Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

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Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

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

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; 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:: INTEGRATED DEM AND PAN-SHARPENED SPOT-4 IMAGE IN URBAN STUDIES G. Doxani, A. Stamou

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 Comparison between multispectral — synthetic image Band 1 Band 2 Band 3 Band4 Bias (ideal value: 0) 0.178 0.099 0.079 0.016 Correlation coefficient 0.798 0.804 0.814 0.747 (ideal value: 1) Standard deviation of the difference image 0.296 0.007 0.03 0.039 (ideal value: 0) Comparison between NDVI multispectral — NDVI synthetic image Bias (ideal value: 0) 1.143 Correlation coefficient 3 0.931 (ideal value: 1) Standard deviation of the difference image (ideal value: 2.611 0) Table 5. The results of the statistical tests The spatial evaluation of the synthetic image is done in order to detect if the synthetic image maintains the spatial characteristics of the high-resolution image (panchromatic image). A high pass filter 7x7 is applied over the synthetic and orthorectified panchromatic image, with the view to exaggerate the linear characteristics. The correlation between the images is done, after the matching of the ‘high-pass’ synthetic to the ‘high-pass’ panchromatic image histograms. Correlation coefficient between ‘high-pass’ panchromatic — ‘high-pass’ synthetic image Synthetic BANDS I 2 3 4 0.892 0.863 0.85 0.834 | Panchromatic BAND Table 6. The results of the correlation between ‘high-pass’ panchromatic — ‘high-pass’ synthetic image 5. CLASSIFICATION The relevant data derived from the satellite sensors are so many that the classical interpretation methods for the extraction of information are difficult and time-consuming. Classification is one of the most reliable methods of recording pixels in classes of land use, with multispectral classification. Classification is the process of defining the image pixels into various classes, representing the different types of land cover and use. Each class or category in one image represents a group of pixels that have the same spectral values. There are two kinds of classification: 1) the unsupervised classification, where the classes of pixels are determined according to their band values without the use of the external data. Once the pixel classes have been formed the land cover type of each class is identified with the help of pixels within the class whose land type has been determined by fieldwork. 2) the supervised classification, where the pixels with known land cover type, determined by fieldwork form the nuclei for the classification of the remaining pixels in one of the already identified classes, on the basis of their band values. (A.Dermanis: Remote sensing) 142 5.1 Preparation of the image In this project the supervised classification is applied on the synthetic image, which was produced with the process of fusion. It should be noted that the synthetic image was divided into two parts, the one of the urban and the other of the hilly area. Each part is classified separately. This is done, because otherwise there were problems in the exact definition of the classes, and so the correlation between pixels and classes was not right and accurate. 5.2 The steps of the classification The first and most important step in the process of classification is the definition of all the classes, where the pixels are going to be inscribed. Consequently, the choice of the samples from specific parts of the image must be done carefully, for the right correlation between the pixels and the classes. For the first part of the synthetic image, the urban area, the following classes are chosen: ] Trees 2. Grass 3. Concrete 4. Buildings 5. Ground 6. Ring road For the second part of the synthetic image, the hilly area, the following classes are chosen: Forest Burnt forest Road m Pom By collecting the proper samples of cach class, the classification is realised according to the fuzzy logic, which contributes to better results. Classes E Forest Burnt forest Ring road Ground Concrete Sea B Grass EH Trees [] Buildings Figure 7. The classified image 5.3 Evaluation of the classification's accuracy Comparing some specific pixels of the classified image and their corresponding reference pixels, which belong to a known class, succeeds the evaluation of the classification. In TAA T= 1 ~~ 1 FT ST SSAITSSTESTÄASTFATZST AT

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