Abstract
Remotely sensed data, ranging from satellite imagery, airborne laser scanner data, and aerial photograph, play more and more important roles in environmental monitoring, emergency response, and disaster assessment. Among the products of the broad range of applications, raster base maps, which are generated from various sources of remote sensing data, are becoming very critical for effective and efficient disaster management. The raster base maps can provide detailed topographic, land-use and land-cover information on the earth’s surface in a short period or near real time. With the growing requirements of such raster base maps, the techniques which can be used for automatically correcting raw data and generating digital maps are urgently required.
This paper presents a system that consists of a set of processing steps to georeference and merge many satellite or aerial images together in order to quickly map a large geographic region. The periodic processing results can be compared and analyzed for monitoring a large emergency area. The technique makes full use of georeference and sensor model information, such as ephemeris data, geometric model, and/or GPS/INS navigation and positioning information, to automatically register and orthorectify the raw image data. Through mosaicking process, a seamless mosaicking image or image tiles is produced, which will be in a selected map projection system with consistent spatial resolution. Additionally, semi-automatic and manual editing can be performed to produce a standard map to satisfy the requirements of mapping agencies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bryant E (2005) Natural Hazards, Cambridge University Press, New York, 551 pp
Habib AF, Lee Y, and Morgan M (2003) Automatic Matching and Three-Dimensional Reconstruction of Free-Form Linear Features from Stereo Images, Photogrammetric Engineering & Remote Sensing, 69(2): pp 189–197.
Jensen JR (2007) Remote Sensing of the Environment, Pearson Prentice Hall, Upper Saddle River, NJ, 592 pp
Kreifelts T (1977) Skelettierung und Linienverfolgung in raster-digitalisierten Linienstrukturen, in Nagel, H.-H. (Ed.), Digitale Bildverarbeitung, pp 223–231
Motrena, P. and Rebordao, J.M., 1998. Invariant models for ground control points in high resolution images, International Journal of Remote Sensing, 19(7): 1359–1375.
Sanguantrakool T, Pricharchon E, Phoompanich S (2005) Remote sensing technology for Tsunami Disasters Along the Andaman Sea, Thailand, 3 rd International Workshop on Remote Sensing for Post-Disaster Response, September 12–13, 2005, Chiba, Japan, 16 pp
Toutin Th (1995) Multisource data fusion with an integrated and unified geometric modelling. EARSeL Journal Advances in Remote Sensing, 4(2): 118–129.
Watson W (2006) Automated Georeferencing for Rapid Data Production, Photogrammetric Engineering and Remote Sensing, 72(4): pp 337–338.
Xin, Y. and Parent, D., 2004. Automated Procedure of a Prototype Mapping System, Proceeding of the 25 st Asian Conference on Remote Sensing, pp 454–45
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Xin, Y., Li, J., Cheng, Q. (2007). Automatic Generation of Remote Sensing Image Mosaics for Mapping Large Natural Hazards Areas. In: Li, J., Zlatanova, S., Fabbri, A.G. (eds) Geomatics Solutions for Disaster Management. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72108-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-72108-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72106-2
Online ISBN: 978-3-540-72108-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)