bluuebunny/crossref_metadata_2025 huggingface dataset:
DIRECT GEOREFERENCING OF UAVS
Authors: Bláha M. , Eisenbeiss H. , Grimm D. , Limpach P.
Published: September 2012

Abstract. UAV systems have become an attractive data acquisition platform in emerging applications. As measuring instrument they extend the lineup of possible surveying methods in the field of geomatics. However, most of UAVs are equipped with low-cost navigation sensors such as GPS or INS, allowing a positioning accuracy of 3 to 5 m. As a result the acquired position- and orientation data fea- tures a low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level (e.g. direct georeferencing). In this paper we will analyze the potential of differential post-processing of GPS data from UAV in order to im- prove the positioning accuracy for applications basing on direct georeferencing. Subsequently, the obtained results are compared and verified with a track of the octocopter carried out with a total station simultaneously to the GPS data acquisition. The results show that the differential post-processing essentially improved the accuracy of the Falcon position data. Thereby the average offset be- tween the data sets (GPS data, track) and the corresponding standard deviation is 0.82 m and 0.45 m, respectively. However, under ideal conditions it is even possible to improve this positioning accuracy to the cm-range. Furthermore, there are still several sources of error such as the offset between the GPS antenna of the Falcon 8 and the prism which is used for the track. Considering this fact there is further room for improvement regarding the here discussed positioning method.
AUTONOMOUS UNMANNED HELICOPTER SYSTEM FOR REMOTE SENSING MISSIONS IN UNKNOWN ENVIRONMENTS
Authors: Merz T. , Chapman S.
Published: September 2012

Abstract. This paper presents the design of an autonomous unmanned helicopter system for low-altitude remote sensing. The proposed concepts and methods are generic and not limited to a speciﬁc helicopter. The development was driven by the need for a dependable, modular, and affordable system with sufﬁcient payload capacity suitable for both research and real-world deployment. The helicopter can be safely operated without a backup pilot in a contained area beyond visual range. This enables data collection in inaccessible or dangerous areas. Thanks to its terrain following and obstacle avoidance capability, the system does not require a priori information about terrain elevation and obstacles. Missions are speciﬁed in state diagrams and ﬂight plans. We present performance characteristics of our system and show results of its deployment in real-world scenarios. We have successfully completed several dozen infrastructure inspection missions and crop monitoring missions facilitating plant phenomics studies.
DEVELOPMENT OF A NEW MULTI-PURPOSE UAS FOR SCIENTIFIC APPLICATION
Authors: Scholtz A. , Kaschwich C. , Krüger A. , Kufieta K. , Schnetter P. , Wilkens C.-S. , Krüger T. , Vörsmann P.
Published: September 2012

Abstract. Project SUBVENTO is a joint research project of the research facility Technische Universität Braunschweig and the industry partner BBR - Baudis Bergmann Rösch Verkehrstechnik GmbH in close cooperation with the German Federal Agency for Technical Relief (THW). The Project is funded within the European Regional Development Fund (EFRE) allocated by the European Union. Therein an integrated system for the fast and automated remote detection of heat sources using an infrared camera is being developed. For a precise detection of fires or persons a very accurate navigation system including the algorithms and the hardware is required. Furthermore additional sensors like a multispectral camera applicable in small unmanned aerial vehicles (UAVs) should be implemented. Since the mentioned sensor equipment exceeds the current UAVs' payload limit, a new Carolo type aircraft with a wingspan of 3.6 m is designed. It has an increased payload capability and an extended flight time. This is possible due to an optimized aerodynamic layout and a high efficient propulsion system. Das Projekt SUBVENTO ist ein Verbund-Forschungsprojekt der Technischen Universität Braunschweig sowie dem Industriepartner BBR – Baudis Bergmann Rösch Verkehrstechnik GmbH und wird in enger Zusammenarbeit mit dem Deutschen Technischen Hilfswerk (THW) durchgeführt. Das Projekt wird über den Europäischen Fond zur regionalen Entwicklung (EFRE) durch die Europäische Union gefördert. In diesem Projekt wird ein integriertes System zur schnellen und automatischen Detektion von Hitzequellen mittels einer Infrarotkamera entwickelt. Zur genauen Positionsbestimmung der Feuer oder Personen ist ein präzises Navigationssystem, bestehend aus den Navigationsalgorithmen und der verwendeten Hardware, nötig. Des Weiteren sollen zusätzliche für Unbemannte Flugzeuge (UAVs) geeignete Sensoren, wie beispielsweise eine Multispektralkamera integriert werden. Da dieses Sensorpaket die Nutzlast der bisher verfügbaren Flugzeuge der Carolo Familie übersteigt, wird ein neues Muster mit einer Spannweite von 3,6 m entwickelt. Durch eine verbesserte aerodynamische Auslegung und ein effizientes Antriebssystem wird die Flugzeit und Nutzlastkapazität gesteigert.
AERIAL SURVEYING UAV BASED ON OPEN-SOURCE HARDWARE AND SOFTWARE
Authors: Mészáros J.
Published: September 2012

Abstract. In the last years the functionality and type of UAV-systems increased fast, but unfortunately these systems are hardly available for researchers in some cases. A simple and low-cost solution was developed to build an autonomous aerial surveying airplane, which can fulfil the necessities (aerial photographs with very-high resolution) of other departments at the university and very useful and practical for teaching photogrammetry.. The base was a commercial, remote controlled model airplane and an open-source GPS/IMU system (MatrixPilot) was adapted to achieve the semi-automatic or automatic stabilization and navigation of the model airplane along predefined trajectory. The firmware is completely open-source and easily available on the website of the project. The first used camera system was a low-budget, low-quality video camera, which could provide only 1.2 megapixel photographs or low resolution video depending on the light conditions and the desired spatial resolution. A field measurement test was carried out with the described system: the aerial surveying of an undiscovered archaeological site, signed by a crop-mark in mountain Pilis (Hungary).
OPEN SOURCE IMAGE-PROCESSING TOOLS FOR LOW-COST UAV-BASED LANDSLIDE INVESTIGATIONS
Authors: Niethammer U. , Rothmund S. , Schwaderer U. , Zeman J. , Joswig M.
Published: September 2012

Abstract. In recent years, the application of unmanned aerial vehicles (UAVs) has become more common and the availability of lightweight digital cameras has enabled UAV-systems to represent affordable and practical remote sensing platforms, allowing flexible and high- resolution remote sensing investigations. In the course of numerous UAV-based remote sensing campaigns significant numbers of airborne photographs of two different landslides have been acquired. These images were used for ortho-mosaic and digital terrain model (DTM) generation, thus allowing for high-resolution landslide monitoring. Several new open source image- and DTM- processing tools are now providing a complete remote sensing working cycle with the use of no commercial hard- or software.
DIGITAL CAMERA CALIBRATION USING IMAGES TAKEN FROM AN UNMANNED AERIAL VEHICLE
Authors: Pérez M. , Agüera F. , Carvajal F.
Published: September 2012

Abstract. For calibrating the camera, an accurate determination of the interior orientation parameters is needed. For more accurate results, the calibration images should be taken under conditions that are similar to the field samples. The aim of this work is the establishment of an efficient and accurate digital camera calibration method to be used in particular working conditions, as it can be found with our UAV (Unmanned Aerial Vehicle) photogrammetric projects. The UAV used in this work was md4-200 modelled by Microdrones. The microdrone is also equipped with a standard digital non- metric camera, the Pentax Optio A40 camera. To find out the interior orientation parameters of the digital camera, two calibration methods were done. A lab calibration based on a flat pattern and a field calibration were fulfilled. To carry out the calibration, Photomodeler Scanner software was used in both cases. The lab calibration process was completely automatic using a calibration grid. The focal length was fixed at widest angle and the network included a total of twelve images with± 90º roll angles. In order to develop the field calibration, a flight plan was programmed including a total of twelve images. In the same way as in the lab calibration, the focal length was fixed at widest angle. The field test used in the study was a flat surface located on the University of Almería campus and a set of 67 target points were placed. The calibration field area was 25 × 25 m approximately and the altitude flight over ground was 50 m. After the software processing, the camera calibration parameter values were obtained. The paper presents the process, the results and the accuracy of these calibration methods. The field calibration method reduced the final total error obtained in the previous lab calibration. Furthermore the overall RMSs obtained from both methods are similar. Therefore we will apply the field calibration results to all our photogrammetric projects in which the flight high will be close to 50 m.
THREE-DIMENSIONAL BUILDING RECONSTRUCTION USING IMAGES OBTAINED BY UNMANNED AERIAL VEHICLES
Authors: Wefelscheid C. , Hänsch R. , Hellwich O.
Published: September 2012

Abstract. Unmanned Aerial Vehicles (UAVs) offer several new possibilities in a wide range of applications. One example is the 3D reconstruction of buildings. In former times this was either restricted by earthbound vehicles to the reconstruction of facades or by air-borne sensors to generate only very coarse building models. This paper describes an approach for fully automatic image-based 3D reconstruction of buildings using UAVs. UAVs are able to observe the whole 3D scene and to capture images of the object of interest from completely different perspectives. The platform used by this work is a Falcon 8 octocopter from Ascending Technologies. A slightly modiﬁed high-resolution consumer camera serves as sensor for data acquisition. The ﬁnal 3D reconstruction is computed ofﬂine after image acquisition and follows a reconstruction process originally developed for image sequences obtained by earthbound vehicles. The per- formance of the described method is evaluated on benchmark datasets showing that the achieved accuracy is high and even comparable with Light Detection and Ranging (LIDAR). Additionally, the results of the application of the complete processing-chain starting at image acquisition and ending in a dense surface-mesh are presented and discussed.
LANDSLIDE MAPPING USING IMAGERY ACQUIRED BY A FIXED-WING UAV
Authors: Rau J. Y. , Jhan J. P. , Lo C. F. , Lin Y. S.
Published: September 2012

Abstract. In Taiwan, the average annual rainfall is about 2,500 mm, about three times the world average. Hill slopes where are mostly under meta-stable conditions due to fragmented surface materials can easily be disturbed by heavy typhoon rainfall and/or earthquakes, resulting in landslides and debris flows. Thus, an efficient data acquisition and disaster surveying method is critical for decision making. Comparing with satellite and airplane, the unmanned aerial vehicle (UAV) is a portable and dynamic platform for data acquisition. In particularly when a small target area is required. In this study, a fixed-wing UAV that equipped with a consumer grade digital camera, i.e. Canon EOS 450D, a flight control computer, a Garmin GPS receiver and an attitude heading reference system (AHRS) are proposed. The adopted UAV has about two hours flight duration time with a flight control range of 20 km and has a payload of 3 kg, which is suitable for a medium scale mapping and surveying mission. In the paper, a test area with 21.3 km2 in size containing hundreds of landslides induced by Typhoon Morakot is used for landslides mapping. The flight height is around 1,400 meters and the ground sampling distance of the acquired imagery is about 17 cm. The aerial triangulation, ortho-image generation and mosaicking are applied to the acquired images in advance. An automatic landslides detection algorithm is proposed based on the object-based image analysis (OBIA) technique. The color ortho-image and a digital elevation model (DEM) are used. The ortho-images before and after typhoon are utilized to estimate new landslide regions. Experimental results show that the developed algorithm can achieve a producer's accuracy up to 91%, user's accuracy 84%, and a Kappa index of 0.87. It demonstrates the feasibility of the landslide detection algorithm and the applicability of a fixed-wing UAV for landslide mapping.
UAS FOR GEO-INFORMATION: CURRENT STATUS AND PERSPECTIVES
Authors: Haarbrink R. B.
Published: September 2012

Abstract. Recent and ongoing developments of state-of-the-art sensor technologies have resulted in smaller and lighter photogrammetric cameras with IMU, lidar scanners and other sensors that can now be integrated with and mounted on the larger Light UAS. This paper describes as an example the successful automatic flight of the 50-megapixel DigiCAM with AEROcontrol IMU developed by IGI flown on Geocopter's GC-201 unmanned helicopter system. The operational and technical requirements of UAS defined in new legislation remain however the safeguard to protect people and costly sensor payload assets. The current prospects of UAS-g face additional challenges related to end-user awareness and the return on investment. The current status of UAS legislation is given in this paper. This legislation justifies UAS-g operations of mapping coastal zones, forests, agricultural fields, and open mines. Sooner return on investment happens when the UAS legislation will be opening up airspace over urban areas (Class 2 approved UAS-g), to longer distances (BLOS operations), and to higher altitudes. UAS-g flights then become feasible to the maximum extent for cadastral mapping of larger areas, oil and gas pipeline monitoring, power line surveys, dike inspection, and highway and railway mapping.
SIMPLIFIED BUILDING MODELS EXTRACTION FROM ULTRA-LIGHT UAV IMAGERY
Authors: Küng O. , Strecha C. , Fua P. , Gurdan D. , Achtelik M. , Doth K.-M. , Stumpf J.
Published: September 2012

Abstract. Generating detailed simpliﬁed building models such as the ones present on Google Earth is often a difﬁcult and lengthy manual task, requiring advanced CAD software and a combination of ground imagery, LIDAR data and blueprints. Nowadays, UAVs such as the AscTec Falcon 8 have reached the maturity to offer an affordable, fast and easy way to capture large amounts of oblique images covering all parts of a building. In this paper we present a state-of-the-art photogrammetry and visual reconstruction pipeline provided by Pix4D applied to medium resolution imagery acquired by such UAVs. The key element of simpliﬁed building models extraction is the seamless integration of the outputs of such a pipeline for a ﬁnal manual reﬁnement step in order to minimize the amount of manual work.
STRAIGHT-LINE PATH FOLLOWING IN WINDY CONDITIONS
Authors: Brezoescu A. , Castillo P. , Lozano R.
Published: September 2012

Abstract. A straight-line following controller for a small and light airplane ﬂying in windy conditions is proposed. In a ﬁrst time, the lateral dynamics of the plane are derived and the error deviation velocity with respect to the desired trajectory is computed. A simple nonlinear control law is developed in order to impose a linear behavior for the airplane position and to track the desired trajectory. Several simulations, taking into account quasi-constant wind disturbances, are performed to analyze the performance of the closed-loop system. Improved results are obtained including the airplane orientation to counter the wind as an input for the ﬂight planning. In order to validate the proposed control scheme an airplane has been developed based on the classic aerodynamic layout. Future work will introduce the experimental results when applying in real-time the proposed control algorithm.
A PRECISE, LOW-COST RTK GNSS SYSTEM FOR UAV APPLICATIONS
Authors: Stempfhuber W. , Buchholz M.
Published: September 2012

Abstract. High accuracy with real-time positioning of moving objects has been considered a standard task of engineering geodesy for 10 to 15 years. An absolute positioning accuracy of 1–3 cm is generally possible worldwide and is further used in many areas of machine guidance (machine control and guidance), and farming (precision farming) as well as for various special applications (e.g. railway trolley, mining, etc.). The cost of the measuring instruments required for the use of geodetic L1/L2 receivers with a local reference station amounts to approximately USD 30,000 to 50,000. Therefore, dual frequency RTK GNSS receivers are not used in the mass market. Affordable GPS/GNSS modules have already reached the mass market in various areas such as mobile phones, car navigation, the leisure industry, etc. Kinematic real-time positioning applications with centimetre or decimetre levels could also evolve into a mass product. In order for this to happen, the costs for such systems must lie between USD 1,000 to 2,000. What exactly low-cost means is determined by the precise specifications of the given individual application. Several university studies in geodesy focus on the approach of high-accuracy positioning by means of single frequency receivers for static applications [e.g. GLABSCH et. al. 2009, SCHWIEGER and GLÄSER 2005, ALKAN 2010, REALINI et. al. 2010, KORTH and HOFMANN 2011]. Although intelligent approaches have been developed that compute a trajectory in the post-processing mode [REALINI et. al., 2010], at present, there are only a very few GNSS Low-Cost Systems that enable real-time processing. This approach to precise position determination by means of the computation of static raw data with single frequency receivers is currently being explored in a research project at the Beuth Hochschule für Technik Berlin – and is being further developed for kinematic applications. The project is embedded in the European Social Fund. It is a follow-up project in the area of static positioning with single GNSS frequency receivers [KORTH and HOFMANN, 2011].
A UAV-BASED ROE DEER FAWN DETECTION SYSTEM
Authors: Israel M.
Published: September 2012

Abstract. This paper presents a UAV based remote sensing system for the detection of fawns in the meadows. There is a high demand because during pasture mowing many wild animals, especially roe deer fawns are killed by mowing machines. The system was tested in several real situations especially with diﬀering weather and iluminating conditions. Its primary sensor is a lightweight thermal infrared camera. The images are captured onboard of the ﬂight system and also transmitted as analog video stream to the ground station, where the user can follow the camera live stream on a monitor for manual animal detection. Beside a high detection rate a fast workﬂow is another very important objective for this application. Therefore a waypoint planning software was developed that accelerates the workﬂow. At adequate illuminating and weather conditions the presented UAV-based fawn detection via thermal imaging is a comfortable, fast and reliable method.
SENSITIVITY ANALYSIS OF UAV-PHOTOGRAMMETRY FOR CREATING DIGITAL ELEVATION MODELS (DEM)
Authors: Rock G. , Ries J. B. , Udelhoven T.
Published: September 2012

Abstract. This study evaluates the potential that lies in the photogrammetric processing of aerial images captured by unmanned aerial vehicles. UAV-Systems have gained increasing attraction during the last years. Miniaturization of electronic components often results in a reduction of quality. Especially the accuracy of the GPS/IMU navigation unit and the camera are of the utmost importance for photogrammetric evaluation of aerial images. To determine the accuracy of digital elevation models (DEMs), an experimental setup was chosen similar to the situation of data acquisition during a field campaign. A quarry was chosen to perform the experiment, because of the presence of different geomorphologic units, such as vertical walls, piles of debris, vegetation and even areas. In the experimental test field, 1042 ground control points (GCPs) were placed, used as input data for the photogrammetric processing and as high accuracy reference data for evaluating the DEMs. Further, an airborne LiDAR dataset covering the whole quarry and additional 2000 reference points, measured by total station, were used as ground truth data. The aerial images were taken using a MAVinci Sirius I – UAV equipped with a Canon 300D as imaging system. The influence of the number of GCPs on the accuracy of the indirect sensor orientation and the absolute deviation’s dependency on different parameters of the modelled DEMs was subject of the investigation. Nevertheless, the only significant factor concerning the DEMs accuracy that could be isolated was the flying height of the UAV.
CHARACTERISTICS OF VERY HIGH RESOLUTION OPTICAL SATELLITES FOR TOPOGRAPHIC MAPPING
Authors: Jacobsen K.
Published: September 2012

Abstract. The ground resolution of optical satellites now overlaps with the ground resolution of aerial images. The radiometric and geometric quality of the satellite images can be compared with original digital aerial images and is better as corresponding analog photos. Important parameters for the operational handling of the very high resolution satellite images as imaging capacity, revisit time and rotation speed, important for getting stereo pairs and the flexibility of imaging of different areas, and effective image resolution are shown in detail. The reason for changed spectral range of GeoEye-1 and WorldView-2 against preceding systems is explained with its consequences to pan-sharpening. Scene orientation today is not a problem, so approximations are not justified anymore. With the improved possibility of stereoscopic coverage within the orbit, digital elevation models operationally can be generated. For some types of automatic image matching epipolar images are required. Based on images projected to a plane with constant height or even a rough height model a rotation of the satellite images to the base direction is satisfying as quasi epipolar images. The remaining discrepancies against theoretical strict epipolar images are estimated.
AN ADAPTIVE MULTI-CHANNEL SPECTROELLIPSOMETER FOR ECOLOGICAL MONITORING
Authors: Mkrtchyan F. A. , Kovalev V. I. , Klimov V. V.
Published: September 2012

Abstract. The creation of multichannel polarization optical instrumentation and use of spectroellipsometric technology are very important for the real-time ecological control of aquatic environment. Spectroellipsometric devices give us high precision of measurements. This report is aimed to describe: •A technology of combined use of spectroellipsometry and algorithms of identification and recognition that allowed the creation of a standard integral complex of instrumental, algorithmic, modular and software tools for the collection and processing of data on the aquatic environment quality with forecasting and decision - making functions. •A compact measuring - information multichannel spectroellipsometric system (device) for monitoring the quality of aquatic environment, that is based on the combined use of spectroellipsometry and training, classification, and identification algorithms. This spectroellipsometric system will differ from modern foreign analogues by the use of a new and very promising method of ellipsometric measurements, an original element base of polarization optics and a complex mathematical approach to estimating the quality of a water object subjected to anthropogenic influence.Unlike foreign analogues, the system has no rotating polarization elements. This allows one to increase the signal-to-noise ratio and the long-term stability of measurements, to simplify and reduce the price of multichannel spectroellipsometers. The system will be trainable to the recognition of the pollutants of aquatic environment. A spectroellipsometer in laboratories of V.A. Kotelnikov's Institute of Radioengineering and Electronics, Russian Academy of Sciences is designed for in-situ real time measurements of spectra of ellipsometric parameters Psi and Delta with consequent changeover to spectra of transmitted and reflected signal from water media in frames of used physical model of water environment.
CONDITIONAL RANDOM FIELDS FOR THE CLASSIFICATION OF LIDAR POINT CLOUDS
Authors: Niemeyer J. , Mallet C. , Rottensteiner F. , Sörgel U.
Published: September 2012

Abstract. In this paper we propose a probabilistic supervised classification algorithm for LiDAR (Light Detection And Ranging) point clouds. Several object classes (i.e. ground, building and vegetation) can be separated reliably by considering each point's neighbourhood. Based on Conditional Random Fields (CRF) this contextual information can be incorporated into classification process in order to improve results. Since we want to perform a point-wise classification, no primarily segmentation is needed. Therefore, each 3D point is regarded as a graph's node, whereas edges represent links to the nearest neighbours. Both nodes and edges are associated with features and have effect on the classification. We use some features available from full waveform technology such as amplitude, echo width and number of echoes as well as some extracted geometrical features. The aim of the paper is to describe the CRF model set-up for irregular point clouds, present the features used for classification, and to discuss some results. The resulting overall accuracy is about 94 %.
AUTOMATIC TRAINING SITE SELECTION FOR AGRICULTURAL CROP CLASSIFICATION: A CASE STUDY ON KARACABEY PLAIN, TURKEY
Authors: Ozdarici Ok A. , Akyurek Z.
Published: September 2012

Abstract. This study implements a traditional supervised classification method to an optical image composed of agricultural crops by means of a unique way, selecting the training samples automatically. Panchromatic (1m) and multispectral (4m) Kompsat-2 images (July 2008) of Karacabey Plain (~100km2), located in Marmara region, are used to evaluate the proposed approach. Due to the characteristic of rich, loamy soils combined with reasonable weather conditions, the Karacabey Plain is one of the most valuable agricultural regions of Turkey. Analyses start with applying an image fusion algorithm on the panchromatic and multispectral image. As a result of this process, 1m spatial resolution colour image is produced. In the next step, the four-band fused (1m) image and multispectral (4m) image are orthorectified. Next, the fused image (1m) is segmented using a popular segmentation method, Mean- Shift. The Mean-Shift is originally a method based on kernel density estimation and it shifts each pixel to the mode of clusters. In the segmentation procedure, three parameters must be defined: (i) spatial domain (hs), (ii) range domain (hr), and (iii) minimum region (MR). In this study, in total, 176 parameter combinations (hs, hr, and MR) are tested on a small part of the area (~10km2) to find an optimum segmentation result, and a final parameter combination (hs=18, hr=20, and MR=1000) is determined after evaluating multiple goodness measures. The final segmentation output is then utilized to the classification framework. The classification operation is applied on the four-band multispectral image (4m) to minimize the mixed pixel effect. Before the image classification, each segment is overlaid with the bands of the image fused, and several descriptive statistics of each segment are computed for each band. To select the potential homogeneous regions that are eligible for the selection of training samples, a user-defined threshold is applied. After finding those potential regions, the training pixels are automatically selected and labelled. Thereafter, those training pixels are utilized in a traditional Maximum Likelihood Classification to classify five crop types namely; corn, tomato/pepper, rice, sugar beet, and wheat. The accuracy of the classification is evaluated in pixel-based manner with the help of a reference map including crop information of the area. Promising results are achieved for pixel-based approach. Based on the error matrices used in the evaluation, overall accuracy of the pixel-based analysis is computed as 89.31%. Similar to the overall accuracies, high individual class accuracies are obtained as well. The results point out that automatically collecting the training samples by extracting representative homogenous areas significantly increases the speed of the classification and minimizes the human interaction. The results also confirm that the proposed approach is highly appropriate for the extraction of representative homogenous training areas.
POTENTIAL OF DENSE MATCHING FOR THE GENERATION OF HIGH QUALITY DIGITAL ELEVATION MODELS
Authors: Rothermel M. , Haala N.
Published: September 2012

Abstract. Until recently, the acquisition of high quality Digital Elevation Models was dominated by the use of airborne LiDAR. However, the increasing quality of digital airborne cameras in combination with recent improvements in matching algorithms meanwhile allow for the automatic image based collection as a suitable alternative. Within the paper, these progresses will be demonstrated on the example of photogrammetric DEM generation using the Semi-Global Matching (SGM) stereo method. Since this approach aims at a pixel-wise matching, dense 3D point clouds can be generated. The tests described in the paper are based on data collected from different digital airborne cameras at various flight scenarios during a recent test on photogrammetric 3D data capture. By these means, the impact of different stereo configurations on the quality of the final outcome can be evaluated and compared to already available test results. Special interest is also paid to the analysis and combination of multiple stereo image pairs with different base- to-height ratios, which can be used efficiently to increase the accuracy and reliability of the matching result.
Feature selection from high resolution remote sensing data for biotope mapping
Authors: Bindel M. , Hese S. , Berger C. , Schmullius C.
Published: September 2012

Abstract. Mapping of Landscape Protection Areas with regard to user requirements for detailed land cover and biotope classes has been limited by the spatial and temporal resolution of Earth observation data. The synergistic use of new generation optical and SAR data may overcome these limitations. The presented work is part of the ENVILAND-2 project, which focuses on the complementary use of RapidEye and TerraSAR-X data to derive land cover and biotope classes as needed by the Environmental Agencies. The goal is to semi-automatically update the corresponding maps by utilising more Earth observation data and less field work derived information. Properties of both sensors are used including the red edge band of the RapidEye system and the high spatial and temporal resolution TerraSAR-X data.The main part of this work concentrates on the process of feature selection. Based upon multi-temporal optical and SAR data various features like textural measurements, spectral features and vegetation indices can be computed. The resulting information stacks can easily exceed hundreds of layers. The goal of this work is to reduce these information layers to get a set of decorrelated features for the classification of biotope types. The first step is to evaluate possible features. Followed by a feature extraction and pre-processing. The pre-processing contains outlier removal and feature normalization. The next step describes the process of feature selection and is divided into two parts. The first part is a regression analysis to remove redundant information. The second part constitutes the class separability analysis. For the remaining features and for every class combination present in the study area different separability measurements like divergence or Jeffries-Matusita distance are computed. As result there is a set of features for every class providing the highest class separability values. As the final step an evaluation is performed to estimate how much features for a class are needed to get the highest classification accuracy by employing an object-based classification approach and to assess how classification accuracy changes with various numbers of features. The study is carried out for two case studies: 1. Rostocker Heide; (Special Area of Conservation (SAC, EC Habitats Directive)), Mecklenburg-Vorpommern and 2. Elsteraue (Landscape Protection Area) near Groitzsch, Sachsen. Both test sites are located in Germany.
Modeling spacecraft oscillations in HRSC images of Mars Express
Authors: Bostelmann J. , Heipke C.
Published: September 2012

Abstract. Since January 2004 the High Resolution Stereo Camera (HRSC) is mapping planet Mars. The multi-line sensor on board the ESA Mission Mars Express images the Martian surface with a resolution of up to 12m per pixel in three dimensions and in color. As part of the Photogrammetric/Cartographic Working Group of the HRSC Science Team the Institute of Photogrammetry and GeoInformation (IPI) of the Leibniz Universit¨at Hannover is involved in photogrammetrically processing the HRSC image data. To derive high quality 3D surface models, color orthoimages or other products, the accuracy of the observed position and attitude information in many cases should be improved. This is carried out via a bundle adjustment. In a considerable number of orbits the results of the bundle adjustment are disturbed by high frequency oscillations. This paper describes the impact of the high frequency angular spacecraft movement to the processing results of the last seven years of image acquisition and how the quality of the HRSC data products is significantly improved by modeling these oscillations.
SEMIGLOBAL MATCHING RESULTS ON THE ISPRS STEREO MATCHING BENCHMARK
Authors: d'Angelo P. , Reinartz P.
Published: September 2012

Abstract. Digital surface models can be efficiently generated with automatic image matching from optical stereo images. The Working Group 4 of Commission I on "Geometric and Radiometric Modelling of Optical Spaceborne Sensors" provides a matching benchmark dataset with several stereo data sets from high and very high resolution space borne stereo sensors at http://www.commission1.isprs.org/wg4/ . The selected regions are in Catalonia, Spain, and include three test areas, covering city areas, rural areas and forests in flat and medium undulated terrain as well as steep mountainous terrain. In this paper, digital surface models (DSM) are derived from the Cartosat-1 and Worldview-1 datasets using Semiglobal Matching. The resulting DSM are evaluated against the first pulse returns of the LIDAR reference dataset provided by the Institut Cartogr`afic de Catalunya (ICC), using robust accuracy measures.
MAN-MADE AREA CHANGE DETECTION BASED ON MASK WITH HJ IMAGE AND TM IMAGE
Authors: He X.
Published: September 2012

Abstract. Change detection of man-made area with HJ image and TM image is difficult mostly due to HJ image having less bands and lower spectral response. In this paper, after the image analysis of HJ image and TM image, a new change detection method based on several times mask of HJ image was used to get really changed man-made area. Several times mask was applied here to narrow the detecting object range. Firstly, coarse man-made areas of new HJ image were extracted by support vector machine (SVM) classer in the mask image based on texture and spectral extraction, while old man-made areas were picked up by SVM classer directly in TM original image. Secondly, after algebra change detection between extracted man-made areas of two images, candidate changed areas were used as mask for HJ image again, and then extractions by SVM classer in the mask images were applied to get really changed man-made area. Through these steps, a high accuracy of man-made area change detection between HJ image and TM image could be got, which had been proved by the experience and accuracy analysis.
DERIVATION OF TREE CANOPY COVER BY MULTISCALE REMOTE SENSING APPROACH
Authors: Wu W.
Published: September 2012

Abstract. In forestry, treecanopy cover (CC) is an important biophysical indicator for characterizing terrestrial ecosystemsand modeling global biogeochemical cycles, e.g., woody biomass estimation, carbon balance analysis (sink/emission). However, currently available CC product cannot fully meet what we need while conducting woody biomass estimation in tropical savannas.It is thus necessary to develop an approach to estimate more reliable CC. Based on the acquisition of multisensor and multiresolution dataset, this study introduces an innovative multiscalemethod for this purpose taking the multiple savannas country Sudan as an example. The procedure includes: (1)Measurement of CC using Google Earth Pro in which very high resolution images such as QuickBirdand GeoEye images are available, and then the measured CC was coupled with atmospherically corrected and reflectance-based 16 frames of Landsat ETM+ vegetation indices (EVI, SARVI and NDVI)dated Nov 1999-2002 to establish the CC-VIs models; it was noted that among these indices NDVI indicates the best correlation with CC (CC = 153.09NDVI– 10.12, R2 = 0.91);(2) The NDVI of Landsat ETM+ was calibrated against MODIS NDVI of the same time period (Nov 2002)to make sure that model developed from Landsat ETM+ data can be applied to MODIS data for upscalingto regional scale study; (3)Time-series MODIS NDVI data of the period Jan 2002–Dec 2009 (MODIS13Q1, 250m, 186 acquisitions) were acquired and used to decompose the woody component(NDVI) from seasonal changeand herbaceous component by time-series analysis;(4) The equation obtained in step 1 was applied to the decomposed MODIS woody NDVI images to derive country scale CC data. The produced CC was checked against the 287 ground measured CC obtained in step 1 and a good agreement (R2 = 0.53-0.71) was found.It is hence concluded that the proposed multiscale approach is effective, operational and can be applied for reliable estimation of regional and even continental scales CC data.
STUDY OF WETLAND INFORMATION ENHANCEMENT APPROACH BASED ON LANDSAT ETM DATA
Authors: Zhang Z. , Tian S. , Dang W.
Published: September 2012

Abstract. Wetland is a versatile, rich biological diversity ecosystems on the planet which is one of the most important living environment of human beings. As the representative data of mid-resolution data, ETM data is widely used in Resources survey by its unique advantage in band set. Based on the analysis of water, terrestrial vegetation and aquatic vegetation's spectral characteristic, this article uses ratio composite method (ETM band3/band5(R)、band2/band4(G)、band3/band7(B) to enhance water and wetland information combining with the band characteristics of ETM data. Practice has proved that this method has unique advantage in enhancing water and wetland information, and can improve the accuracy and efficiency in automatic Extraction of wetland information.
GEOSPATIAL SERVICE WEB: FROM DATA, INFORMATION, AND KNOWLEDGE SHARING TO WEB GEOINTELLIGENCE
Authors: Gong J. , Wu H. , Yue P. , Zhu X. , Gao W.
Published: September 2012

Abstract. The existing Spatial Data Infrastructure applications or virtual globes allow users to experiment with these tools for sharing and exploration of geospatial data. A typical application is the recently launched MapWorld, an interactive geospatial data browser developed based on GeoGlobe. Geospatial Service Web goes further by providing a geospatial infrastructure that integrates various geospatial-related resources through the Web and service technologies. The development of the Geospatial Service Web will be the establishment of a platform where data, information, and knowledge can be shared and exchanged in an interoperable and interworkable way. The fulfilment of this platform requires the integration of geospatial data acquisition system, data transformation system, distributed spatial data collection, high-capability server system, and large volume storage system etc., and exploration and extraction of useful information and knowledge from oceans of data. These are together known as Web-based Geospatial Intelligence (i.e. Web GeoIntelligence), which is an important content of the Geospatial Service Web.
A COMPARATIVE STUDY OF SPATIAL DATA HARVEST STANDARDS
Authors: Yan Y. , Li G. , Xie J. , Guo L.
Published: September 2012

Abstract. So far, thousand kinds of Spatial Data were acquired, produced, published and used for specialized applications. Heterogeneity is obviously one key problem for spatial data in the process of its creating, structuring or managing. The heterogeneity keeps the complete and variety of spatial data, but induces the difficulty of describing, publishing, sharing, interoperability or metadata harvesting. Decentralized, multi-organization and synchronization are the major features of the next generation spatial data service infrastructure. Standard research on geospatial metadata harvesting and data service is becoming a research focus. More and more organizations and consortiums (e.g. ISO/TC 211, OGC) drafted and released their geospatial metadata and service standards. However, these standards are diverse in order to fit to different spatial data format and research fields, which makes spatial data owner hard to choose standard. The paper focuses on analyzing metadata harvesting from multi-organizations archives, including Spatial Data description, publishing, sharing, and interoperability. Several of most widely used Spatial Data standards are introduced, and compared. Advices on how to choose the standards are given for Spatial Data owner.
SECOND GENERATION MOSAIC:A NOVEL MECHANISM BASED ON REFERENCE DATABASE FOR MAP UPDATING
Authors: Hu G. , Bignone F.
Published: September 2012

Abstract. A totally new automatic workflow mechanism, named Second generation Mosaic module, based on the well-known Pixel Factory system, will be introduced here, which enables existing digital orthoimages and mosaics to be quickly updated. The process extracts all required parameters from the reference database to be able to perform automatic bundle adjustment and radiometric adaptation.In this paper, two examples for both satellite data and aerial data processed based on this mechanism will be presented here and discussed. Finally, the cost reduction will also be analysed according to the real mapping updating project.In a final statement, this paper will present an integrated solution named second generation mosaic module based on the well-known Pixel Factory system which is completely dedicated to fast processing of photogrammetric products Thanks to this integrated hardware and software solution, it is even possible to manage large data volume quickly in order to have precise map updating information as soon as possible after acquisition.
COMPARISON OF GOSAT CAI AND SPOT VGT NDVI DATA WITH DIFFERENT SEASON AND LAND COVER IN EAST ASIA
Authors: Liu Y. , Wang X. , Guo M. , Tani H.
Published: September 2012

Abstract. The Normalized Difference Vegetation Index (NDVI) has become one of the most widely used indices in remote sensing applications in a variety of fields. Many studies have compared the NDVI values for different satellite sensors. Nowadays, the Greenhouse Gases Observing Satellite (GOSAT) was successfully launched on January 23, 2009. It is used to monitor greenhouse gases on the Earth's surface and also has a sensor, the Cloud Aerosol Imager (CAI), that senses red and near infrared spectrums. It can also process NDVI data. Therefore, we are first compare GOSAT CAI and SPOT VGT NDVI data in different seasonal and land cover in East Asian, to explore the relationship between the two types of datasets, and to discuss the possibility of extending SPOT VGT data using GOSAT CAI NDVI data for the same area. We used GOSAT CAI Level 3 data to derive 10–day composite NDVI values for the East Asia region for November 2009 and January, April and July 2010 using the maximum value composite (MVC) method. We compared these values with 10–day composite SPOT VGT NDVI data for the same period. The results show that the correlation coefficients of regression analysis generally revealed a strong correlation between NDVI from the two sensors in November 2009 and January, April and July 2010 (0.88, 0.85, 0.77 and 0.74, respectively). The differences place may be affected by cloud cover. From the combined analysis of seasonal changes and land cover, we found that the correlations between the SPOT VGT and the GOSAT CAI NDVI data are less affected by seasonal change and the SPOT VGT data is more sensitive to high vegetation coverage than the GOSAT CAI data. In the future, through continued monitoring and processing by cloud removal technology, the accuracy of GOSAT CAI NDVI data will be further improved and thus be more widely used.
MULTI-SENSOR NETWORK FOR LANDSLIDES SIMULATION AND HAZARD MONITORING - DESIGN AND DEPLOYMENT
Authors: Wu H. , Qiao G. , Lu P. , Feng T. , Tian Y. , Fan H. , Liu S. , Liu C. , Tong X. , Wang W. , Shen Y. , Guan Z. , Li R.
Published: September 2012

Abstract. This paper describes a newly developed multi-sensor network system for landslide and hazard monitoring. Landslide hazard is one of the most destructive natural disasters, which has severely affected human safety, properties and infrastructures. We report the results of designing and deploying the multi-sensor network, based on the simulated landslide model, to monitor typical landslide areas and with a goal to predict landslide hazard and mitigate damages. The integration and deployment of the prototype sensor network were carried out in an experiment area at Tongji University in Shanghai. In order to simulate a real landslide, a contractible landslide body is constructed in the experiment area by 7m*1.5m. Then, some different kind of sensors, such as camera, GPS, crackmeter, accelerometer, laser scanning system, inclinometer, etc., are installed near or in the landslide body. After the sensors are powered, continuous sampling data will be generated. With the help of communication method, such as GPRS, and certain transport devices, such as iMesh and 3G router, all the sensor data will be transported to the server and stored in Oracle. These are the current results of an ongoing project of the center. Further research results will be updated and presented in the near future.
POLE-LIKE OBJECTS RECOGNITION FROM MOBILE LASER SCANNING DATA USING SMOOTHING AND PRINCIPAL COMPONENT ANALYSIS
Authors: Yokoyama H. , Date H. , Kanai S. , Takeda H.
Published: September 2012

Abstract. With the spread of the Mobile Laser Scanning (MLS) system, the demands for the management of road and facilities using MLS point clouds have increased. Especially, pole-like objects such as streetlights, utility poles, street signs and etc. are in high demand as facilities to be managed. We propose a method for recognizing pole-like objects from MLS point clouds. Our method is based on Laplacian smoothing using the k-nearest neighbors graph, Principal Component Analysis for recognizing points on pole-like objects, and thresholding for the degree of pole-like objects. Our method can robustly recognize pole-like objects with various radii and tilt angles from MLS point clouds. For correctly segmented objects, accuracy of pole-like object recognition is on average 97.4%.