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/3: INFORMATION EXTRACTION FROM HYPERSPECTRAL DATA]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: CLASSIFICATION OF ROOF MATERIALS USING HYPERSPECTRAL DATA C. Chisense

Document type:: Multivolume work

Structure type:: Chapter

/ pixels naterial g to the already is to be le from s those iles are ay tiles elected itumen, ten are naining ses and centre to map ne, the able in ed by features raction. lysis of lowing identify assified )DATA ut map, A class red that lass for CESS. a set of gorithm :d. This | space ing the iminant analysis feature extraction (determines a feature subspace that is optimal for discriminating between defined classes). The output of the extraction is a linear combination of the 125 original bands to form new bands (features) that automatically occur in descending order of their value for producing an effective discrimination. Twenty two (22) features are obtained from the feature extraction process. However, only the 11 features obtained in the final feature extraction transformation matrix (DAFE) are used to form a new data set since these provide most of the available separability and this is confirmed by the magnitude of the corresponding eigenvalues (high values). The new data is classified using the ECHO classifier. The output classification map is overlaid with an orthophoto covering the same area as shown in Figure 2. Bitumen Roof material 2 Roof material 3 Zinc plated sheet Kaufland roof material Roof material 5 Roof material 1 Red roof chipping Roof material 4 Vegetation Background Roof material 6 Figure 2: Overlay of classification map and orthoimage. The classification map fits well with the orthophoto and this gives an indication of the accuracy of the classification in terms of geometry. In order to identify areas in the classification map which require improvement, the corresponding classification probability map is inspected (see Figure 3). The pixels represented by yellow to red colours in the probability map indicate a high probability of being correct. These pixels are very close to the training pixels for the classified pixels. Dark blue colours represent a low probability of being correct. The pixels represented by these colours are very far from the training pixels for all the classes and are candidates for definition of additional training regions. Figure 3: Classification probability map. Defining additional training regions for areas with a low probability helps to improve the result. Most of the roofs in the probability map with a low likelihood of being correct consist of heterogeneous surface materials. For instance, the material of the roof in a white circle is not homogeneous. Therefore, additional training regions are required for areas where a surface material varies in terms of spectral properties. Defining training regions for areas requiring improvement is sufficient for achieving a 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 classification result that represents ground features accurately. However, the required number of additional training regions depends on the scene, the material classes of interest and the accuracy requirements. The discriminant analysis feature extraction and the ECHO classifier are applied to the whole research area. The processing and analysis is done for each strip. The result obtained for each strip is shown in Figure 4. (a) Stripl (b) Strip 2 (c) Strip 3 Figure 4: Classification results of the strips covering the research area. The output classification maps (Figure 4) fit well with orthophotos covering the research area in terms of geometry. Inspection of the corresponding classification probability maps shown in Figure 5 indicates that most of the classified building

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