space has an enormous impact on the accuracy of the results. Achieving satisfactory results in detecting changes inurban areasrequires the use of optimal spectral and spatial features (texture). Although global search is the only guarantees of achieving the optimal set of features, but it is a very timely and impractical process in practice. Data reduction techniquessuch as PCA considers the independence of the data tofind a smaller set of variables with less redundancy withoutintending to improve the CD accuracy. Difficulty in setting thebest threshold for JM distance in Separability Analysis Algorithm (SAA)reduces its efficiency. The main purpose of this paper is to select the optimaltextural and spectral features to enhance the CD accuracy usinggenetic algorithms (GA) and Bayesian classifier. To investigate the effectivenessof the proposed tecknique, a case study using IRS-P6and GeoEye1 satellite imagery taken from Sahand New Town (Northwest ofIran on July 15, 2006, andSeptember 1, 2013) was performed. All of the aforementioned methods of feature selection (PCA, SAA and proposed GA-based method) were implemented in MATLABR2013a. The results show that, textural features provides a complementary sourceof data for CD in urban areas. The results show thatfeature selection is an effective process fordetecting changes basedon textural and spectral features. Each of the techniques for selecting features has its own limitations and advantages, but in general, improve the CD accuracy. The proposed GA-based feature selectionapproach was found to be relatively effective when compared withPCA and SSA approaches. Overall accuracy and Kappa coefficient ofCD were increased from 53.66% to 88.49% and 58.94% to90.39%respectivelyusing proposed methods compared tothe use of spectral information.
Hamid Enayati; Mohsen Hasanzadeh Shahraji
Volume 22, Issue 87 , November 2013, , Pages 48-53
Abstract
Availability of spatial information and decision making based on the analyses performed by geographic information system are among the fundamental components of sustainable development. For this purpose, an organization or more is responsible for the production of spatial information in different countries. ...
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Availability of spatial information and decision making based on the analyses performed by geographic information system are among the fundamental components of sustainable development. For this purpose, an organization or more is responsible for the production of spatial information in different countries. In recent years and in the era of information technology and public access to internet, creating a platform for providing spatial information in cyberspace is considered to be much more important. As a result, the new generation of spatial information products have the capability of being presented and disseminated in the cyberspace. Some organization have proceeded and not only pioneered for dissemination of spatial information in the Internet, but also have provided users with the possibility of performing some basic spatial analyses. In developed countries, these possibilities are available and spatial information is being provided in cyberspace. In order to take advantage of developed countries knowledge and experience in producing and disseminating spatial information, it is necessary to evaluate the procedure of producing spatial data in these countries. USGS in United States of America and Survey Ordnance in UK are responsible for producing spatial data. Therefore, the present article investigates the procedure of producing spatial information.
Mojdeh Ebrahimikia; Hamid Enayati
Volume 22, SEPEHR , July 2013, , Pages 43-48
Abstract
Nowadays, energy use has increased dramatically in Iran. Gas is one of the most important energy resources. Gas use will grow in future and its pipe lines are quickly developing. The length of this gas distributing network reaches thousands of miles, so validating and timely defect detection in each ...
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Nowadays, energy use has increased dramatically in Iran. Gas is one of the most important energy resources. Gas use will grow in future and its pipe lines are quickly developing. The length of this gas distributing network reaches thousands of miles, so validating and timely defect detection in each part of pipe line is important and essential. The present article reviews current technology of leakage detection in pipe lines and points out the role of remote sensing and aerial methods in this detection.
In the first section, different leakage detection methods applied on gas pipe lines are shortly reviewed and the second section focuses on optical methods and applying remote sensing and aerial methods with the aim of decreasing costs and time of leakage detection in vast areas. Finally, different methods of leakage detection are compared in the conclusion.
Hamid Enayati
Volume 21, Issue 83 , November 2012, , Pages 86-90
Abstract
Summarizing DTM received from LIDAR data is performed to generalize (decrease details) and strengthen important features. In order to incarnate ground surface, we need to strengthen some especial features like routes and dames. The present article seeks to prepare an algorithm to extract routes. Using ...
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Summarizing DTM received from LIDAR data is performed to generalize (decrease details) and strengthen important features. In order to incarnate ground surface, we need to strengthen some especial features like routes and dames. The present article seeks to prepare an algorithm to extract routes. Using summarization algorithm, it is possible to estimate route network and LIDAR filtered cloud points.
Mojdeh Ebrahimikia; Hamid Enayati
Volume 21, Issue 81 , April 2012, , Pages 41-46
Hamid Enayati; Shima Toori
Volume 19, Issue 74 , August 2010, , Pages 75-80
Abstract
In recent years the use of aerial laser scanners for determining the topography of water beds has been introduced in the world and has found practical aspect. Depth measurement using laser scanners is a more precise, cost- efficient, and faster method than other depth-measuring methods, which is based ...
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In recent years the use of aerial laser scanners for determining the topography of water beds has been introduced in the world and has found practical aspect. Depth measurement using laser scanners is a more precise, cost- efficient, and faster method than other depth-measuring methods, which is based on accurate measurement of the travel time of two light signals transmitted to the surface and bed of water. Consequently, the use of appropriate hardware and software, in which the source of the major errors is detected and minimized, is very effective on the result of the flight. This paper presents a variety of depth-measuring laser scanners, various techniques used in each of them, and a description of how depth-measuring operations are performed. In addition to expressing the natural causes of error as well as noise causes in operational data, an algorithm for data correction and a method for noise cancellation is presented.
Hamid Enayati (Compilation and Edition)
Volume 16, Issue 64 , February 2008, , Pages 54-56
Abstract
Nowadays, accelerating the production of three-dimensional (3D) maps applying new photogrammetric methods using automated technology is not completely realized. For executives and users in the implementation of various projects that have serious need of maps, the time of production of map is a matter ...
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Nowadays, accelerating the production of three-dimensional (3D) maps applying new photogrammetric methods using automated technology is not completely realized. For executives and users in the implementation of various projects that have serious need of maps, the time of production of map is a matter of importance. Therefore, considering the issue raised, it is a question of whether another high-speed product can be produced that could be an appropriate alternative to certain maps and be able to meet the needs of users?
Hamid Enayati (Translator)
Volume 9, Issue 33 , May 2000, , Pages 47-52
Abstract
This paper reviews the application of the MATCH-T System in automatic preparation of digital elevation model using digital image processing, as well as a number of general subjects such as Feature Matching and addition of collected information. Next, the resultant precision in operation of system and ...
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This paper reviews the application of the MATCH-T System in automatic preparation of digital elevation model using digital image processing, as well as a number of general subjects such as Feature Matching and addition of collected information. Next, the resultant precision in operation of system and the cases in which we face problematic places are discussed, and finally the correction of part of automatic digital elevation model necessary for dealing with these matters is mentioned. Such corrections can make application of a Multi-Sensor method for areas of dense vegetation possible.
Hamid Enayati
Volume 4, Issue 15 , November 1995, , Pages 20-23
Abstract
Today, with the advancement of computer technology, many of the related organizations have changed the analog photogrammetric systems to Analytical system or digital analogue system in order to achieve digital maps. With the help of computers and electronic connections, it is possible to transform an ...
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Today, with the advancement of computer technology, many of the related organizations have changed the analog photogrammetric systems to Analytical system or digital analogue system in order to achieve digital maps. With the help of computers and electronic connections, it is possible to transform an analog photogrammetric system into a semi-analytic (digital) and analytical system.
The technology of transforming an analog system into a digital analog system is not very complicated; in other words, it does not require major changes in the photogrammetric device, and merely by installing a series of encoder on the machine, it is possible to convert the mechanical motion (z, y and x) of the measurement system to electronic pulses. These pulses can be digitized by a connector (connector board between the photogrammetric system and the computer).
It is possible through a brief examination to convert linear movement to a set of digits by using a suitable computer and installing connecting board inside it, and by employing an appropriate software that is compatible with the mentioned board. However, in the case of an analytical system, it is necessary to remove certain mechanical parts of the device. In this case, the connection between the device and the computer is bilateral, so it is necessary to use a series of engines in the circuit of the device, so that the visual radii (spatial rods) be converted from mechanical state with physical function to analytical picture radii. One of the devices that has been transformed into analytical systems is B8.
