bluuebunny/crossref_metadata_2025 huggingface dataset:
A MODIFIED POLARIMETRIC DECOMPOSTION FOR APPLICABILTY IN COMPLEX AGRICULTURAL ENVIRONMENT
Authors: Dehghan-Soraki Y. , Saha S. K. , Kumari M.
Published: September 2013

Abstract. A new model based decomposition on coherency matrix is demonstrated for the analysis of polarimetric SAR data. In this method a first order Bragg scattering model was fitted to explain the Bragg scatter from a moderately rough surface; randomly oriented dipole for explaining the volume scattering from a canopy layer; and a rotated dihedral model for pair of orthogonal scatters in Copol and Crosspol channels. The distinctive nature of this model is: fitting a rotated dihedral model to the coherency matrix which provides an ability to distinguish the same double-bounce mechanism occurs in small size bunded cropland and in orthogonal manmade structures. The model is applied to Radarsat-2 full polarimetric data which was acquired in a complex agricultural landscape. The result from decomposition was quite effective in reducing the scattered double-bounce pollutions from bunded trees surrounding croplands with extra enhancement in decomposition of orthogonal as well as oblique manmade structures.
A New Developed GIHS-BT-SFIM Fusion Method Based On Edge and Class Data
Authors: Dehnavi S. , Mohammadzadeh A.
Published: September 2013

Abstract. The objective of image fusion (or sometimes pan sharpening) is to produce a single image containing the best aspects of the source images. Some desirable aspects are high spatial resolution and high spectral resolution. With the development of space borne imaging sensors, a unified image fusion approach suitable for all employed imaging sources becomes necessary. Among various image fusion methods, intensity-hue-saturation (IHS) and Brovey Transforms (BT) can quickly merge huge amounts of imagery. However they often face color distortion problems with fused images. The SFIM fusion is one of the most frequently employed approaches in practice to control the tradeoff between the spatial and spectral information. In addition it preserves more spectral information but suffer more spatial information loss. Its effectiveness is heavily depends on the filter design. In this work, two modifications were tested to improve the spectral quality of the images and also investigating class-based fusion results. First, a Generalized Intensity-Hue-Saturation (GIHS), Brovey Transform (BT) and smoothing-filter based intensity modulation (SFIM) approach was implemented. This kind of algorithm has shown computational advantages among other fusion methods like wavelet, and can be extended to different number of bands as in literature discussed. The used IHS-BT-SFIM algorithm incorporates IHS, IHS-BT, BT, BT-SFIM and SFIM methods by two adjustable parameters. Second, a method was proposed to plus edge information in previous GIHS_BT_SFIM and edge enhancement by panchromatic image. Adding panchromatic data to images had no much improvement. Third, an edge adaptive GIHS_BT_SFIM was proposed to enforce fidelity away from the edges. Using MS image off edges has shown spectral improvement in some fusion methods. Fourth, a class based fusion was tested, which tests different coefficients for each method due to its class. The best parameters for vegetated areas was k1 = 0.6, k2 = 0.8; and for urban region it was k1 = 0.4, k2 = 0.4. Results might be useful for future studies on fusion methods and their generalization.
3D OBJECT COORDINATES EXTRACTION BY RADARGRAMMETRY AND MULTI STEP IMAGE MATCHING
Authors: Eftekhari A. , Ghannadi M. A. , Motagh M. , Saadat Seresht M.
Published: September 2013

Abstract. Nowadays by high resolution SAR imaging systems as Radarsat-2, TerraSAR-X and COSMO-skyMed, three-dimensional terrain data extraction using SAR images is growing. InSAR and Radargrammetry are two most common approaches for removing 3D object coordinate from SAR images. Research has shown that extraction of terrain elevation data using satellite repeat pass interferometry SAR technique due to atmospheric factors and the lack of coherence between the images in areas with dense vegetation cover is a problematic. So the use of Radargrammetry technique can be effective. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-stage algorithm founded on the combination of feature based and area based image matching. Then the RPCs that calculate for each images use for extracting 3D coordinate in matched points. At the end, the coordinates calculating that compare with coordinates extracted from 1 meters DEM. The results show root mean square errors for 360 points are 3.09 meters. We use a pair of spotlight TerraSAR-X images from JAM (IRAN) in this article.
DIGITAL ELEVATION MODEL APPROXIMATION FROM STREAM NETWORKS: A REVERSED APPROACH
Authors: Ghandehari M.
Published: September 2013

Abstract. The delineation of stream networks and catchment areas is one the most common applications of Digital Elevation Models (DEMs). In this article, an innovative reversed approach for the approximation of DEMs from stream networks is presented. As a fundamental preprocessing step, the stream networks are sampled with a set of points. Then, a Delaunay triangulation and Voronoi diagram are used to extract the skeleton (medial axis) of stream networks as an approximation of the catchment areas. The catchment areas contain implicit information that is representative of the terrain, and so the elevation points can be extracted along the catchment area boundaries. Furthermore, we employ the stream orders to enrich the elevation data set. Finally, the elevation points are converted into an elevation grid through a raster interpolation method. While an approximation approach, the results show that the proposed method achieves the desired results.
UNCERTAIN TRAINING DATA EDITION FOR AUTOMATIC OBJECT-BASED CHANGE MAP EXTRACTION
Authors: Hajahmadi S. , Mokhtarzadeh M. , Mohammadzadeh A. , Valadanzouj M. J.
Published: September 2013

Abstract. Due to the rapid transformation of the societies, and the consequent growth of the cities, it is necessary to study these changes in order to achieve better control and management of urban areas and assist the decision-makers. Change detection involves the ability to quantify temporal effects using multi-temporal data sets. The available maps of the under study area is one of the most important sources for this reason. Although old data bases and maps are a great resource, it is more than likely that the training data extracted from them might contain errors, which affects the procedure of the classification; and as a result the process of the training sample editing is an essential matter. Due to the urban nature of the area studied and the problems caused in the pixel base methods, object-based classification is applied. To reach this, the image is segmented into 4 scale levels using a multi-resolution segmentation procedure. After obtaining the segments in required levels, training samples are extracted automatically using the existing old map. Due to the old nature of the map, these samples are uncertain containing wrong data. To handle this issue, an editing process is proposed according to K-nearest neighbour and k-means algorithms. Next, the image is classified in a multi-resolution object-based manner and the effects of training sample refinement are evaluated. As a final step this classified image is compared with the existing map and the changed areas are detected.
THE INVESTIGATION OF SENSITIVITY OF SVM CLASSIFIER RESPECT TO THE NUMBER OF FETURES AND THE NUMBER OF TRAINING SAMPLES
Authors: Imani M. , Ghassemian H.
Published: September 2013

Abstract. Supervised classification of hyperspectral images is a difficult task due to the unbalance between the high dimensionality of the data and the limited availability of labeled training samples. Recently support vector machine (SVM), has received considerable attention for classifying high dimensional data and is applied successfully for classification of hyperspectral images because it discriminates classes by a geometrical criterion not by statistical criteria. In this paper, we investigate sensitivity of SVM classifier respect to two factors. The first factor is the dimensional of data (the number of features) and the second factor is the number of training samples. We evaluate the effect of these factors on the performance of classification in the point of view both accuracy and reliability. Experiments are carried out on the three different common used hyperspectral datasets, Indian pines, Pavia University and Salinas.
USE OF UBIQUITOUS TECHNOLOGIES IN MILITARY LOGISTIC SYSTEM IN IRAN
Authors: Jafari P. , Sadeghi-Niaraki A.
Published: September 2013

Abstract. This study is about integration and evaluation of RFID and ubiquitous technologies in military logistic system management. Firstly, supply chain management and the necessity of a revolution in logistic systems especially in military area, are explained. Secondly RFID and ubiquitous technologies and the advantages of their use in supply chain management are introduced. Lastly a system based on these technologies for controlling and increasing the speed and accuracy in military logistic system in Iran with its unique properties, is presented. The system is based on full control of military logistics (supplies) from the time of deployment to replenishment using sensor network, ubiquitous and RFID technologies.
SPATIOTEMPORAL MODELLING OF DUST STORM SOURCES EMISSION IN WEST ASIA
Authors: Khodabandehloo E. , Alimohamdadi A. , Sadeghi-Niaraki A. , Darvishi Boloorani A. , Alesheikh A. A.
Published: September 2013

Abstract. Dust aerosol is the largest contributor to aerosol mass concentrations in the troposphere and has considerable effects on the air quality of spatial and temporal scales. Arid and semi-arid areas of the West Asia are one of the most important regional dust sources in the world. These phenomena directly or indirectly affecting almost all aspects life in almost 15 countries in the region. So an accurate estimate of dust emissions is very crucial for making a common understanding and knowledge of the problem. Because of the spatial and temporal limits of the ground-based observations, remote sensing methods have been found to be more efficient and useful for studying the West Asia dust source. The vegetation cover limits dust emission by decelerating the surface wind velocities and therefore reducing the momentum transport. While all models explicitly take into account the change of wind speed and soil moisture in calculating dust emissions, they commonly employ a "climatological" land cover data for identifying dust source locations and neglect the time variation of surface bareness. In order to compile the aforementioned model, land surface features such as soil moisture, texture, type, and vegetation and also wind speed as atmospheric parameter are used. Having used NDVI data show significant change in dust emission, The modeled dust emission with static source function in June 2008 is 17.02 % higher than static source function and similar result for Mach 2007 show the static source function is 8.91 % higher than static source function. we witness a significant improvement in accuracy of dust forecasts during the months of most soil vegetation changes (spring and winter) compared to outputs resulted from static model, in which NDVI data are neglected.
THE DESIGN AND IMPLEMENTATION OF AN OPTICAL ASTRONOMICAL SATELLITE TRACKING SYSTEM
Authors: Samadzadegan F. , Alidoost F.
Published: September 2013

Abstract. This paper presents a satellite tracking method based on optical celestial images. The proposed method is composed of two acquiring modes that are called Sidereal Stare Mode (SSM) and Track Rate Mode (TRM). To track the unknown satellites, first of all the entire of the sky is observed and the primary knowledge of the satellite location is predicted in SSM. Then, the measured pointing data is calculated and used by the telescope to acquire the satellite tracking images at the appropriate time. The framework of SSM contains main steps such as the image correction due to the noise and the image background by applying the iterative filtering methods, the star detection and removal using a double gate filter and PSF concepts, the star identification for image calibration based on a star catalogue, the streak detection of the satellite using the matched filter and finally, the extraction of the celestial coordinate of the satellite as a predicted position. In TRM, the group of star streaks should be identified in the free background image. Then, Fast Fourier Transformation (FFT) is applied and the characteristic of star streaks are extracted. Finally, the centroid of the satellite is estimated precisely by applying a binary mask and the right ascension and declination of it is calculated using astrometric transformation parameters. In this study, the searching and tracking algorithms is applied on the simulation images to detect and identify the satellite position in the sky. Therefore, a telescope along with a CCD camera is simulated to generate sequences images using the well-known star catalogues, the optical and orbital parameters. The precise celestial coordinate of a real satellite and two fictitious satellites are obtained from simulated images. The study results show that the accuracy of the satellite estimated position after star calibration is better than 5 arc seconds and the satellites tracking accuracy is around 1–3 arc seconds.
INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) TECHNOLOGY AND GEOMORPHOLOGY INTERPRETATION
Authors: Maghsoudi M. , Hajizadeh A. , Nezammahalleh M. A. , SeyedRezai H. , Jalali A. , Mahzoun M.
Published: September 2013

Abstract. Geomorphology is briefly the study of landforms and their formative processes on the surface of the planet earth as human habitat. The landforms evolution and the formative processes can best be studied by technologies with main application in study of elevation. Interferometric Synthetic Aperture Radar (InSAR) is the appropriate technology for this application. With phase differences calculations in radar waves, the results of this technology can extensively be interpreted for geomorphologic researches. The purpose of the study is to review the geomorphologic studies using InSAR and also the technical studies about InSAR with geomorphologic interpretations. This study states that the InSAR technology can be recommended to be employed as a fundamental for geomorphology researches.
IMAGE ENHANCEMENT AND SPECKLE REDUCTION OF FULL POLARIMETRIC SAR DATA BY GAUSSIAN MARKOV RANDOM FIELD
Authors: Mahdian M. , Motagh M. , Akbari V.
Published: September 2013

Abstract. In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR) data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF) has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF), which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.
INVESTIGATION OF POLARIZATION PHASE DIFFERENCE RELATED TO FOREST FIELDS CHARACTERIZATIONS
Authors: Majidi M. , Maghsoudi Y.
Published: September 2013

Abstract. The information content of Synthetic Aperture Radar (SAR) data significantly included in the radiometric polarization channels, hence polarimetric SAR data should be analyzed in relation with target structure. The importance of the phase difference between two co-polarized scattered signals due to the possible association between the biophysical parameters and the measured Polarization Phase Difference (PPD) statistics of the backscattered signal recorded components has been recognized in geophysical remote sensing. This paper examines two Radarsat-2 images statistics of the phase difference to describe the feasibility of relationship with the physical properties of scattering targets and tries to understand relevance of PPD statistics with various types of forest fields. As well as variation of incidence angle due to affecting on PPD statistics is investigated. The experimental forest pieces that are used in this research are characterized white pine (Pinus strobus L.), red pine (Pinus resinosa Ait.), jack pine (Pinus banksiana Lamb.), white spruce (Picea glauca (Moench Voss), black spruce (Picea mariana (Mill) B.S.P.), poplar (Populus L.), red oak (Quercus rubra L.) , aspen and ground vegetation. The experimental results show that despite of biophysical parameters have a wide diversity, PPD statistics are almost the same. Forest fields distributions as distributed targets have close to zero means regardless of the incidence angle. Also, The PPD distribution are function of both target and sensor parameters, but for more appropriate examination related to PPD statistics the observations should made in the leaf-off season or in bands with lower frequencies.
HEAT OF MARS IS LOVE OF LIFE?! TWO WAYS TO LOOK AT MARS
Authors: Alavipanah S. K. , Van Gasselt S. , Mulder N. J. , Nezammahalleh M. A.
Published: September 2013

Abstract. Earth and Mars travel in neighboring orbits around the sun. Both are rocky planets, but only the earth has the conditions to support life on. Is such a great difference due to their surface temperatures? It is obvious that the surface temperatures of these planets are governed by two factors of: (a) the amount of energy they receive from the sun and, (b) the composition of their atmospheres. If it is true, we must focus more on the Thermal Remote Sensing on Mars. Since heat is an important factor in any physical, chemical and biological study, it can be said that the heat in the form of love and psychological processes is effective for these studies. In study about life on another planet, not only the thermal characteristics are essential but love or passion in Scientists' efforts that are related to inner heat should also be considered. Therefore, in this paper we review the studies on Mars with the emphasis on the temperature. We consider science, art, literature, and technology as well as any things related to the heat including ice melting, volcanology, soil, morphology, and geothermal. As we believe that it must be bridged between mental and science gaps, shouldn't we make both the art and the science convergent? Therefore, we have used different scientific and art resources to make the role of heat in the Mars clear. We are seeking to answer the question whether the heat can be as a common factor in the researches.
GIS BASED SYSTEM FOR POST-EARTHQUAKE CRISIS MANAGMENT USING CELLULAR NETWORK
Authors: Raeesi M. , Sadeghi-Niaraki A.
Published: September 2013

Abstract. Earthquakes are among the most destructive natural disasters. Earthquakes happen mainly near the edges of tectonic plates, but they may happen just about anywhere. Earthquakes cannot be predicted. Quick response after disasters, like earthquake, decreases loss of life and costs. Massive earthquakes often cause structures to collapse, trapping victims under dense rubble for long periods of time. After the earthquake and destroyed some areas, several teams are sent to find the location of the destroyed areas. The search and rescue phase usually is maintained for many days. Time reduction for surviving people is very important. A Geographical Information System (GIS) can be used for decreasing response time and management in critical situations. Position estimation in short period of time time is important. This paper proposes a GIS based system for post–earthquake disaster management solution. This system relies on several mobile positioning methods such as cell-ID and TA method, signal strength method, angel of arrival method, time of arrival method and time difference of arrival method. For quick positioning, the system can be helped by any person who has a mobile device. After positioning and specifying the critical points, the points are sent to a central site for managing the procedure of quick response for helping. This solution establishes a quick way to manage the post–earthquake crisis.
AUTOMATIC 3D MAPPING USING MULTIPLE UNCALIBRATED CLOSE RANGE IMAGES
Authors: Rafiei M. , Saadatseresht M.
Published: September 2013

Abstract. Automatic three-dimensions modeling of the real world is an important research topic in the geomatics and computer vision fields for many years. By development of commercial digital cameras and modern image processing techniques, close range photogrammetry is vastly utilized in many fields such as structure measurements, topographic surveying, architectural and archeological surveying, etc. A non-contact photogrammetry provides methods to determine 3D locations of objects from two-dimensional (2D) images. Problem of estimating the locations of 3D points from multiple images, often involves simultaneously estimating both 3D geometry (structure) and camera pose (motion), it is commonly known as structure from motion (SfM). In this research a step by step approach to generate the 3D point cloud of a scene is considered. After taking images with a camera, we should detect corresponding points in each two views. Here an efficient SIFT method is used for image matching for large baselines. After that, we must retrieve the camera motion and 3D position of the matched feature points up to a projective transformation (projective reconstruction). Lacking additional information on the camera or the scene makes the parallel lines to be unparalleled. The results of SfM computation are much more useful if a metric reconstruction is obtained. Therefor multiple views Euclidean reconstruction applied and discussed. To refine and achieve the precise 3D points we use more general and useful approach, namely bundle adjustment. At the end two real cases have been considered to reconstruct (an excavation and a tower).
FUSION OF HYPERSPECTRAL AND PANCHROMATIC IMAGES USING SPECTRAL UNMIXING RESULTS
Authors: Rajabi R. , Ghassemian H.
Published: September 2013

Abstract. Hyperspectral imaging, due to providing high spectral resolution images, is one of the most important tools in the remote sensing field. Because of technological restrictions hyperspectral sensors has a limited spatial resolution. On the other hand panchromatic image has a better spatial resolution. Combining this information together can provide a better understanding of the target scene. Spectral unmixing of mixed pixels in hyperspectral images results in spectral signature and abundance fractions of endmembers but gives no information about their location in a mixed pixel. In this paper we have used spectral unmixing results of hyperspectral images and segmentation results of panchromatic image for data fusion. The proposed method has been applied on simulated data using AVRIS Indian Pines datasets. Results show that this method can effectively combine information in hyperspectral and panchromatic images.
ASSESMENT AND EVLUATION OF THE IMPACT OF USING POLSAR IMAGERIES WITH DIFERENT INCIDENT ANGLES IN FOREST CLASSIFICATION
Authors: Ranjbar K. , Maghsoudi Y. , Sahebi M. R.
Published: September 2013

Abstract. Forests are a dominant biome of the earth and have an important impact on its economic and environmental well-being. Forestry applications of radar remote sensing are addressed in the context of both forest management and ecosystem understanding, modelling and monitoring. Nowadays, radar remote sensing is being used for a lot of applications in various fields. Due to the applications of polarimetric radar in recent decades, many researchers have tended to this field. One of the main advantages of SAR images is that these images are independent over the time (day and night) and weather condition. The polarimetric SAR (POLSAR) images compared with other remote sensing images are more informative. Classification of radar images is a way by which we can separate different types of forest species. In addition to the main characteristics of the target, the backscatter from a SAR image is widely dependant on various radar system parameters. One of these system parameters is the incident angle of the radar system. In this paper, the impact of using PolSAR images with different incidence angles for the classification of forest areas is investigated. Two polSAR images with different incident angles taken by RADARSAT-2 in fine quad polarized mode (FQ4 and FQ18) have been used in this study. The study area is located in the Petawawa Research Forest (PRF) near Chalk River, Ontario, Canada The methodology of this paper contains three steps: (1) preprocessing, (2) wishart classification and (3) evaluating & analyzing the results. The preprocessing steps consist of the speckle noise filtering, covariance matrix extraction and georeferencing. In the second step, each incidence angle image was classified by using the supervised Wishart classification. The Wishart classification method has the capability of having multiple images at the same time. Thus, in the next experiment the classification was performed using both incidence angle images. Finally, the obtained results from each class and the classification results in each of three cases were evaluated and analyzed. The results showed that Wishart classification provides an overall accuracy of % 67.17 using the lower incidence angle PolSAR image and % 65.38 for the higher incidence angle POLSAR image. Also, the overall accuracy of the simultaneous classification by using the extracted covariance matrix from both images is 72.63 %. Those results showed a better performance of the image with lower incident angle compared to that of an image with higher incident angle for forest classification. It is also shown that combining extracted covariance matrix from the FQ4 image with extracted covariance matrix from the FQ18 image can significantly improve the classification accuracy (overall accuracy).
WIRELESS SENSOR NETWORKS AND FUSION OF CONTEXTUAL INFORMATION FOR WEATHER OUTLIER DETECTION
Authors: Amidi A. , Hamm N. A. S. , Meratnia N.
Published: September 2013

Abstract. Weather stations are often expensive hence it may be difficult to obtain data with a high spatial coverage. A low cost alternative is wireless sensor network (WSN), which can be deployed as weather stations and address the aforementioned shortcoming. Due to imperfect sensors in WSNs context, provided raw data may be drawn in from of a low quality and reliability level, expectedly that is an emergence of applying outlier detection methods. Outliers may include errors or potentially useful information called events. In this research, forecast values as contextual information are utilized for weather outlier detection. In this paper, outliers are identified by comparing the patterns of WSN and forecasts. With that approach, temporal outliers are detected with respect to slopes of the WSNs and forecasts in the presence of pre-defined tolerance. The experimental results from the real data-set validate the applicability of using contextual information in the context of WSNs for outlier detection in terms of accuracy and energy efficiency.
MAPPING FROM SPACE – ONTOLOGY BASED MAP PRODUCTION USING SATELLITE IMAGERIES
Authors: Asefpour Vakilian A. , Momeni M.
Published: September 2013

Abstract. Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83 %. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7 %. Results showed that vegetation cover and water features have been extracted completely (100 %) and about 71 % of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.
DIAGNOSIS AND REPAIR OF RANDOM NOISE IN THE SENSOR'S CHRIS-PROBA
Authors: Mobasheri M. R. , Zendehbad S. A.
Published: September 2013

Abstract. The CHRIS sensor on the PROBA-1 satellite has imaged as push-broom way, 18 meter spatial resolution and 18 bands (1.25–11 nm) spectral resolution from earth since 2001. After 13 years of the life of the sensor because of many reasons including the influence of solar radiation and magnetic fields of Earth and Sun, behaviour of the response function of the detector exit from calibration mode and performance of some CCDs has failed. This has caused some image information in some bands have been deleted or invalid. In some images, some dark streaks or light bands in different locations need to be created to identify and correct. In this paper all type of noise which likely impact on sensor data by CHRIS from record and transmission identified, calculated and formulated and method is presented through modifying. To do this we use the In-fight and On-ground measurements parameters. Otherwise creation of noise in images is divided into horizontal and vertical noise. Due to the random noise is created in different bands and different locations, those images in which noise is observed is used. In this paper, techniques to identify and correct the dark or pale stripe detail of the images are created. Finally, the noisy images were compared before and after the reform and effective algorithms to detect and correct errors were demonstrated.
MAPPING FROM SPACE – ONTOLOGY BASED MAP PRODUCTION USING SATELLITE IMAGERIES
Authors: Asefpour Vakilian A. , Momeni M.
Published: September 2013

Abstract. Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83%. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7%. Results showed that vegetation cover and water features have been extracted completely (100%) and about 71% of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.
EVALUATION AND ANALYSIS OF A PARAMETRIC APPROACH FOR SIMULTANEOUS SPACE RESECTION-INTERSECTION OF HIGH RESOLUTION SATELLITE IMAGES WITHOUT USING GROUND CONTROL POINTS
Authors: Azizi A. , Afsharnia H. , Hadavand A.
Published: September 2013

Abstract. This paper initially proves mathematically that the solution of the relative orientation of the push broom stereo images leads to a set of ill-posed system of observation equations which means no relative orientation for this kind of imageries is possible. It is then demonstrated that the only way to bypass the inherent rank deficiency in the system of the relative orientation equations, is to incorporate fictitious data as known values into the equations. The proposed solutions given so far for the relative orientation of the push-broom images use a physical collinearity model and incorporate the so-called Virtual Ground Control points (VCPs) to bypass the ill-conditioning problem. The main objective of this paper is to replace the physical collinearity model with the 3D-affine transformation and use fictitious height information for the solution of the relative orientation of the push-broom images. The main advantage gained by this replacement model is its independence with respect to the sensor's interior orientation parameters and also the simplicity of its functional model. Cartosat-1 P5 stereo images over a highly mountainous terrain are used to evaluate the potential of the 3D-affine for the solution of the aforementioned problem. The tests conducted in this research work indicate that the 3D-affine model with fictitious information can eliminate the ill-posed problem associated with the relative orientation of the push-broom images. However, the main disadvantage of the 3D-affine model is the fact that it imposes certain level of model deformation into the generated relative DEM. This paper also demonstrates the influence of the inclusion of the perspective-to-parallel transformation coefficient into the 3D-affine resection-intersection equations. The main contribution of this paper is, therefore, the solution of the relative orientation of the push-broom images with the 3D-affine model using fictitious information. The superimposed height deformation on the generated relative DEM is also analyzed.
A CLUSTERING-BASED APPROACH FOR EVALUATION OF EO IMAGE INDEXING
Authors: Bahmanyar R. , Rigoll G. , Datcu M.
Published: September 2013

Abstract. The volume of Earth Observation data is increasing immensely in order of several Terabytes a day. Therefore, to explore and investigate the content of this huge amount of data, developing more sophisticated Content-Based Information Retrieval (CBIR) systems are highly demanded. These systems should be able to not only discover unknown structures behind the data, but also provide relevant results to the users' queries. Since in any retrieval system the images are processed based on a discrete set of their features (i.e., feature descriptors), study and assessment of the structure of feature space, build by different feature descriptors, is of high importance. In this paper, we introduce a clustering-based approach to study the content of image collections. In our approach, we claim that using both internal and external evaluation of clusters for different feature descriptors, helps to understand the structure of feature space. Moreover, the semantic understanding of users about the images also can be assessed. To validate the performance of our approach, we used an annotated Synthetic Aperture Radar (SAR) image collection. Quantitative results besides the visualization of feature space demonstrate the applicability of our approach.
USING AEROSOL REFLECTANCE FOR DUST DETECTION
Authors: Bahramvash Shams S. , Mohammadzade A.
Published: September 2013

Abstract. In this study we propose an approach for dust detection by aerosol reflectance over arid and urban region in clear sky condition. In urban and arid areas surface reflectance in red and infrared spectral is bright and hence shorter wavelength is required for this detections. Main step of our approach can be mentioned as: cloud mask for excluding cloudy pixels from our calculation, calculate Rayleigh path radiance, construct a surface reflectance data base, estimate aerosol reflectance, detect dust aerosol, dust detection and evaluations of dust detection. Spectral with wavelength 0.66, 0.55, 0.47 μm has been used in our dust detection. Estimating surface reflectance is the most challenging step of obtaining aerosol reflectance from top of atmosphere (TOA) reflectance. Hence for surface estimation we had created a surface reflectance database of 0.05 degree latitude by 0.05 degree longitude resolution by using minimum reflectivity technique (MRT). In order to evaluate our dust detection algorithm MODIS aerosol product MOD04 and common dust detection method named Brightness Temperature Difference (BTD) had been used. We had implemented this method to Moderate Resolution Imaging Spectroradiometer (MODIS) image of part of Iran (7 degree latitude and 8 degree longitude) spring 2005 dust phenomenon from April to June. This study uses MODIS LIB calibrated reflectance high spatial resolution (500 m) MOD02Hkm on TERRA spacecraft. Hence our dust detection spatial resolution will be higher spatial resolution than MODIS aerosol product MOD04 which has 10 × 10 km2 and BTD resolution is 1 km due to the band 29 (8.7 μm), 31 (11 μm), and 32 (12 μm) spatial resolutions.
CLASSIFIER FUSION OF HYPERSPECTRAL AND LIDAR REMOTE SENSING DATA FOR IMPROVEMENT OF LAND COVER CLASSIFCATION
Authors: Bigdeli B. , Samadzadegan F. , Reinartz P.
Published: September 2013

Abstract. The interest in the joint use of remote sensing data from multiple sensors has been remarkably increased for classification applications. This is because a combined use is supposed to improve the results of classification tasks compared to single-data use. This paper addressed using of combination of hyperspectral and Light Detection And Ranging (LIDAR) data in classification field. This paper presents a new method based on the definition of a Multiple Classifier System on Hyperspectral and LIDAR data. In the first step, the proposed method applied some feature extraction strategies on LIDAR data to produce more information in this data set. After that in second step, Support Vector Machine (SVM) applied as a supervised classification strategy on LIDAR data and hyperspectal data separately. In third and final step of proposed method, a classifier fusion method used to fuse the classification results on hypersepctral and LIDAR data. For comparative purposes, results of classifier fusion compared to the results of single SVM classifiers on Hyperspectral and LIDAR data. Finally, the results obtained by the proposed classifier fusion system approach leads to higher classification accuracies compared to the single classifiers on hyperspectral and LIDAR data.
A comparison of the measured North Sea Andrea rogue wave with numerical simulations
Authors: Bitner-Gregersen E. M. , Fernandez L. , Lefèvre J. M. , Monbaliu J. , Toffoli A.
Published: September 2013

Abstract. A coupling of a spectral wave model with a nonlinear phase resolving model is used to reconstruct the evolution of wave statistics during a storm crossing the North Sea on 8–9 November 2007. During this storm a rogue wave (named the Andrea wave) was recorded at the Ekofisk field. The wave has characteristics comparable to the well-known New Year wave measured by Statoil at the Draupner platform the 1 January 1995. Hindcast data of the storm are here applied as input to calculate random realizations of sea surface and evolution of its statistical properties associated with this specific wave event by solving the Euler equations with a Higher Order Spectral Method (HOSM). The numerical results are compared with the Andrea wave profile as well as characteristics of the Andrea wave record measured by the down-looking lasers at the Ekofisk field.
Human Rights and Environmental Wrongs: Achieving Environmental Justice through Human Rights Law
Authors: Lewis Bridget
Published: September 2013

The numerous interconnections between the environment and human rights are well established internationally. It is understood that environmental issues such as pollution, deforestation or the misuse of resources can impact on individuals’ and communities’ enjoyment of fundamental rights, including the right to health, the right to an adequate standard of living, the right to self-determination and the right to life itself. These are rights which are guaranteed under international human rights law and in relation to which governments bear certain responsibilities. Further, environmental issues can also impact on governments’ capacity to protect and fulfil the rights of their citizens. In this way human rights and environmental protection can be constructed as being mutually supportive. In addition to these links between the environment and human rights, human rights principles arguably offer a framework for identifying and addressing environmental injustice. The justice implications of environmental problems are well documented and there are many examples where pollution, deforestation or other degradation disproportionately impact upon poorer neighbourhoods or areas populated by minority groups. On the international level, environmental injustice exists between developed and developing States, as well as between present and future generations who will inherit the environmental problems we are creating today. This paper investigates the role of human rights principles, laws and mechanisms in addressing these instances of environmental injustice and argues that the framework of human rights norms provides an approach to environmental governance which can help to minimise injustice and promote the interests of those groups which are most adversely affected. Further, it suggests that the human rights enforcement mechanisms which exist at international law could be utilised to lend weight to claims for more equitable environmental policies.
Invalidation: A Neglected Dimension of Gender-based Violence and Inequality
Authors: Salter Michael
Published: September 2013

This article proposes that invalidation is a pervasive manifestation of gender relations as expressed through strategies of minimisation, disbelief and denial. Invalidation is embedded within interpersonal and institutionalised arrangements and interactions. It is a constitute element of gender-based violence as well as a socio-political condition that enables gender-based violence. Invalidation serves to inscribe gender relations upon the bodies of women through the mental and physical health deficits of the gender-based violence that it enables and facilitates, as well as through the denial of testimonial legitimacy and the consequent withholding of resources, support and services.
Suspect Subjects: Affects of Bodily Regulation
Authors: Henne Kathryn , Troshynski Emily
Published: September 2013

There is a growing body of academic literature that scrutinises the effects of technologies deployed to surveil the physical bodies of citizens. This paper considers the role of affect; that is, the visceral and emotive forces underpinning conscious forms of knowing that can drive one’s thoughts, feelings and movements. Drawing from research on two distinctly different groups of surveilled subjects – paroled sex offenders and elite athletes – it examines the effects of biosurveillance in their lives and how their reflections reveal unique insight into how subjectivity, citizenship, harm and deviance become constructed in intimate and public ways vis-à-vis technologies of bodily regulation. Specifically, we argue, their narratives reveal cultural conditions of biosurveillance, particularly how risk becomes embodied and internalised in subjective ways.
Looking Behind the Increase in Custodial Remand Populations
Authors: Brown David
Published: September 2013

Numbers, rates and proportions of those remanded in custody have increased significantly in recent decades across a range of jurisdictions. In Australia they have doubled since the early 1980s, such that close to one in four prisoners is currently unconvicted. Taking NSW as a case study and drawing on the recent New South Wales Law Reform Commission Report on Bail (2012), this article will identify the key drivers of this increase in NSW, predominantly a form of legislative hyperactivity involving constant changes to the Bail Act 1978 (NSW), changes which remove or restrict the presumption in favour of bail for a wide range of offences. The article will then examine some of the conceptual, cultural and practice shifts underlying the increase. These include: a shift away from a conception of bail as a procedural issue predominantly concerned with securing the attendance of the accused at trial and the integrity of the trial, to the use of bail for crime prevention purposes; the diminishing force of the presumption of innocence; the framing of a false opposition between an individual interest in liberty and a public interest in safety; a shift from determination of the individual case by reference to its own particular circumstances to determination by its classification within pre-set legislative categories of offence types and previous convictions; a double jeopardy effect arising in relation to people with previous convictions for which they have already been punished; and an unacknowledged preventive detention effect arising from the increased emphasis on risk. Many of these conceptual shifts are apparent in the explosion in bail conditions and the KPI-driven policing of bail conditions and consequent rise in revocations, especially in relation to juveniles. The paper will conclude with a note on the NSW Government’s response to the NSW LRC Report in the form of a Bail Bill (2013) and brief speculation as to its likely effects.
Meeting the Fluoridation Reporting Challenge
Authors: Talend Don , Roueiheb Khaled
Published: September 2013

Experience has shown that the basic reasons for low or erratic fluoride levels are inconsistent feed systems and inadequate measurement methods. A California utility devised a way to maintain consistent fluoride levels and fulfill reporting requirements.
Understand Radio Frequency Propagation to Optimize Advanced Meter‐Reading Functionality
Authors: Dan Merritt
Published: September 2013

This is the second of a two‐part series about helping water utilities leverage meter data. The first article, Leveraging Data for Improved Utility Operations (www.awwa.org/fillinger13), which appeared in the September 2013 issue of Opflow, provided an overview of technologies and techniques for leveraging meter‐reading data. This article details how radio frequency propagation provides a strong foundation for automated reading systems.