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A citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) / Ilyas Yalcin in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 15 p. Titre : A citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) Type de document : Article/Communication Auteurs : Ilyas Yalcin, Auteur ; Sultan Aksakal Kocaman, Auteur ; Candan Gokceoglu, Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] carte sismologique [Termes IGN] données localisées des bénévoles [Termes IGN] gestion des risques [Termes IGN] Istanbul (Turquie) [Termes IGN] krigeage [Termes IGN] risque naturel [Termes IGN] science citoyenne Résumé : (auteur) Nowadays several scientific disciplines utilize Citizen Science (CitSci) as a research approach. Natural hazard research and disaster management also benefit from CitSci since people can provide geodata and the relevant attributes using their mobile devices easily and rapidly during or after an event. An earthquake, depending on its intensity, is among the highly destructive natural hazards. Coordination efforts after a severe earthquake event are vital to minimize its harmful effects and timely in-situ data are crucial for this purpose. The aim of this study is to perform a CitSci pilot study to demonstrate the usability of data obtained by volunteers (citizens) for creating earthquake iso-intensity maps in a short time. The data were collected after a 5.8 Mw Istanbul earthquake which occurred on 26 September 2019. Through the mobile app “I felt the quake”, citizen observations regarding the earthquake intensity were collected from various locations. The intensity values in the app represent a revised form of the Mercalli intensity scale. The iso-intensity map was generated using a spatial kriging algorithm and compared with the one produced by The Disaster and Emergency Management Presidency (AFAD), Turkey, empirically. The results show that collecting the intensity information via trained users is a plausible method for producing such maps. Numéro de notice : A2020-264 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040266 Date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.3390/ijgi9040266 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95027 [article]

Sensor modelling and validation for linear array aerial and satellite imagery / Sultan Aksakal Kocaman (2009)  

Public Titre : Sensor modelling and validation for linear array aerial and satellite imagery Type de document : Thèse/HDR Auteurs : Sultan Aksakal Kocaman, Auteur ; Armin W. Gruen, Directeur de thèse ; Christian Heipke, Directeur de thèse Editeur : Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH Année de publication : 2009 Collection : IGP Mitteilungen, ISSN 0252-9335 num. 106 Importance : 166 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-906467-88-7 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] ADS40 [Termes IGN] capteur aérien [Termes IGN] capteur en peigne [Termes IGN] capteur linéaire [Termes IGN] capteur optique [Termes IGN] capteur spatial [Termes IGN] compensation par faisceaux [Termes IGN] détecteur à transfert de charge [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] image ALOS-PRISM [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modélisation géométrique de prise de vue [Termes IGN] orientation du capteur [Termes IGN] Panchromatic Remote Sensing Instrument for Stereo Mapping [Termes IGN] pouvoir de résolution géométrique Index. décimale : 35.13 Prises de vues par capteurs spatiaux Résumé : (Auteur) The Linear Array CCD technology is widely used in the new generation aerial photogrammetric sensors and also in the high-resolution satellite optical sensors. In comparison to the Matrix (frame/area) Array sensors, the Linear Array CCD sensors have smaller number of detectors to cover the same swath width. In addition, the flexibility is higher in the physical sensor design. The conventional film cameras used in aerial photogrammetry are manufactured in frame format. The first remote sensing sensors for Earth observation employed film cameras as well. The recent sensor technologies of the optical remote sensing satellites are replaced with the Linear Array CCDs. In case of the aerial photogrammetric sensors, medium and small format aerial cameras are produced only in the frame format. The development in large format cameras is twofold. The Linear Array CCD and Matrix Array CCD sensors have been present in the industry since the year 2000. Due to the geometric differences between the Linear Array cameras and the frame cameras, the conventional photogrammetric procedures for the geometric processing of the Linear Array CCD images should be redefined or newly developed. The trajectory modeling is one of the main concepts, which entered into the field of photogrammetry with the aerial and satellite pushbroom sensors. The modified collinearity equations are extended with mathematical functions to model the image trajectory in the bundle adjustment. This study encompasses the triangulation of Linear Array CCD images with the use of different trajectory models. The self-calibration models are partially adapted from the frame sensors in accordance with the physical structures of the Linear Array CCD sensors. In general, the triangulation and self-calibration of the aerial and the satellite Linear Array CCD images show similarities in terms of trajectory modeling and the physical definitions of the additional parameters. The main difference is in the number unknown parameters defined in the bundle adjustment, which is calculated as a function of the number of lenses, the trajectory model configuration, and the number of Linear Array CCDs used in the sensor. Therefore, similar sensor modeling and calibration approaches are applied in this study, with necessary adjustments for each system. In order to obtain high accuracy point positioning, high quality image trajectory measurement is crucial. The given trajectory can be modeled in the adjustment by using constant and linear correction parameters, as well as higher order polynomials. This study investigates the three different trajectory models with three different mathematical approaches. Two of the models are investigated at different levels of sophistication by altering the model parameters. Two different aerial Linear Array CCD sensors, the STARIMAGER of former Starlabo Corporation, Japan, and the ADS40 sensor of the Leica Geosystems, Heerbrugg, are used for the practical investigations. The PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) onboard of Japanese ALOS satellite launched by JAXA (Japan Aerospace Exploration Agency) in 2006 is the satellite Linear Array CCD sensor used for the application parts of this study. The two aerial Linear Array CCD sensors work with the TLS (Three-Line-Scanner) principle. Three or more Linear Array CCDs are located in the focal plane of a single lens with different viewing angles providing stereo capability. The PRISM sensor differs in the optical design with three camera heads, each associated with a different viewing angle. Due to the design differences between the sensors, two sets of additional 'parameters for self-calibration are applied in this study. The aerial TLS sensors share the same set of additional parameters due to similar interior geometries of the sensors. The self-calibration of the PRISM sensor uses a different set due to multiple lenses and also multiple CCD chips used to form each image line. The sensor orientation and calibration methods presented in this study are validated using a number of application datasets. The image datasets of the three sensors are acquired over specially established testfields. Triangulation results prove the importance of high quality trajectory measurements for accurate sensor orientation. When the given image trajectory has a low quality, a sophisticated trajectory model should be used together with a high number of ground control points. This study also shows that, despite their weaker sensor geometry, the Linear Array CCD sensors have reached the accuracy potential of the conventional frame imagery for point determination. In addition, similar to the conventional film sensors, self-calibration has proven as a powerful tool for modeling the systematic errors of the Linear Array CCD imagery, albeit the method should be applied with a great care. Note de contenu : 1 Introduction 1.1 Research Objectives 1.2 Review of Digital Optical Sensors 1.2.1 Point-based Sensors 1.2.2 Linear Array CCD Sensors 1.2.3 Frame Array CCD Sensors 1.3 Review of Sensor Calibration Approaches for Linear Array CCD Sensors 1.4 Review of Sensor Orientation Methods for Linear Array CCD Sensors 1.4.1 Direct vs. Indirect Georeferencing 1.4.2 Rigorous vs. Generic Models for Georeferencing 1.5 Quality Analysis and Validation for the Geometric Processing Methods 1.6 Outline 2 Characterizations of the Linear Array CCD Sensor Geometries 2.1 Optical System Specification 2.2 Line Geometry 2.3 Resolution Specification 2.3.1 Spatial Resolution 2.3.2 Radiometric Resolution 2.3.3 Spectral Resolution 2.3.4 Temporal Resolutions of Satellite Sensors 2.4 Operation Principles 2.4.1 Sensor and Platform Synchronization 2.4.2 Stereo Acquisition 2.4.3 Platform Stabilization 3 Calibration Parameters for the Linear Array CCD Sensors . 3.1 Optical System Related Parameters 3.1.1 Principal Point Displacement 3.1.2 Camera Constant 3.1.3 Lens Distortions 3.2 CCD Line Related Parameters 3.2.1 Scale effect 3.2.2 Rotation 3.2.3 Displacement from the Principal Point 3.2.4 Bending 4 Methodology for Sensor Orientation and Calibration 4.1 Preparation for Rigorous Sensor Orientation 4.1.1 Image Trajectory Extraction 4.1.2 Interior Orientation Extraction 4.1.3 Coordinate System Transformations 4.2 Rigorous Sensor Orientation 4.2.1 Modified Bundle Adjustment with Trajectory Modeling 4.2.2 Self-calibration Method 4.2.3 Weighting Scheme of the Bundle Adjustment 4.2.4 Accuracy Assessment of the Bundle Adjustment 4.2.5 Processing time 5 Applications 5.1 Starlmager Sensor 5.1.1 Applications over the Yoriichio Testfield, Japan 5.1.2 Findings and Discussion 5.2 ADS40 Sensor 5.2.1 Applications to Testfields 5.2.2 Findings and Discussion 5.3 The ALOS/PRISM Sensor 5.3.1 Introduction 5.3.2 Applications to Testfields 5.3.3 Findings and Discussion 6 Conclusions and Outlook 6.1 Summary 6.2 Conclusions 6.3 Recommendations for Future Work Numéro de notice : 15509 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère En ligne : http://dx.doi.org/10.3929/ethz-a-005780510 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62742

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15509-01	35.13	Livre	Centre de documentation	En réserve M-103	Disponible