XXII ISPRS Congress 2012: Technical Commission VII

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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/4: METHODS FOR LAND COVER CLASSIFICATION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: NEW COMBINED PIXEL/OBJECT-BASED TECHNIQUE FOR EFFICIENT URBAN CLASSSIFICATION USING WORLDVIEW-2 DATA Ahmed Elsharkawy, Mohamed Elhabiby & Naser El-Sheimy

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 NEW COMBINED PIXEL/OBJECT-BASED TECHNIQUE FOR EFFICIENT URBAN CLASSSIFICATION USING WORLDVIEW-2 DATA Ahmed Elsharkawy ^", Mohamed Elhabiby *° & Naser El-Sheimy ^? "Dept. of Geomatics Engineering, University of Calgary, Calgary, Alberta, T2N 1N4 Phone: 403-210-7897, Fax: 403-284-1980, "Email: askelsha(@Ducalgary.ca ‘Public Works Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt Email: mmelhabi@ucalgary.ca 4 Email: elsheimy@ucalgary.ca Commission VII/A KEY WORDS: High resolution satellite imagery, Pixel/ Object-based, Curvelet transform, Edge detection, Band ratio, Building detection. ABSTRACT The new advances of having eight bands satellite mission similar to WorldView-2, WV-2, give the chance to address and solve some of the traditional problems related to the low spatial and/or spectral resolution; such as the lack of details for certain features or the inability of the conventional classifiers to detect some land-cover types because of missing efficient spectrum information and analysis techniques. High-resolution imagery is particularly well suited to urban applications. High spectral and spatial resolution of WorldView-2 data introduces challenges in detailed mapping of urban features. Classification of Water, Shadows, Red roofs and concrete buildings spectrally exhibit significant confusion either from the high similarity in the spectral response (e.g. water and Shadows) or the similarity in material type (e.g. red roofs and concrete buildings). This research study assesses the enhancement of the classification accuracy and efficiency for a data set of WorldView-2 satellite imagery using the full 8-bands through integrating the output of classification process using three band ratios with another step involves an object-based technique for extracting shadows, water, vegetation, building, Bare soil and asphalt roads. Second generation curvelet transform will be used in the second step, specifically to detect buildings’ boundaries, which will aid the new algorithm of band ratios classification through efficient separation of the buildings. The combined technique is tested, and the preliminary results show a great potential of the new bands in the WV-2 imagery in the separation between confusing classes such as water and shadows, and the testing is extended to the separation between bare soils and asphalt roads. The Integrated band ratio- curvelet transform edge detection techniques increased the percentage of building detection by more than 30%. 1. INTRODUCTION The processes of per-pixel supervised classification methods were always the primary tool to extract land cover classes from digital remotely sensed data (Bhaskaran et al, 2010). The ultimate goal of any image classification procedure is to automatically categorize all pixels in an image into land cover classes (Lillesand and kiefer, 2001). For the purpose of urban planning, supervised classification has been used extensively. Unfortunately, this procedure always results in mixed pixel’s problem (Bhaskaran et al, 2010). This problem leads many researchers to incorporate segmentation, texture, context, colour, and many other parameters to glide the mixed or wrongly classified pixels into their proper classes. Segmentation can be done either by detecting similarities or by detecting singularities (edge detection) (Gonzalez and Woods, 2002). Contrasting spectral methods, object-oriented methods are based on segmenting the image into homogeneous parcels of pixels then these parcels are classified using spectral, spatial, textural, relational and contextual methods (Bhaskaran et al., 2010). The primary objective of this study was to classify urban features from a WorldView-2 imagery by using both per-pixel classification (three new band ratios), and object-oriented classification method (edge detection using curvelet transforms). The first approach was to use the three new band ratios to classify the image and check accuracy of all classes. The following approach was to improve the accuracy of the lowest two classes’ accuracy. In 2009 Digital Globe launched the WorldView-2 satellite. It is the first commercial high-resolution satellite to provide eight spectral sensors in the visible to the near-infrared range. Each sensor closely focuses on a particular range of the electromagnetic spectrum which is sensitive to a specific feature on the ground and was designed to improve the segmentation and classification of land and marine. Figure 1 is a concise comparison between QuickBird, IKONOS, WorldView-1 and WorldView-2 of their spectral and panchromatic bands. In addition to its large-scale collection capacity, WorldView-2 has a high spatial and spectral resolution. According to (Globe, 2009) this satellite can capture a 46 cm panchromatic image with 1.84 m spectral resolution with 8-band multispectral imagery. The high spatial resolution facilitates the differentiation of fine details like small and medium-size buildings, shallow reefs and individual trees while the high spectral resolution provides detailed information about diverse

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