XXII ISPRS Congress 2012: Technical Commission VII

Bibliographic data

Multivolume work

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:: AN INVESTIGATION OF AUTOMATIC CHANGE DETECTION FOR TOPOGRAPHIC MAP UPDATING Patricia Duncan & Julian Smit

Document type:: Multivolume work

Structure type:: Chapter

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 AN INVESTIGATION OF AUTOMATIC CHANGE DETECTION FOR TOPOGRAPHIC MAP UPDATING Patricia Duncan! & Julian Smit? IThe Chief Directorate: National Geospatial Information, Department of Rural Development and Land Reform, Cape Town, South Africa pduncan@ruraldevelopment. gov.za 2Geomatics Division, School of Architecture, Planning & Geomatics, University of Cape Town, Cape Town, South Africa Julian. Smit@uct.ac za KEY WORDS: Mapping, Change Detection, Classification, Pixel, Object ABSTRACT Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa’s national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques. INTRODUCTION The Chief Directorate of National Geo-spatial Information (CD: NGI), South Africa’s national mapping agency, is responsible for the official, definitive, national topographic mapping, aerial imagery and control survey network of South Africa. One of the responsibilities of the CD: NGI is the capturing and revision of topographical data into the national integrated database of geo-spatial information. The process of detecting changes to the landscape and updating CD: NGI's topographic database is currently performed manually, which is time consuming and relies on the knowledge and interpretation of the operator. The focus of this research is on updating topographic data for urban built-up areas, as these areas can change rapidly. An automated method of detecting changes to these areas is needed so that the topographic database can be updated regularly. The proposed method of detecting change is through image classification. In this paper we will compare various methods of image classification for the purpose of updating topographic databases. The change detection part of the research will come at a later stage once the most appropriate method of image classification has been decided on. It is envisaged that changes will be detected by comparing the newly classified data with the existing topographic vector data. The imagery used in this study is 0.5m resolution aerial imagery. Available image bands are red, green, blue and near-infrared. Existing vector data representing topographical features is the basis for measuring and comparing changes that are detected. UPDATING TOPOGRAPHIC DATABASES THROUGH IMAGE CLASSIFICATION PIXEL-BASED CLASSIFICATION Supervised classification Using the maximum likelihood classification method, Walter & Fritsch (1998) found that forests are recognised as homogenous and are well detected, while agricultural areas may show inconsistencies due to planting structure, but they could also be well detected. The water class was the most easily detected. Larger streets are recognised without significant problems, but sometimes there is confusion between pixels from the street class and pixels that represent house roofs due to their similar spectral characteristics. Pixels are only recognised as settlement areas if they represent house roofs, while other pixels in

Access restriction

Copyright

fullscreen: Technical Commission VII (B7)

Multivolume work

Volume

Chapter

Chapter

Table of contents

Cite and reuse

Volume

Chapter

Image

Image fragment

Citation links

Citation recommendation