University of TehranEarth Observation and Geomatics Engineering2588-43521120170601On the evaluation of second order phase statistics in SAR interferogram stacks1156386510.22059/eoge.2017.63865.1016ENSamiSamiei-EsfahanyDepartment of Geoscience and Remote Sensing, Delft University of Technology, Delft, the NetherlandsRamonHanssenDepartment of Geoscience and Remote Sensing, Delft University of Technology, Delft, the NetherlandsJournal Article20161120During the last decades, time-series interferometric synthetic aperture radar (InSAR) has been emerged as a powerful technique to measure various surface deformation phenomena of the earth. The multivariate statistics of interferometric phase stacks plays an important role in the performance of different InSAR methodologies and also in the final quality description of InSAR derived products. The multivariate phase statistics are ideally described by a joint probability distribution function (PDF) of interferometric phases, whose closed-form evaluation in a generic form is very complicated and is not found in the literature. Focusing on the first two statistical moments, the stack phase statistics can be effectively described by a full (co)variance matrix. Although a closed-form expression of interferometric phase variances has been derived in literature for single-looked pixels, there is no such an expression for neither the variances of the multilooked pixels nor the covariances among interferometric phases. This paper presents two different approaches for evaluation of the full covariance matrix: one based on the numerical Monte-Carlo integration and the other based on an analytical approximation using nonlinear error propagation. We first, clarify on the noise components that are the subject of statistical models of this paper. Then, the complex statistics in SAR stacks and the phase statistics in a single interferogram are reviewed, followed by the phase statistics in InSAR stacks in terms of second statistical moments. The Monte-Carlo approach and the derivation of an analytical closed-form evaluation of InSAR second-order phase statistics are then introduced in details. Finally, the two proposed methods are validated against each other.https://eoge.ut.ac.ir/article_63865_ddea1d650b33f5a40e9d553f47778305.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43521120170601Automatic generation of E-LOD1 from LiDAR point cloud16256386610.22059/eoge.2017.230917.1004ENMaryamSajadianSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranHosseinArefiSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranJournal Article20161204LiDAR as a powerful system has been known in remote sensing techniques for 3D data acquisition and modeling of the earth’s surface. 3D reconstruction of buildings, as the most important component of 3D city models, using LiDAR point cloud has been considered in this study and a new data-driven method is proposed for 3D buildings modeling based on City GML standards. In particular, this paper focuses on the generation of an Enhanced Level of Details 1 (E-LOD1) of buildings containing multi-level flat-roof structures. An important primary step to reconstruct the buildings is to identify and separate building points from other points such as ground and vegetation points. For this, a multi-agent strategy is proposed for simultaneous extraction of buildings and segmentation of roof points from LiDAR point cloud. Next, using a new method named “Grid Erosion” the edge points of roof segments are detected. Then, a RANSAC-based technique is employed for approximation of lines. Finally, by modeling of the rooves and walls, the 3D buildings model is reconstructed. The proposed method has been applied on the LiDAR data over the Vaihingen city, Germany. The results of both visual and quantitative assessments indicate that the proposed method could successfully extract the buildings from LiDAR data and generate the building models. The main advantage of this method is the capability of segmentation and reconstruction of the flat buildings containing parallel roof structures even with very small height differences (e.g. 50 cm). In model reconstruction step, the dominant errors are close to 30 cm that are calculated in horizontal distance. https://eoge.ut.ac.ir/article_63866_833ade1735f2c2f1a5aa81e615cec8f8.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43521120170601Presenting an extended evaluation framework for building detection algorithms using high spatial resolution images26356386710.22059/eoge.2017.63867.1000ENImanKhosraviDepartment of Surveying Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, IranMehdiMomeniDepartment of Surveying Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, IranJournal Article20161202This paper aims to provide an extended evaluation framework for building detection algorithms using a diverse set of High Spatial Resolution (HSR) images. The HSR images utilized in this paper were chosen from different places and different sensors, and based on several important challenges in an urban area such as building alignment, density, shape, size, color, height, and imaging angle. The classical evaluation metrics such as detection rate, reliability, false positive rate, and overall accuracy only demonstrate the performance evaluation of an algorithm in relation to the buildings and cannot interpret the mentioned challenges. The extended evaluation framework proposed in this paper composed several extended metrics for performance evaluation of building detection algorithms in relation to these challenges in addition to the classical metrics. The paper intends to declare that the success or failure metrics of a building detection algorithm can have more varieties. In fact, a building detection algorithm may be successful at one or several metrics, whilst it may be unsuccessful at the other metrics.https://eoge.ut.ac.ir/article_63867_0d59d075ead4bb40030c3dd9cd28704c.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43521120170601Monitoring of sea surface currents by using sea surface temperature and satellite altimetry data in the Caspian Sea36466386810.22059/eoge.2017.226309.1001ENEmadGhalenoeiDepartment of Geomatics Engineering, University of Calgary, Calgary, Alberta, CanadaMahdiHasanlouSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-7254-4475Journal Article20161225The spatial and temporal monitoring of Sea Surface Currents (SSCs) has a crucial importance in the study of the strategic environmental assessments. Although the geostrophic currents have been calculated by altimetry data, in this study, we show these currents have an appropriate correlation with the Sea Surface Temperature (SST). Two different methods are used to estimate the SSCs. First, we propose a model for calculating the geostrophic currents via removing the effects of Mean Sea Surface (MSS) from the Sea Surface Height (SSH), and second, the optical flow method (Horn-Schunck) has been applied to two sequential SST imageries to extract the SST patterns movements. In the first part of results, we map the geostrophic currents on the SST surface to explain the physical events like eddies, and in the second part, we calculate the optical flow and compare them with the geostrophic currents. Because there are no appropriate validation currents in the Caspian Sea, we use the SST products corrected by NASA and no changes have been performed on them in this study. We conclude that both optical flow and geostrophic currents show the same results but in different schemes. The schematic results shown in this article can provide new and small-scale phenomena to see that movements of sea surface have meaningful aspects.https://eoge.ut.ac.ir/article_63868_39877ebe0240ed91ee143bd4023aa73d.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43521120170601Non-rigid star pattern recognition for preparation of IOD’s observations47576386910.22059/eoge.2017.220378.1005ENMonaKosarySchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran.SaeedFarzanehSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran.Journal Article20170119The invention of electro-optical devices at the beginning of the 21st century was really a rebirth in the geodetic astronomy. Today, the digital cameras with relatively high geometric and radiometric accuracy have opened a new insight in the satellite attitude determination and the study of the Earth's surface geometry and physics of its interior, i.e., the computation of astronomical coordinates and the vertical deflection components. In the automatic star detection, high precision and reliability in extraction of the star's centers from the captured images and corresponding them with the astronomical coordinates is the most important point. In this article, the probabilistic method has been applied for the star matching. The registration is treated as a Maximum Likelihood estimation problem with the motion constraint over the velocity field such that the catalogue coordinates set moves coherently to align with the pixels coordinates set. The motion coherence has been constrained to the matching problem and derives a solution of regularized ML estimation through the vibrational approach, which leads to an elegant kernel form. In this way, the EM algorithm has been applied for the penalized ML optimization with deterministic annealing. This method finds correspondence between stars coordinates in catalogue and image without making any prior assumption of the transformation model except the motion coherence. This method can estimate the gnomonic transformations between the catalogue and the image and is shown to be accurate and robust in the presence of image noise and outliers. The result of evaluation by proposed algorithm on the image taken by the TZK2-D camera, indicated that the point matching is achieved by standard deviation less than 0.001 pixel.https://eoge.ut.ac.ir/article_63869_c866f9e1363a10e7919b3e979165d9ec.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43521120170601A new approach based on the RFS method for evaluating popularity of top open-source GIS software packages using user comments in forums58706387010.22059/eoge.2017.237260.1009ENMostafaGhodousiDepartment of GIS, Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, IranAbolghasemSadeghi-NiarakiDepartment of GIS, Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, IranBahramSaeidianDepartment of GIS, Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, IranJournal Article20170115Open-source software packages have various functions. An important factor is choosing the right package. On the other hand, no organization is responsible for these packages. In this regard, using the users' experience can be a good option or method in selecting the right package. There are many online forums which users discuss their experiences about the open-source software packages. Analyzing the data from these forums can help users to select the appropriate packages. This paper evaluates three top open-source software packages, namely QGIS, GRASS, and gvSIG, based on online forums covering spatial issues. In addition, the paper compares software packages and forums based on users' behaviors through a new approach, namely a Recency-Frequency-Satisfaction (RFS) method based on Recency-Frequency-Monetary (RFM) in Customer relationship management (CRM). Finally, the paper analyzes the procedure for using software packages by users’ comments by year. The results show that QGIS was used more than the other two and that the procedure was in ascending order for years.https://eoge.ut.ac.ir/article_63870_af45a9bd6bdd4d530b89d0c44ada8420.pdf