High Resolution Satellite Imagery

The relationship between dams, engineers, heritage and archaeologists has often been contentious, if not openly hostile. Dams can inundate or destroy hundreds, if not thousands, of sites, many of which are not excavated or even recorded. Yet, as the global population rises, millions of people live without clean water or electricity, and searching for ways to feed them is an international priority. Climate change exacerbates the extreme weather conditions which lead to droughts and flooding. Dams can provide power and water for drinking and irrigation projects, and can regulate the water in areas that have too much, or provide for those with none at all. The How to Build a Dam and Save Cultural Heritage Project is run jointly between Durham and Edinburgh Universities, and is intended to provide an interdisciplinary platform for all groups involved in the issue to begin to seek a way forward. The inaugural event - a two day workshop held at Durham University on 6-7th July 2012 - was w...

Leaf area index (LAI) is one of the surface parameters that has importance in climate, weather, and ecological studies, and has been routinely estimated from remote sensing measurements. Canada-wide LAI maps are now being produced using cloud-free Advanced Very High-Resolution Radiometer (AVHRR) imagery every 10 days at 1-km resolution. The archive of these products began in 1993. LAI maps at the same resolution are also being produced with images from the SPOT VEGETATION sensor. To improve the LAI algorithms and validate these products, a group of Canadian scientists acquired LAI measurements during the summer of 1998 in deciduous, conifer, and mixed forests, and in cropland. Common measurement standards using the commercial Tracing Radiation and Architecture of Canopies (TRAC) and LAI-2000 instruments were followed. Eight Landsat Thematic Mapper (TM) scenes at 30-m resolution were used to locate ground sites and to facilitate spatial scaling to 1-km pixels. In this paper, examples of Canada-wide LAI maps are presented after an assessment of their accuracy using ground measurements and the eight Landsat scenes. Methodologies for scaling from high-to coarse-resolution images that consider surface heterogeneity in terms of mixed cover types are evaluated and discussed. Using Landsat LAI images as the standard, it is shown that the accuracy of LAI values of individual AVHRR and VEGETATION pixels was in the range of 50 -75%. Random and bias errors were both considerable. Bias was mostly caused by uncertainties in atmospheric correction of the Landsat images, but surface heterogeneity in terms of mixed cover types were also found to cause bias in AVHRR and SPOT VEGETATION LAI calculations. Random errors come from many sources, but pixels with mixed cover types are the main cause of random errors. As radiative signals from different vegetation types were quite different at the same LAI, accurate information about subpixel mixture of the various cover types is identified as the key to improving the accuracy of LAI estimates.

The Kunlun fault is one of the major strike-slip faults accommodating the eastward escape of the Tibetan plateau as a result of the India/Eurasia collision. During the last hundred years, several segments have ruptured through large earthquakes with magnitude from 6.1 to 7.5 ...

The aim of this work is to describe an experimentation on the possibility of extracting digital surface models (DSM) from stereoscopic images acquired from one of the less investigated satellite platforms: EROS-B. In the present paper the phases of extraction of a DSM from high resolution stereopairs using different methodologies are illustrated, and the results obtained are described and analyzed. Experimentation on using GCPs from GPS/GNSS survey and cartography were performed. The experimentation focused on two "pseudo" stereo pairs and one actual stereopair acquired by this satellite on areas morphologically different between them, one in the center of L'Aquila city and the other just some kilometer eastern (Paganica area), whose history was marked by some earthquakes because they are situated partially on an active seismic area and on an ancient lake-bed. The importance of this study is due in part to test the possibility of use of EROS-B imagery in an area recently marked by a strong earthquake, allowing so the extraction of digital models to compare the DSM before and after the earthquake. In this way we'll have the possibility to quantify the buildings volumetric changes to perform an initial assessment of damages.

The goal of this work was to evaluate the mean accuracy and its dependency on morphology and land cover types of the digital surface models (DSMs) extracted from IKONOS-II and EROS-A highresolution satellite in-track stereo imagery. DSMs were generated by the software PCI Geomatica OrthoEngine v. 9.0, which implements the well-known 3D rigorous (physical) model developed at the Canada Centre for Remote Sensing, Natural Resources Canada (CCRS). The paper illustrates the encountered problems and the achieved results during three experiments regarding two stereo IKONOS-II panchromatic images (with a small overlapping) of the Pozzuoli area (Naples, Southern Italy) and one stereo EROS-A image of the Tivoli area (Rome, Central Italy). Ground control points (GCPs) were collected by GPS: in the Pozzuoli area 29 GCPs were rapid-static surveyed with a mean 3D accuracy of 0.2-0.3 m; in the Tivoli area 23 GCPs with a mean 3D accuracy of 0.1 m were collected by RTK survey assisted by the GPS permanent network of the Lazio Region, managed by the Area di Geodesia e Geomatica-Università di Roma "La Sapienza". Three types of comparison were carried out when possible, in order to assess both mean accuracy and its dependency on morphology and land cover types: sample comparison, based on significant numbers of Independent Check Points (ICP) with a mean 3D accuracy of 0.3-0.5 m collected by kinematic GPS surveys; local and global comparisons with DEM generated from available maps, considering both contour lines and single points with photogrammetric derived heights; in this last respect, local comparisons were especially devoted to evaluate the accuracy dependency on morphology and land cover types (residential areas, dense forests, volcanic craters, bare soils, lakes, sea shoreline, Travertino quarries). A mean sample accuracy (RMS) of 1.9 and 6.0 m were achieved for IKONOS-II and EROS-A respectively. It has to be underlined that mean accuracy decreases remarkably in residential areas and forests, so that it is supposed that the intrinsic accuracy is better represented by the results obtained on bare soil and lakes, where RMS of 1.9 and 5.0 m were achieved for IKONOS-II and EROS-A respectively. The poorer results for EROS-A are probably mainly due to its asynchronous acquisition mode and to the extremely critical radiometric situation occurring on Travertino quarries, which appear almost uniformly white. Concerning the DEM/DSM classification criteria established by the Technical Steering Committee of the Italian State-Region Conference for GIS under the direction of O. Köebl, IKONOS-II derived DSMs have a quality at level 2-3, EROS-A at level 1-2.

The main goal of this paper is to find answer for two questions: why stereo orthoimage (orthophoto) was forgotten, and furthermore, what conditions have to be fulfilled for this particular technique to be reanimated? Stereo orthophoto concept was first introduced by Collins, during late seventies of last century (Colins, 1968). It has ignited huge interest, and many researchers were looking forward for its development , Kraus et al. 1976). However, after around twenty years, interest in stereo-orthophoto has shrunk, and during eighties of XX century it was almost extinct. Despite of fact that digital photogrammetry provides better conditions for it now than ever, it has never got chance for reactivation. There was but few papers about stereo orthoimage, and they are proposing continuous stereo ortho-mosaic generation while preserving its metric value . Reasons of downfall of this interest were examined, and it has been concluded that the main cause was usage of this technique in conjunction with analog photogrammetry. The radiometric value of orthophotomaps and stereo components developed on photosensitive paper were very low during that time. Equipment for observation and measurement were simply very big and therefore impractical. Authors have concluded, that nowadays sum of gains outweighs its flaws and it is reason enough to go back to it. But in a time of digital vector 3D models there is a need for proper strategy for popularization stereo orthophoto. Main point of this strategy would be encapsulating stereo orthoimage method into GIS tools, optimally open source. GIS have large numbers of consumers whom regard for orthophotomap (or orthoimage) is very high. If they were to be proposed with possibility of using stereo orthoimage inside a GIS tool, as a complementary to the orthophotomap, probably they would recon how much stereoscopy helps with interpretation of an image. Authors have planned to develop software for utilization of stereo orthoimage available from the Quantum GIS interface, and test version is to be based on anaglyph stereoscopy. Value of creating continuous stereo-mosaic composed from many 3D models was assessed. Consensus was, however, that this solution surprises us with frequent perspective changes which leads to discomfort. As an outcome it was decided to focus on single stereo orthoimage pairs. When area constrains are specified for single model, one can load them as requested by an user. In case of increased lateral and longitudinal coverage, which is more common in modern aerial photogrammetric flights, every localization will be accessible for visualization using several models, and there will be less concealed areas. Few algorithms for generation of parallax are tested. After completion of sets from a dozen or so example models of interesting areas are gathered, there will be release. Authors are confident that stereo orthoimage may prove more useful for GIS users than true orthophotomap.

Raw digital images can not be used as maps because they contain geometric distortions which stem from the image acquisition process. To supply the same geometric integrity as a map, original raw images must be geometrically corrected and the distortions, such as variations in altitude, and earth curvature, must be compensated for. There are two techniques that can be used to correct the various types of geometric distortions present in digital image data: one is orbital geometry modelling and the other one, rather used in many image processing, is the transformation based on ground control points. In the last few years there has been a significant resurgence of interest in using artificial neural network algorithms for different image processing procedures. In this study besides the conventional image processing procedures, an artificial neural network algorithm for the rectification of the SPOT-P image of the study area in #stanbul was developed and applied for generating both new grids and corresponding brightness values. The rectification results were compared with those from the polynomials, and their merits and weakness were addressed.

Recent research conducted at the University of Melbourne has shown that commercial high resolution satellite imagery can be accurately rectified using the combination of bias -corrected rational polynomial coefficients (RPCs) and ground control points (GCPs). Research carried out to date has used GCPs measured using differential GPS, a relatively expensive and time-consuming process. This paper presents the initial results of an investigation into the possibilities of using GCPs automatically extracted from digital orthomosaics created from aerial photography. As long as common points can be located in corresponding pairs of orthomosaics and satellite images, the need for ground surveyed GCPs is eliminated. Experiments using various combinations of matched points extracted from aerial photography and high resolution Ikonos satellite images were used to remove positioning biases in RPCs and hence improve the geometric precision of the satellite images. The results showed that, in mos...

Launched in 2014, the European Space Agency (ESA) Sentinel-1 satellite carrying a medium resolution (20 m) C-Band Synthetic Aperture Radar (SAR) sensor holds much promise for new applications of multi-temporal interferometry (MTI) in landslide assessment. Specifically, the regularity of acquisitions, timeliness of data delivery, shorter repeat cycle (currently 12 days with Sentinel-1A sensor), and flexible incidence angle geometry, all imply better practical utility of MTI relying on Sentinel-1 with respect to MTI based on data from earlier ESA’s satellite radar C-band sensors (ERS1/2, ENVISAT). Furthermore, the upcoming launch of Sentinel-1B will cut down the repeat cycle to 6 days, thereby further improving temporal coherence and quality and coverage of MTI products. Taking advantage of the Interferometric Wide (IW) Swath acquisition mode of Sentinel-1 (images covering a 250 km swath on the ground), in this work we test the potential of such data for regional scale slope instabili...

Curriculum development is the key to the future. It is an ongoing process and it is crucial to both the educational institutions and the society they serve. This relates especially to educational programs designed to professionals such as the surveyors. There is no doubt that the main challenge of the future will be that the only constant is change. To deal with this constant change the educational base must be flexible. The graduates must be adaptable to a rapidly changing labour market. The point is that professional and technical skills can be acquired and updated at a later stage in ones career while skills for theoretical problem-solving and skills for learning to learn can only be achieved through the process of academic training at the universities. The focus should be on educating for life -not for short term skills. The paper touches on a range of issues and lessons learnt with a special emphasis on ways and means of building professional competence through curriculum development. The basic argument is that development, maintenance and enhancement of professional competence should be seen as a process facilitated through an efficient interaction between education, research and professional practice.

This paper addresses the epipolar geometry of linear pushbroom imagery. Two images of a single scene are related by epipolar geometry which contain all geometric information and is essential for the three dimensional reconstruction of the scene in computer vision and remote sensing. It is told that the epipolar geometry of the linear pushbroom sensor is different from that of the perspective one. In this paper, we propose an epipolarity model which does not require the ephemeris data but shows high performance (in accuracy, processing time, etc.). We also quantitatively analyse various epipolarity models such as the epipolar geometry of perspective and aerial imagery, the one by Gupta and Hartly and the one based on the Orun and Natarajan sensor model. To analyze the accuracy of the proposed epipolarity model and others, we quantitatively measure the distance between the truth point and epipolar lines on two types of linear pushbroom images; SPOT and KOMPSAT. The results show that the epipolarity model based on the Orun and Natarajan sensor model is more accurate than that of perspective sensor and by Gupta and Hartly because the ephemeris data of the satellite image is applied. The proposed epipolarity model shows a high accuracy similar to that of the Orun and Natarajan sensor model without the ephemeris data. Our epipolarity model will be very useful when the ephemeris data are not available such as IKONOS images or are not accurate.

Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is desirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found. In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classification has been tested and compared with two existing classification algorithms. The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with the following result (correctly classified pixels)

Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is desirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found. In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classification has been tested and compared with two existing classification algorithms. The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with the following result (correctly classified pixels)

The western coast of Sumatra Island is highly susceptible to earthquakes, which have the potential to trigger tsunami hazards. Padang, the largest city along this coast, is particularly vulnerable to these seismic events. Therefore, it is crucial to implement tsunami mitigation measures, specifically coastal ecology-based strategies. This research aimed to compare the extent of tsunami runoff in Padang city using two different models. The first model simulated tsunami runoff based on the existing land cover conditions, while the second model optimized land cover conditions in line with coastal ecological suitability. The simulation results indicated that the model based on the current land cover conditions, predicted a tsunami inundation area spanning 3,231 hectares. However, by optimizing land cover conditions based on coastal ecology, the inundation area was reduced to 2,839 hectares. This shows the adoption of the coastal ecology-based modeling approach led to a reduction of 391 hectares in a tsunami inundation area.

The launch of extremely high-resolution sensor satellites has paved the way for many researchers to explore the potential gain in producing Digital Elevation Model (DEM) from stereo imagery. This paper deals with the issue of extracting DEM automatically from IKONOS stereopair of imagery using modified the Rational Function Model (RFM). Since high-resolution satellite imagery companies do not provide precise sensor information and orbit parameters for various reasons. Thus, the use of RFM as a generic sensor model has become an alternative to accurate sensor models. This model uses the Rational Polynomial Coefficients (RPCs) provided with the images describing the relationship between ground space and image space. However, the RPCs supplied by the vendors may not always represent well the true imaging process and this affects the accuracy of DEM. Therefore, RPCs modification is a better choice for obtaining DEM with reasonable accuracy. The study was conducted on a stereo pair of IKONOS imagery over an area in the North of Khartoum (Sudan), covering about 30 sq-km. A well-distributed set of 12 ground points was selected over stereo images and then surveyed using Differential Global Positioning System (DGPS) static technique, these points are divided into control and checkpoints to assess the accuracy. DEM generation automatically depends on a series of processes within the Imagine Photogrammetry software package that were used in this research with the modified RFM. The results of the experiment showed that the accuracy of extracting DEM by modifying RFM has a very good consistency and within a 2 m-level using a few Ground Control Points (GCPs). Finally, the results of this paper are mainly motivating for professionals from different disciplines who need to use a DEM for planning and transportation issues as well as using highresolution stereo images to replace the traditional aerial photography in generating DEM, which limits the cost and time-consuming.

With the development of video--protection, the number of cameras deployed is increasing rapidly. To effectively exploit these videos, it is essential to develop tools that automate the monitoring at least part of their analysis. One of the difficulties and poorly resolved problems in this area is the tracking of people in a large space (metro, shopping center, airport, etc ...) covered by a network of non--overlapping cameras. Point detection can be done on the region of interest obtained by the standard approaches of pixel--wise background subtraction and motion detection. But we also propose an implementation of this phase using only interest points, to develop a complete processing chain adapted to future smart cameras that would calculate interest points in real--time on integrated hardware and provide them as complementary or alternative output. In our approach, re--identification is done by collecting a set of interest points during a time window, then looking for each of their corresponding most similar amongst all descriptors previously stored in a KD--tree. This allows a very fast search even among a large number of points corresponding to many people followed previously in other cameras. We conduct quantitative evaluations of our technique on public databases such as CAVIAR and ETHZ, and a new set of videos containing 40 people, that we recorded in our laboratory, which we propose as a benchmark for the community. The performance of re--identification of our initial algorithm is at least comparable to the state of the art, with approximately 80% of correct identification at first--rank on our 40--persons database. We also present comparisons with other commonly used descriptors (color histogram, HOG, SIFT), which have a lower performance. Finally, we propose and test possible improvements, particularly for the automatic selection of moments or interest points, to obtain a set of points for each individual which are the most varying and more discriminating to those of other people. This probabilistic variant of our method, which weights keypoints according to their relative frequencies within models and globally, brings tremendous improvement to performance, which rise at 95% correct identification among 40 persons, which is above state--of--the--art.

In relation to surveying education there is one big question to be asked: Is the role of the surveyors changing? In a global perspective the answer will be "Yes". There is a big swing that could be entitled "From Measurement to Management". This does not imply that measurement is no longer a relevant discipline to surveying. But it does imply that the focus of the surveying profession is changing from being very much related to doing measurements to now being increasingly related to management of the measurement processes, the geospatial data, and the property and land-use regimes.

The geometric resolution of the images coming from the new generation satellites is almost competitive with that found in the trational aerial photograms. The aim of this work is to define the role of satellite ephemerides and to optimise the number and distribution of Ground Control Points (GCPs) for the image registration. A zone of the Campania region in Italy has been used as a test area: it is characterized by a mountainous area without constructions and by flat land areas densely inhabited. The images that have been used relate to different epochs and different satellites such as Spot5, Ikonos2 and QuickBird. Spot5 images have also been used to generate automatic Digital Elevation Models (DEMs). The assessment of DEM precision has been carried out by comparison with raster DEMs from cartography. The GCPs coordinates have been obtained from a GPS network made up of almost hundred and some of them are used as Check Points (CPs). Different tests have been performed, either varying the number of GCPs or hypothesizing the presence or absence of satellite ephemeris. Some numerical evaluations confirm that the use of the satellite ephemeris greatly reduces the amount of residuals on the CPs; in the case of Spot5 images this improvement becomes even more evident.

In this work some results of an experiment of processing a panchromatic SPOT stereo-pair by using the OrthoEngine Satellite Edition software by PCI are presented. The goal is to verify the metric accuracy of the cartographic products which may be obtained. The Test area is located in some districts of Campania (Italy), which were affected by a dramatic landslide event on May 1998. Several tests have been performed by using the two mathematical models provided by the software in order to compute a warping transformation, which are polynomial transformations and thin plate splines. The automatic DEM extraction has been carried out by applying the method of the epipolar images, which provides a level of accuracy similar to that one achievable by using the same images not rectified, because the two procedures require the same kind of parameters (i.e. internal and external orientation parameters of the images, resampling alghoritms).

Water resources play an important role in environmental, transportation and region planning, natural disaster, industrial and agricultural production and so on. Surveying of water-bodies and delineate its features properly is very first step for any planning, especially for places like India, where the land-cover is dominated by water-bodies. Recording images, such as from satellite, sometimes does not reflect the distinguished characteristics of water with non-water features, e.g. shadows of super structures. Image of water body is confused easily with the shadow of skyscraper, since calm water surface induces mirror reflection when it gives birth to echo wave. Water transport is cheapest. Developing/poor countries like India will be benifitted if water transport is encouraged. In water transport, the link should be made between various land masses, including building blocks, through proper navigational system. Hence there should be clear distinction between calm water and the shadows of buildings. Over the past decade, a significant amount of research been conducted to extract the water body information from various multi-resolution satellite images. The objective of this paper is to review methodologies applied for water body extraction using satellite remote sensing. The Geographic Information System (GIS) and the Global Positioning System (GPS) have also been discussed as they are closely linked with Remote Sensing. Initially, studies on water body detection are treated. Methodological issues related to the use of these methods were analysed followed by summaries. Results from empirical studies, applying water-body extraction techniques are collected and discussed. Important issues for future research are also identified and discussed.

This 3D modeling experience lies in the more general framework of large scale cartography aimed at conservation of an historical city center. The study has been applied to the ancient nucleus of "Certaldo Alto", a medieval village in Tuscany famous as Boccaccio's birthplace. The data acquisition project exploited the synergy of topography, photogrammetry and 3D scanning for generating a cartography at 1:500 scale. The model was built starting from a common aerophotogrammetric survey, suitable for generating a traditional cartographic representation. Instead of dropping the height information, it was employed for building a texturized 3D model, suitable for visualization and virtual visit of the site. Preliminarily to the 3D model creation a critical analysis of the data obtained by photogrammetry has been carried out and different objects have been assigned to different layers. 3D polylines have been then extruded from the vertexes of each building for generating the external walls. Similarly roofs surfaces have been identifi ed. All the elements not deductible by photogrammetry, as stairs, porches and overhangs, have been modeled through the integration of a topographic survey. The altimetry of the area has been obtained from an aerophotogrammety generated DTM. The model texturization with digital photographs allowed to add visual reality to the model. The fi nal passage to formats for animation (.avi) or interactive exploration (.wrl), allowed fi nally to dynamically present the town survey.

This 3D modeling experience lies in the more general framework of large scale cartography aimed at conservation of an historical city center. The study has been applied to the ancient nucleus of “Certaldo Alto”, a medieval village in Tuscany famous as Boccaccio’s birthplace. The data acquisition project exploited the synergy of topography, photogrammetry and 3D scanning for generating a cartography at 1:500 scale. The model was built starting from a common aerophotogrammetric survey, suitable for generating a traditional cartographic representation. Instead of dropping the height information, it was employed for building a texturized 3D model, suitable for visualization and virtual visit of the site. Preliminarily to the 3D model creation a critical analysis of the data obtained by photogrammetry has been carried out and different objects have been assigned to different layers. 3D polylines have been then extruded from the vertexes of each building for generating the external walls....

Uncontrolled sprawl occurring in large cities of developing countries requires intensive mapping efforts to update geodatabases. The intense urbanization process experienced since the 70's in Sao Paulo city illustrates this scenario. Despite aerial data and the more recent high resolution satellite imagery data which have been employed as the base for mapping, the need for precise, faster and cheaper mapping processes is real. Automated classification has demonstrated unsatisfactory results when traditional per-pixel classifiers are used. The increasing success of object-based classification has stimulated researches on creating new methodologies to provide geoinformation. The idea is extract object-primitives from images and use their information to compose strategies to improve the classification process. This paper reports this technology applied on road detection and classification in informal settlements areas. An 11 bit Ikonos multi-spectral image was used. Principal components were pre-computed and used on features customization. Auxiliary data were calculated from spectral information and combined with geometric information of the segments. Classification rules were created from objects information, by using combination between original multispectral bands, principal components as well as using combinations of geometric characteristics like width, length, neighbor and asymmetry and contextual ones. Considering the Ikonos second principal component as a good indicator of impervious areas, and considering the detection of bare soil areas, paved and unpaved roads were discriminated. Preliminary results have indicated that this classification method produces accurate results. Procedures and rules of the present methodology are presented here. Comparisons between automatic approaches and manual ones will attest the efficiency of the methodology.

In recent years the research activity in image registration has grown at the same pace as the high resolution satellite images have found their way to end users. Much of this research activity has concentrated on methods improving the accuracy of georeferencing provided as RPC values. In this study the image registration via projective transformation based on straight line segments is investigated. The transformation parameters are solved based on real data extracted from topographic database and measurements done on QuickBird image. Same data is processed also with point wise method and accuracy numbers in selected check points are calculated. The RMS values computed in same check points prove that with the line based method the equivalent accuracy can be achieved as with the point wise method computed with minimum number of observations. In a smaller sub image the accuracy of transformation with line segments could be verified to be in size of a pixel.

Ground subsidence triggered by salt mining from deposits located beneath the city of Tuzla (Bosnia and Herzegovina) is one of the major dangers acting on a very densely urbanized area since 1950, when the salt deposit exploitation by means of boreholes began. As demonstrated in this paper, subsidence induced several hazard factors such as severe ground deformations, the arising of deep and superficial fractures and a very fast water table rise, connected with the brine extraction, now affecting several districts. The above mentioned factors have been quantified by the use of geomatic methodologies, including field surveys and analysis of geographical data. In order to estimate the historical sinking rates, authors processed the large (and never before processed) amount of topographical data collected during two periods; from 1956 to 1991, and from 1992 to 2003, with only poor data collected. Afterward, traditional surveys were completely and definitively stopped. The analysis reveals a cumulative subsidence as high as 12 m during the whole period, causing damage to buildings and infrastructures within an area that includes a large portion of the historical town, at present almost entirely destroyed. Modern sinking rates have been monitored with static GPS whereas the presence of superficial fractures monitored with kinematic GPS. Factors related to the presence of deep fractures and water table rise have been evaluated by curvature analysis techniques and piezometric data respectively. Finally, hazard factors have been combined in a risk map using the GIS (Geographical Information System) map algebra capabilities and a simple multicriteria decision analysis (MDA). In order to do that, a vulnerability map has been derived on the basis of information reported on a couple of recently sensed high resolution satellite imageries. The final risk, arisen from the combination of single hazard factors and vulnerability map, highlights critical scenarios and unsuspected threatening that are under consideration by the local decision makers and urban planners. In particular, as highlighted in the final risk map, the present-day water table rise, triggered by the decrease in brine pumping, is seriously posing a threat to a portion of the city which is not the most involved in ground deformations.

The electroperforation distribution in thin porous materials is investigated using the quadrat counts method (QCM), a classical statistical technique aimed to evaluate the deviation from complete spatial randomness (CSR). Perforations are created by means of electrical discharges generated by needle-like tungsten electrodes. The objective of perforating a thin porous material is to enhance its air permeability, a critical issue in many industrial applications involving paper, plastics, textiles, etc. Using image analysis techniques and specialized statistical software it is shown that the perforation locations follow, beyond a certain length scale, a homogeneous 2D Poisson distribution.

The objectives of this research are to characterize urban building damage, using a comparative analysis of remote sensing imagery acquired before and after an earthquake event, and to develop preliminary damage detection algorithms for locating collapsed urban structures.

ABSTRACT: The physical and generalized sensor models are two widely used imaging geometry models in the photogrammetry and remote sensing. Utilizing the rational function model (RFM) to replace physical sensor models in photogrammetric mapping is becoming a standard way for economical and fast mapping from high-resolution images. The RFM is accepted for imagery exploitation since high accuracies have been achieved in all stages of the photogrammetric process just as performed by rigorous sensor models. Thus it is likely ...

A t wo-stage approach is discussed for reconstructing a dense digital elevation model DEM of the terrain from multiple pre-calibrated images taken by distinct cameras at di erent time under various illumination. First, the terrain DEM and orthoimage are obtained by independent voxel-based reconstruction of the terrain points using simple relations between the corresponding image gray v alues. As distinct from other approaches, possible occlusions and changing shadow l a youts are taken into account implicitly by evaluating a con dence of every reconstructed terrain point. Then, the reconstructed DEM is re ned by excluding occlusions of more con dent points by less con dent ones and smoothed with due account of the con dence values. Experiments with RADIUS model-board images show that the nal re ned and smoothed DEM gives a feasible approximation to the desired terrain.

This article summarizes briefly the results obtained within the symmetrized approach to intensity‐based computer binocular stereo vision, considering it as a problem of optimal statistical estimation of digital terrain model (DTM) from a given stereo pair of images. This approach was proposed by the author in 1972–1979 and then extended to take into account main geometric and photometric characteristics of the binocular stereo vision: symmetry of both channels, nonuniform intensity distortions over the images, limited possibilities for binocular perception of the terrain, and inherent ambiguity of the DTM estimation from the stereo pair.

High-resolution satellite images, including KOMPSAT, WorldView-3, and Pléiades, are widely used for mapping and environmental monitoring. In particular, satellite images with high spatial resolution have accurate location information and provide essential spatial information. Most high-resolution satellite image files are provided with rational polynomial coefficients (RPCs) that can be used for sensor modeling. However, the RPCs have an initial bias. Therefore, most satellite image platforms and researchers match satellite images to ground control point (GCP) information and perform RPCs bias compensation of images using the matching information. In Korea, an image-based GCP chip database built using orthographic images has been provided for the georegistration of various satellite images. In this manuscript, RPCs bias compensation of KOMPSAT-3A satellite images was performed using the GCP chips, and then, the possibility of automation of RPCs bias compensation through GCP chips was analyzed. Image matching, such as area-based and edge-based techniques, was used, and the results of RPCs bias compensation using the GCP chips were analyzed through experiments for various regions. The automated compensation in both area-based or edge-based matching performed well, achieving accuracy within 1.5 pixels for test areas with various topographic features. However, the forest area posed a challenge, requiring new GCP chips with rich feature information. In addition, edge-based matching showed potentials to overcome large seasonal differences, including snow cover.

KOMPSAT-3A (KOrea MultiPurpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

A large amount high-resolution satellite imagery (HRSI) has been available in the commercial market because of its value in creating accurate base maps for various applications. As massive amounts of HRSI are acquired globally by satellites with short revisit times, automated but accurate georegistration is still required despite advances in precise orbit tracking and estimation. Motivated by the attractive properties of airborne lidar data, such as their high resolution and accuracy, this study proposes a new automated method for refining the HRSI with rational polynomial coefficients (RPCs) using airborne lidar information. By projecting the lidar intensity return into the HRSI space, the image matching complexity is reduced to a simple, 2D case. The true challenge is in overcoming the difference between the HRSI and the lidar intensity return to allow for reliable matching. To this end, this paper proposes a new method based on simple relative edge cross correlation (RECC) with a screening method to prevent false matching. To make the approach more robust, data snooping was added for a final detection of outliers. Experiments were performed using three Kompsat-2 images and the potential of the approach was confirmed, showing sub-pixel accuracy. 1. Feature identification from the target and reference. 2. Feature matching with outlier removal. 3. Establishment of the sensor model parameters. 4. Image resampling, if needed.

Conventional manual georegistration has been labor-intensive and time-consuming to process globally acquired high-resolution satellite imagery (HRSI) including the Korea MultiPurpose Satellite-2 (KOMPSAT-2). While an image-to-image matching-based method can provide an automated procedure, geometric and pixel value differences such as the apparent leaning of the terrain limits an accurate georegistration. This study utilizes the projection of orthoimages into the HRSI space using external elevation data to reduce the geometric difference, and an edge matching is applied to overcome the pixel value differences. Either rigorous or replacement sensor modeling is then carried out for georegistration with robust outlier removal. An experiment for a KOMPSAT-2 strip using Digital Orthophoto Quadrangles and the Shuttle Radar Topography Mission improved the horizontal positional accuracy from 70 to only a few meters for the test data set.

High-resolution earth-observing satellites acquire substantial amount of geospatial images. In addition to high image quality, high-resolution satellite images (HRSI) provide unprecedented direct georegistration accuracy, which have been enabled by accurate orbit determination technology. Direct georegistration is carried out by relating the determined position and attitude of camera to the ground target, i.e., projecting an image point to the earth ellipsoid using the collinearity equation. However, the apparent position of ground target is displaced due to the atmosphere and satellite velocity causing significant georegistration bias. In other words, optic ray from the earth surface to satellite cameras at 400~900km altitude refracts due to the thick atmosphere which is called atmospheric refraction. Velocity aberration is caused by high traveling speed of earth-observing satellites, approximately 7.7 km/s, relative to the earth surface. These effects should be compensated for accurate direct georegistration of HRSI. Therefore, this study presents the equation and the compensation procedure of atmospheric refraction and velocity aberration. Then, the effects are simulated at different image acquisition geometry to present how much bias is introduced. Finally, these effects are evaluated for Quickbird and WorldView-1 based on the physical sensor model.

Epipolar line determination and image resampling are important steps for stereo image processing. Unlike frame cameras that have well-known epipolar geometry, the pushbroom camera does not produce straight epipolar lines and the epipolar pair does not exist for the entire scene. These properties make it difficult to establish epipolar geometry of the pushbroom camera for epipolar image resampling. Therefore, some researchers have adopted approximate models to avoid these problems. In this study, a new method for the conjugate epipolar curve pair determination and epipolar resampling of spaceborne pushbroom images based on RPC is proposed. The proposed method assumes that the conjugate epipolar curve pairs exist approximately for the local scene area and the global epipolar pairs can also exist if the local pairs are sequentially linked. Then, epipolar image resampling is established by reassigning the generated conjugate epipolar curve pair points to satisfy the epipolar resampling image condition. Ikonos stereo images are tested for the evaluation, and the proposed method showed a maximum y-parallax of 1.25 pixels for manually measured tie points, while the resampling method by the parallel projection model showed a maximum of 4.59 pixels.

The learners' needs are an important factor in designing syllabus and materials design, this research deals with the syllabus and material design based on the professional's needs. It is expected that the syllabus and materials designes are communicatively applicable to the professional academy. Descriptive method is applied in this research. The sample of this research is 30 students of ATII Immanuel Academy Medan. They were selected by random sampling to get the data, the questioners were administered to students. the questioners consisted of 54 items and the semi structured interview consisted of 5 questions, the finding indicated that learners' needs were focused on reading and speaking skills. With reference appropriately and proportionally derived for students of the Professional Academy. Further on the basis of the syllabus, materials are designed in which the skills of using language become a priority. The results of this research will be disseminated using the website

Remote sensing is a powerful and well-known tool in the collection, analysis, and modeling of environmental data, however, not much attention has been given to the use of thermal infrared (TIR) remote sensing. Land surface temperature (LST) is a key parameter for many environmental studies such as global environmental change, climate models, and human-environment interactions. In this study, a software tool which retrieves LST from Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) imagery has been developed in Visual Basic .NET. The tool consists of five main modules: 1-Converting DN to Radiances, 2-Calculating surface reflectances, 3-Calculating NDVI, 4-Calculating emissivity and 5-Calculating surface temperature. In this tool, Jimenez Munoz and Sobrino's Single Channel (SC JM&S) Algorithm for ASTER was employed. With this tool, user can be able to calculate LST using (1) atmospheric parameters such as atmospheric transmissivity, upwelling and downwelling atmospheric radiances, (2) atmospheric water-vapor content. Hopefully, this program will be a useful tool for scientists/persons who are interested in studying thermal environments.

Cevresel verinin toplanmasi, analizi ve modellemesinde uzaktan algilama cok onemli ve iyi bilinen bir arac olmasina ragmen, termal kizilotesi (TIR) uzaktan algilamasina gereken onem verilmemistir. Kuresel cevre degisimi, iklim modelleri ve insan-cevre etkilesimleri gibi bircok cevresel calismalar icin yer yuzey sicakligi (LST) onemli bir parametredir. Bu calismada, Visual Basic NET programlama dili kullanilarak ASTER uydu goruntusunden yer yuzey sicakligini hesaplayan bir yazilim araci gelistirilmistir. Bu arac bes modulden olusmaktadir: 1- Dijital Sayilari (DN) Radyansa donusturme, 2- Yuzey yansima degerinin hesaplanmasi, 3- NDVI’in hesaplanmasi, 4- Yayinirligin hesaplanmasi ve 5- Sicakligin hesaplanmasi. Bu yazilim aracinda Jimenez Munoz ve Sobrino’nun ASTER uydu goruntusunden yer yuzey sicakliginin hesaplanmasi icin gelistirdigi Tek Kanal (Single Channel) Algoritmasi kullanilmistir. Bu programin termal cevre uzerine calisan bilim insanlari veya konuyla ilgilenen kisiler icin fayd...

Remote sensing is a powerful and well-known tool in the collection, analysis, and modeling of environmental data, however, not much attention has been given to the use of thermal infrared (TIR) remote sensing. Land surface temperature (LST) is a key parameter for many environmental studies such as global environmental change, climate models, and human-environment interactions. In this study, a software tool which retrieves LST from Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) imagery has been developed in Visual Basic .NET. The tool consists of five main modules: 1-Converting DN to Radiances, 2-Calculating surface reflectances, 3-Calculating NDVI, 4-Calculating emissivity and 5-Calculating surface temperature. In this tool, Jimenez Munoz and Sobrino's Single Channel (SC JM&S) Algorithm for ASTER was employed. With this tool, user can be able to calculate LST using (1) atmospheric parameters such as atmospheric transmissivity, upwelling and downwelling atmospheric radiances, (2) atmospheric water-vapor content. Hopefully, this program will be a useful tool for scientists/persons who are interested in studying thermal environments.

Unreliability involved in the extraction of shaded vegetation-covered surfaces (VS) is a common problem in urban vegetation mapping. Serving as a solution to it, a novel method named Nonlinear Fitting-based Seeded Region Growing (NFSRG) is explored. With NFSRG, a series of classified results are organized by a seeded-region-growing process. In order to adapt to the variable separability between VS and background, the growing is limited in several weighted buffers defined by some nonlinear fitting relationships. When searching new VS members (member means both pixel and patch) within such a buffer, a gradually reduced weight makes the buffer width continually narrowed as the separability worsens. To avoid unexpected entrances of water and smooth shaded background members, a during-growing constraint, named expansion rate, is proposed. Accuracy assessments reveal that more than 96% of VS members can be accurately extracted by the proposed method.

In 2008 and with the cooperation of the U.S. Department of Defence, it was launched a new commercial very high resolution (VHR) satellite named GeoEye-1 (GeoEye, Inc.) which, nowadays, is the commercial satellite with the best geometric resolution, so much in panchromatic (0.41m) as in multispectral (1.65m). More recently, on January 4, 2010, DigitalGlobe have begun to commercialize imagery of the last of the VHR satellites launched: WorldView-2. Its most relevant technical innovation includes the radiometric accuracy improvement, since the number of bands that compose its multispectral image has increased to 8, instead of the 4 classic bands (R, G, B, NIR) of the previous VHR satellites. These new VHR satellites offer important improvements closely related to spatial and spectral resolution. Therefore, an improvement is awaited in: (i) the geometric accuracies obtained in orthoimages and digital elevation models (DEMs) generated from scenes of GeoEye-1 and WorldView-2, as well as, (ii) an increase in the accuracy of the objects classification (urbanizations, buildings, highways, impervious zones, crops). These possible improvements will have to be contrasted with real tests carried out in field conditions, studying the ideal performance procedures in the seeking of accurate geo-referenced information. In this work the geometric accuracy of a single panchromatic image of GeoEye-1 with an off-nadir angle higher than 20 degrees was researched. Rational Polynomial Coefficients refined by a zero order polynomial adjustment (RPC0) was the sensor model that generated the best results. Using a DEM with a vertical accuracy of about 1.34 m, accurate orthoimages (planimetric root mean square error of 0.87 m) can be obtained from GeoEye-1 imagery.

In this paper we present an application of aerial remote sensing to the analysis of spatial information in a mountainous area of central Italy by applying texture measures and landscape indices. Land cover data acquired in different time periods are used to calculate measures of landscape pattern and structure at pixel level (tone and texture variables) and patch-level (landscape indices). Images of the patches from the 1950s, 1980s and 1990s have been derived from the tone-texture classification of scanned black-and-white photographs. Multitemporal analysis of landscape indices has been performed to detect changes of landscape elements and related effects on vegetation dynamics due to the reduction of human impact.

In this paper we present an application of aerial remote sensing to the analysis of spatial information in a mountainous area of central Italy by applying texture measures and landscape indices. Land cover data acquired in different time periods are used to calculate measures of landscape pattern and structure at pixel level (tone and texture variables) and patch-level (landscape indices). Images of the patches from the 1950s, 1980s and 1990s have been derived from the tone-texture classification of scanned black-and-white photographs. Multitemporal analysis of landscape indices has been performed to detect changes of landscape elements and related effects on vegetation dynamics due to the reduction of human impact.

BACKGROUND: Household-level geographic information systems (GIS) database are usually constructed using the geographic positioning system (GPS). In some research settings, GPS receivers may fail to capture accurate readings due to structural barriers such as tall buildings. We faced this problem when constructing a household GIS database for research sites in Karachi, Pakistan because the sites are comprised of congested groups of multi-storied building and narrow lanes. In order to overcome this problem, we used high resolution satellite imagery (IKONOS) to extract relevant geographic information. RESULTS: The use of IKONOS satellite imagery allowed us to construct an accurate household GIS database, which included the size and orientation of the houses. The GIS database was then merged with health data, and spatial analysis of health was possible. CONCLUSIONS: The methodological issues introduced in this paper provide solutions to the technical barriers in constructing household G...