MAMUD : contribution of HR satellite imagery to a better monitoring, modeling and understanding of urban dynamics

In this treatise the discussion of a methodology and results of semi-automatic city DSM extrac-tion from an Ikonos triplet, is introduced. Built-up areas are known as being complex for photogrammetric purposes, partly because of the steep changes in elevation caused by buildings and urban features. To make DSM extraction more robust and to cope with the specific problems of height displacement, concealed areas and shadow, a multi-image based approach is followed. For the VHR tri-stereoscopic study an area extending from the centre of Istanbul to the urban fringe is chosen. Research will concentrate, in first phase on the development of methods to optimize the extraction of photogrammetric products from the bundled Ikonos triplet. Optimal methods need to be found to improve the radiometry and geometry of the imagery, to improve the semi-automatically derivation of DSM’s and to improve the postprocessing of the products. Secondly we will also investigate the possibilities of creating stereo models out of images from the same sensor taken on a different date, e.g. one image of the stereo pair combined with the third image. Finally the photogrammetric products derived from the Ikonos stereo pair as well as the products created out of the triplet and the constructed stereo models will be investigated by comparison with a 3D reference. This evaluation should show the increase of accuracy when multi-imagery is used instead of stereo pairs

Assessment of a photogrammetric approach for urban DSM extraction from tri-stereoscopic satellite imagery

Built-up environments are extremely complex for 3D surface modelling purposes. The main distortions that hamper 3D reconstruction from 2D imagery are image dissimilarities, concealed areas, shadows, height discontinuities and discrepancies between smooth terrain and man-made features. A methodology is proposed to improve automatic photogrammetric extraction of an urban surface model from high resolution satellite imagery with the emphasis on strategies to reduce the effects of the cited distortions and to make image matching more robust. Instead of a standard stereoscopic approach, a digital surface model is derived from tri-stereoscopic satellite imagery. This is based on an extensive multi-image matching strategy that fully benefits from the geometric and radiometric information contained in the three images. The bundled triplet consists of an IKONOS along-track pair and an additional near-nadir IKONOS image. For the tri-stereoscopic study a densely built-up area, extending from the centre of Istanbul to the urban fringe, is selected. The accuracy of the model extracted from the IKONOS triplet, as well as the model extracted from only the along-track stereopair, are assessed by comparison with 3D check points and 3D building vector data

Geometric and Radiometric Calibration of Video Infrared Imagers for Photogrammetric Applications

This thesis is concerned with the geometric and radiometric calibration of infrared imagers with a view to their use in close-range and airborne photogrammetric applications. From the geometric point of view, three quite different types of infrared imager can be distinguished - these comprise (i) the pyroelectric vidicon camera; (ii) the CCD camera based on the use of an areal array of solid-state detectors; and (iii) the thermal video frame scanner (TVFS). The special optics and the detector technologies that are used in these imagers to generate images in the middle and thermal bands of the infrared spectrum, together with the underlying video technology, are first reviewed and discussed in some detail with an emphasis on their fundamental geometric and radiometric characteristics and properties. On this basis, the design and construction of a special target plate has been undertaken that allows all these different types of imager to be calibrated both geometrically and radiometrically. After describing this target plate, the actual experiment set-up and procedures and the subsequent data processing and analysis are outlined, including the method devised and used for the automatic measurement of the positions of all the target crosses on the calibration plate employing image matching techniques. The results obtained from the successful calibration of a representative sample of CCD cameras and thermal video frame scanners are presented and discussed in detail. They provide much new and accurate information on the geometric characteristics of these types of infrared imager that will be invaluable to those undertaking photogrammetric measurements on the infrared images that are being acquired and used in military, medical, industrial and environmental applications. For the radiometric calibration of each imager, measurements of the grey level values were made over the whole of the image covering the target radiation source for a range of temperatures. Thus much original and valuable information on the radiometric characteristics of the imagers has been obtained from the work undertaken during this research project, more especially at lower operational temperatures. However the techniques used gave less good results at higher temperatures and these need to be modified if more useful results are to be obtained. Suggestions are made for the further development of the calibration technique, in particular for its use with low-resolution imagers such as the pyroelectric vidicon camera which have not been calibrated in this research project due to time and financial limitations

A mixed spaceborne sensor approach for surface modelling of an urban scene

Three-dimensional (3D) surface models are vital for sustainable urban management studies, and there is a nearly unlimited range of possible applications. Along-or across-track pairs from the same set of sensor imagery may not always be available or economical for a certain study area. Therefore, a photogrammetric approach is proposed in which a digital surface model (DSM) is extracted from a stereo pair of satellite images, acquired by different sensors. The results demonstrate that a mixed-sensor approach may offer a sound alternative to the more established along-track pairs. However, one should consider several criteria when selecting a suitable stereo pair. Two cloud-free acquisitions are selected from the IKONOS and QuickBird image archives, characterized by sufficient overlap and optimal stereo constellation in terms of complementarity of the azimuth and elevation angles. A densely built-up area in Istanbul, Turkey, covering 151 km(2) and with elevations ranging between sea level and approximately 160 m is presented as the test site. In addition to the general complexity of modelling the surface and elevation of an urban environment, multi-sensor image fusion has other particular difficulties. As the images are acquired from a different orbital pass, at a different date or instant and by a different sensor system, radiometric and geometric dissimilarities can occur, which may hamper the image-matching process. Strategies are presented for radiometric and geometric normalization of the multi-temporal and multi-sensor imagery and to deal with the differences in sensor characteristics. The accuracy of the generated surface model is assessed in comparison with 3D reference points, 3D rooftop vector data and surface models extracted from an along-track IKONOS stereo pair and an IKONOS triplet. When compared with a set of 35 reference GPS check points, the produced mixed-sensor model yields accuracies of 1.22, 1.53 and 2.96 m for the X, Y and Z coordinates, respectively, expressed in terms of root mean square errors (RMSEs). The results show that it is feasible to extract the DSM of a highly urbanized area from a mixed-sensor pair, with accuracies comparable with those observed from the DSM extracted from an along-track pair. Hence, the flexibility of reconstructing valuable elevation models is greatly increased by considering the mixed-sensor approach

Point-based and model-based geolocation analysis of airborne laser scanning data

Airborne laser scanning (ALS) is one of the most effective remote sensing technologies providing precise three-dimensional (3-D) dense point clouds. A large-size ALS digital surface model (DSM) covering the whole Istanbul province was analyzed by point-based and model-based comprehensive statistical approaches. Point-based analysis was performed using checkpoints on flat areas. Model-based approaches were implemented in two steps as strip to strip comparing overlapping ALS DSMs individually in three subareas and comparing the merged ALS DSMs with terrestrial laser scanning (TLS) DSMs in four other subareas. In the model-based approach, the standard deviation of height and normalized median absolute deviation were used as the accuracy indicators combined with the dependency of terrain inclination. The results demonstrate that terrain roughness has a strong impact on the vertical accuracy of ALS DSMs. From the relative horizontal shifts determined and partially improved by merging the overlapping strips and comparison of the ALS, and the TLS, data were found not to be negligible. The analysis of ALS DSM in relation to TLS DSM allowed us to determine the characteristics of the DSM in detail. © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)

Benchmarking and quality analysis of DEM generated from high and very high resolution optical stereo satellite data

The Working Group 4 of Commission I on ¿Geometric and Radiometric Modelling of Optical Spaceborne Sensors¿ provides on its website several stereo data sets from high and very high resolution spaceborne sensors. Among these are data from the 2.5 meter class like ALOS-PRISM and Cartosat-1 as well as, in near future, data from the highest resolution sensors (0.5 m class) like GeoEye-1 and Worldview-1 and -2. The region selected is an area in Catalonia, Spain, including city areas (Barcelona), rural areas and forests in flat and medium undulated terrain as well as steeper mountains. In addition to these data sets, ground truth data: orthoimages from airborne campaigns and Digital Elevation Models (DEM) produced by laser scanning, all data generated by the Institut Cartogràfic de Catalunya (ICC), are provided as reference for comparison. The goal is to give interested scientists of the ISPRS community the opportunity to test their algorithms on DEM generation, to see how they match with the reference data and to compare their results within the scientific community. A second goal is to develop further methodology for a common DEM quality analysis with qualitative and quantitative measures. Several proposals exist already and the working group is going to publish them on their website. But still there is a need for more standardized methodologies to quantify the quality even in cases where no better reference is available. The data sets, the goal of the benchmarking and first evaluation results are presented within the paper. Algorithms using area-based least squares matching are compared to those using additionally feature-based matching or newly developed algorithms from the Computer Vision community. The main goal though is to motivate further researchers to join the benchmarking and to discuss pros and cons of the methods as well as to trigger the process of establishing standardized DEM quality figures and procedures.JRC.DG.G.2-Global security and crisis managemen

Developing 3D geospatial database from terrestrial laser scanned data

Most major cities a rebeing managed spatially by 20 geo-DBMS, however, unlike Istanbul city it is in the verge of 3D spatial information system especially for the historical peninsular region. Thousands of its 3D objects (mainly buildings - old a nd new) are in the process of 3D da tabase development Istanbul city municipality is currently busy with various GIS projects including an initiative towards a 3D database for the city. This paper describes the development of 3D database from terrestrial laser scanned data where a leading geo -DAMS, i.e. Oracle Spatial 109 were utilised . Useful 3D geoinformation could be generated from such 3D database, thus the initiative would provide an excellent tool fo r the city's decision making process e.g. for the city planning purposes. and etc. The 3D geo-database approach described III this paper is certainly would be very beneficial 10 the city and other GIS users since the current and commercial GIS software face some difficulties in providing such GIS operations and information to the relevant authorities. The paper also highlight s new 3D spatial operations developed for possible spatial analysis of 3D objects (surface and underground objects)

Developing 3D geo DBMS for terrestrial laser scanning data

Terrestrial laser scan was used to capture data for historical peninsula region in Istanbul, Turkey. These datasets need to be managed efficiently in a 3D database management system. The 3D database is one of the products generated from mapping and GIS initiatives currently being undertaken by the city municipality. This paper describes the development of 3D database with the leading geo- DBMS, i.e. Oracle Spatial 10g for the historical peninsula region in Istanbul. From the database, some information of 3D object could be generated from such 3D database and this could be one of the tools for decision making for the city planning purposes as current GIS software faces some difficulties to perform such operations

Automated extraction of buildings from aerial LiDAR point cloud and digital imaging datasets for 3D cadastre - preliminary results

The demand for accurate 3D mapping of buildings has increased due to the spatial detail required by engineers, architects and city planners. An accurate information about location and dimension of building features is important for cadastral, city modeling, infrastructure mapping and safety analysis in an urban environment. LiDAR technology provides rapid, continuous and cost effective capability to acquire 3D geospatial information. In this paper, we present an automated approach for extracting building features from integrated aerial LiDAR point cloud and digital imaging datasets. Our approach is based on the assumption that the LiDAR data can be used to distinguish between high and low rise objects while the multispectral dataset can be used to filter out vegetation from the data. We make a use of LiDAR elevation and multiple echo attributes to extract building objects. Morphological operations are applied to the extracted building objects in order to complete their shapes and remove noise. We tested our automated buildings extraction approach on aerial LiDAR point cloud and digital imaging datasets of Istanbul city. The successful extraction of building objects validates our automated approach