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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004
The fusion of the panchromatic orthoimage and the
multispectral orthoimage led to a pan-sharpened orthoimage of
I-m and four bands, which preserves the spatial and spectral
characteristics of both images. This conclusion is confirmed by
the criteria used for the evaluation of the quality of the pan-
sharpened image.
A supervised classification based on the fuzzy logic was
applied initially to the whole image but did not have good
results. Since the classification of urban areas is usually
difficult having complex structures of various materials
(asphalt, cement, glass), it was decided to classify separately
the urban and the tree-covered part. This resulted in satisfactory
classification for both image parts.
Finally, certain ways of visualizing the DTM and the pan-
sharpened orthoimage were presented for the observation of the
study area.
REFERENCES
Behdinian, B., 2002. Generating orthoimage from Ikonos data.
Publication in session “Very high resolution mapping” in 23
Asian Conference on Remote Sensing, Kathmandu, Nepal.
http://www .gisdevelopment.net/aars/acrs/2002/vhr/017.pdf
(accessed 2 Oct. 2003)
Dare, P., Pendlebury, N., Fraser, C., 2002. Digital orthomosaics
as a source of control for geometrically correcting high
resolution satellite imagery. Publication in session “Very high
resolution mapping” in 23™ Asian Conference on Remote
Sensing, Kathmandu, Nepal.
http://www .gisdevelopment.net/aars/acrs/2002/vhr/108.pdf
(accessed 2 Oct. 2003)
Di K., Ma, R., Li, R., 2003. Rational Functions and potential for
rigorous sensor model recovery. Photogrammetric Engineering
& Remote Sensing, Vol. 69, No. 1, pp. 33-41.
Dial, G., Grodecki, J., 2002. IKONOS accuracy without ground
control. Proceedings of ISPRS Comission I Mid-Term
Symposium, Denver, USA.
http://www.spaceimaging.com/whitepapers pdfs/2002/IKONO
S%20Accuracy%20without%20Ground%20Control-
ISPRS96202002.pdf (accessed 19 Oct. 2003)
Erdas, 1999. Erdas Field Guide, Erdas 5" ed., USA, pp. 226-
236, 357-364.
Graf, C.K., 1995. Realistic landscape rendering using remote
sensing images, digital terrain models and 3D objects. Remote
Sensing series, Zurich, Vol. 25, pp. 1-12.
Haala, N., Walter, 1999. Automatic classification of urban
environments for database revision using Lidar and Color
Aerial Imagery. In: The International Archives of the
Photogrammetry and Remote Sensing, Valladolid, Spain, Vol.
32, Part 7-4-3 W6.
Grocecki, J., Dial, G., 2003. Block Adjustment of High-
Resolution Satellite Images Described by Rational Polynomials.
Photogrammetric Engineering & Remote Sensing, Vol. 69, No.
l, pp. 59-68.
Kratky, V., 1989. Rigorous photogrammetric processing of
SPOT images at CCM Canada.
Photogrammetry and Remote Sensing, No. 44, pp. 53-71.
ISPRS Journal of
191
Kuo, C., Chou, T. Lee, R., 2001. Identification characteristic
using Ikonos high-resolution satellite image. Publication in
session “Very high resolution mapping” in 22" Asian
Conference on Remote Sensing, Singapore,...
http://www.crisp.nus.edu.sg/-acrs2001/pdf/171KUO.pdf
(accessed 10 Sep. 2003)
Li, J., 2000. Spatial quality evaluation of fusion of different
resolution images. In: The International Archives of
Photogrammetry and Remote Sensing, Amsterdam,
Netherlands, Vol. XXXIII, Part B7, pp. 752-759.
Pohl, C., Van, G.J.L., 1998. Multisensor Image Fusion in
Remote Sensing: Concepts, Methods and Applications.
International Journal Remote Sensing, Vol. 19, No. 5, pp. 823-
854.
Schickler, W., Thorpe, A., 1998. Operational procedure for
automatic true orthophoto generation. In: The International
Archives of the Photogrammetry and Remote Sensing, Stuttgart,
Germany, Vol. 32, Part 4, pp. 527-532.
Tao, V.C., Hu, Y., 2001. A comprehensive study of the
Rational Function Model for photogrammetric processing.
Photogrammetric Engineering & Remote Sensing, Vol. 67, No.
12, pp. 1347-1357.
Tsakiri-Strati, M., Papadopoulou, M., Georgoula, O., 2002.
Fusion of XS SPOT4 and PAN SPOT2 images and assessment
of the spectral quality of the products. Technika Chronika,
Scientific Journal of the
Technical Chamber of Greece, Section A, vol. 22, No. 3.
Wald, L., Ranchin, T., Mangolini, M., 1997. Fusion of satellite
images of different spatial resolutions: Assessing the quality of
resulting images. Photogrammetric Engineering & Remote
Sensing, Vol. 63, No. 6, pp. 691-699.
Yesou, H., Besnus, Y., Rolet, J., 1993. Extraction of Spectral
Information from Landsat TM Data and Merger with SPOT
Panchromatic Imagery- A Contribution to the Study of
Geological Structures. /SPRS Journal of Photogrammetry and
Remote Sensing, Vol. 48, No. 5, pp. 23-36.
Yu, Z., Gixian, Z., Guangliang, W., Zoingjian, L., 2002. Urban
land-use classification using integrated airborne laser scanning
data and high resolution multi-spectral satellite imagery.
Proceedings of ISPRS Comission I Mid-Term Symposium,
Denver, USA.
http://www. isprs.org/commission I /proceedings/paper/00100.pd
f (accessed 1 Oct. 2003)
Zhang, Y., 2001. Texture-Integrated Classification of Urban
Treed Areas in High-Resolution Color-Infrared Imagery.
Photogrammetric Engineering & Remote Sensing, Vol. 67, No.
12, pp. 1359-1365.
Zhang, J., Foody, G.M., 1998. A fuzzy classification of sub-
urban land cover from remotely sensed imagery. International
Journal Remote Sensing, Vol. 19, No. 14, pp. 2721-2738.
Zhou, J., Civco, D.L., Silander, J.A., 1998. A wavelet
transformation method to merge Landsat TM and Spot
panchromatic data. International Journal Remote Sensing, Vol.
19, No. 4, pp. 743-757.
