XXII ISPRS Congress 2012: Technical Commission VII

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Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/5: METHODS FOR CHANGE DETECTION AND PROCESS MODELLING]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: OBJECT-BASED CHANGE DETECTION USING HIGH-RESOLUTION REMOTELY SENSED DATA AND GIS N. Sofina, M. Ehlers

Document type:: Multivolume work

Structure type:: Chapter

inaugh sitions ired in about rred to | thus, sition. in the Can be It OF a e with le that ; large es the nsities -made ibles a ta for use of Itering pach — curacy ext of ] even further kernel Cessor th, A., looded Radar eview. . ich for 'hange "^ the nation oralen "tation ca.uni- Roth, oncept sk. In: ensing 1971, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia OBJECT-BASED CHANGE DETECTION USING HIGH-RESOLUTION REMOTELY SENSED DATA AND GIS N. Sofina *, M. Ehlers ° ‘University of Osnabrueck, Institute for Geoinformatics and Remote Sensing, 49076 Osnabrueck, Barbarastrasse 22b, Germany - nsofina@igf.uni-osnabrueck.de "University of Osnabrueck, Institute for Geoinformatics and Remote Sensing, 49076 Osnabrueck, Barbarastrasse 22b, Germany - manfred.ehlers@uos.de Commission VII, WG VII/5 KEY WORDS: Change Detection, Geographic Information Systems (GIS), Detected Part of Contour, Generation of Features, Data Mining, GIS GRASS, Python ABSTRACT: High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and — for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. À promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change. 1. INTRODUCTION Since the 20-th century the integration of cartography, Geoinformatics, and remote sensing technologies has been developed due to rapid technological advances. This evolution implied a number of derivative scientific directions and consolidation of conventional and digital cartographic techniques. The technological progress in remote sensing was one of the most important origins of this integration. Its influence on the cartography is many-folded. The main aspect is that remotely sensed images are considered as maps which lead to the development of new photogrammetry and image processing methods. A second origin of the integration tendencies was the development of geoinformation technologies. In recent years the application of GIS has offered the greatest potential for processing large volumes of multi-source data (Ehlers et al., 1989). For change detection of the Earth’s surface the development of methods based on integrated analysis of vector and image data is a point of general interest. The majority of change detection methods address land-use change dynamics (see, for example, Centeno & Jorge, 2000; Lo & Shipman, 1990; Li, 2009; Mattikalli, 1995; Weng, 2002) and only a few deal with damage assessment. Samadzadegan & Rastiveisi (2008) used information from pre-event vector maps and post-event satellite images to compare different textural features for extracted building vector. Chesnel et al. (2007) used a pair of very high resolution images of a crisis region together with GIS data for investigation based on different acquisition angles of the images. This paper presents a GIS-based approach for the detection of destroyed buildings which were affected by a catastrophic event like an earthquake, a landslide or a military action. The methodology is based on the integrated analysis of vector data containing information about the original urban layout and remotely sensed images obtained after a catastrophic event. The proposed method was applied to damage mapping after the earthquake in Qinghai, China (2010). GIS information was obtained by digitizing from pre-earthquake images. The performed experiments indicate that a GIS-based analysis for change detection can essentially improve the potential of remotely sensed data interpretation and can be considered as a powerful tool for the detection of destroyed building. The proposed methodology was developed solely within the Open Source software environment (GRASS GIS, Python, Orange). The use of Open Source software provides an innovative, flexible and cost-effective solution for change detection analyses. 2. STUDY AREA To assess the effectiveness of the proposed approach, the experiments were conducted using a high-resolution panchromatic QuickBird image acquired after the earthquake that struck Yushu, Qinghai, China on April 14, 2010 with a magnitude of 6.9Mw. GIS information was obtained by digitizing from pre-earthquake images.

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