Street Mapping using Fuzzy Approach with Remote Sensing Images

International Journal of Geoinformatics and Geological Science

© 2015 by SSRG - IJGGS Journal

Volume 2 Issue 1

Year of Publication : 2015

Authors : Hadwin, Kenward

10.14445/23939206/IJGGS-V2I1N2P101

How to Cite?

Hadwin, Kenward, "Street Mapping using Fuzzy Approach with Remote Sensing Images," SSRG International Journal of Geoinformatics and Geological Science, vol. 2,  no. 1, pp. 14-17, 2015. Crossref, https://doi.org/10.14445/23939206/IJGGS-V2I1N2P101

Abstract:

The semi-automated and computerized extraction of street features like roads, pathways, canals etc., from high resolution settlement imagery is under research from several years. It is aauspicious task of research in continuing studies for value addition and constant apprising in geographic applications. This research is under advancement by the launch of several remote identifying satellites in the areas of high resolution satellite imagery and airborne satellite imagery. Though, with the depth of the resolution, range in high resolution sensors and instantaneousobtainability of the high resolution image datasets, newer products development is possible. But, it enables huge image processing on the remote sensing

Keywords:

Street Mapping,Remote Sensing

References:

[1] Agouris, P., A. Stefanidis, and S. Gyftakis, ―Differential snakes for change detection in road segments,‖ Photogrammetric Engineering & Remote Sensing, 67(12): 2001a, pp. 1391–1399.
[2] Agouris, P., P. Doucette, and A. Stefanidis, ―Spatiospectral cluster analysis of elongated regions in aerial imagery,‖ in proc of the IEEE International Conference on Image Processing, 07–10 Oct, Thessaloniki, Greece, 2001b, pp. 789–792.
[3] Baumgartner, A., C. Steger, H. Mayer, W. Eckstein, and H. Ebner. ―Automatic road extraction based on multiscale, grouping, and context,‖ Photogrammetric Engineering & Remote Sensing, 1999, 65(7): 777–785.
[4] Definiens 2003 eCognition homepage, URL: http://www.definiensimaging.com (last date accessed: 11 December 2012).
[5] Digital Globe, Digital Globe homepage, URL: http://www.digitalglobe.com 2003 (last date accessed: 11 December 2012).
[6] Doucette, P., P. Agouris, M. Musavi, and A. Stefanidis,―Automated extraction of linear features from aerial imagery using Kohonen learning and GIS data, Lecturer Notes in Computer Science: Integrated Spatial Databases Workshop—Digital Images and GIS,‖ 1999, Vol. 1737, pp. 20–33.
[7] Fischler, M.A., J.M. Tenenbaum, and H.C. Wolf, ―Detection of roads and linear structures in low resolution aerial imagery
using a multisource knowledge integration technique,‖ Computer Graphics and Image Processing, 1981, 15, pp.201–233. 
[8] Fitton, N.C., and S.J.D. Cox, ―Optimizing the application of the Hough transform for automatic feature extraction from geo scientific images,‖ Computers and Geosciences, 1998, 24(10), pp. 933–951.
[9] Gardner, M.E., D.A. Roberts, C. Funk, and V. Noronha, ―Road extraction from AVIRIS using spectral mixture and Qtree filter techniques,‖ in proc. of the AVIRIS Airborne Geo science Workshop, 27 February–March, Pasadena, California, 2001 URL: http:// avris.jpl.nasa.gov/docs/workshops/aviris.proceedings.html
(last date accessed: 16 July 2013).
[10] Gibson, L., ―Finding road networks in IKONOS satellite imagery,‖ in proc. of the ASPRS Annual Conference,05–09 May, Anchorage, Alaska (American Society for Photogrammetry and Remote Sensing), 2003, unpaginated CDROM.