Book contents
- Frontmatter
- Contents
- List of contributors
- Foreword by Jón A. Benediktsson
- Acknowledgements
- PART I The Importance of Image Registration for Remote Sensing
- PART II Similarity Metrics for Image Registration
- PART III Feature Matching and Strategies for Image Registration
- PART IV Applications and Operational Systems
- 14 Multitemporal and multisensor image registration
- 15 Georegistration of meteorological images
- 16 Challenges, solutions, and applications of accurate multiangle image registration: Lessons learned from MISR
- 17 Automated AVHRR image navigation
- 18 Landsat image geocorrection and registration
- 19 Automatic and precise orthorectification of SPOT images
- 20 Geometry of the VEGETATION sensor
- 21 Accurate MODIS global geolocation through automated ground control image matching
- 22 SeaWiFS operational geolocation assessment system
- PART V Conclusion
- Index
- Plate section
- Plate section
- References
21 - Accurate MODIS global geolocation through automated ground control image matching
from PART IV - Applications and Operational Systems
Published online by Cambridge University Press: 03 May 2011
- Frontmatter
- Contents
- List of contributors
- Foreword by Jón A. Benediktsson
- Acknowledgements
- PART I The Importance of Image Registration for Remote Sensing
- PART II Similarity Metrics for Image Registration
- PART III Feature Matching and Strategies for Image Registration
- PART IV Applications and Operational Systems
- 14 Multitemporal and multisensor image registration
- 15 Georegistration of meteorological images
- 16 Challenges, solutions, and applications of accurate multiangle image registration: Lessons learned from MISR
- 17 Automated AVHRR image navigation
- 18 Landsat image geocorrection and registration
- 19 Automatic and precise orthorectification of SPOT images
- 20 Geometry of the VEGETATION sensor
- 21 Accurate MODIS global geolocation through automated ground control image matching
- 22 SeaWiFS operational geolocation assessment system
- PART V Conclusion
- Index
- Plate section
- Plate section
- References
Summary
Abstract
A global network of ground control points (GCPs) is being used to maintain the geolocation accuracy of terrestrial remote sensing data from the two Moderate Resolution Imaging Spectroradiometers (MODIS) on NASA's Earth Observing System (EOS) Terra and Aqua spacecrafts. Biases and trends in the sensor orientation determined from automated control point matching are removed by updating models of the spacecraft and instrument orientation in the MODIS geolocation software. This technique has been used to keep the MODIS geolocation accuracy to approximately 50 m (1σ) at nadir. This chapter overviews an approach to automated matching of global GCPs and summarizes eight years of geolocation analysis. This approach allows an operational characterization of the MODIS geolocation errors and enables individual MODIS observations to be geolocated to the subpixel accuracies required for terrestrial global change applications.
Introduction
Two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors (Salomonson et al., 1989) have been launched as part of NASA's Earth Observing System (EOS). The first was launched in December 1999 on the Terra platform and the second in May 2002 on the Aqua platform. The observations from these sensors need to be geolocated to subpixel accuracies for Earth science research and applications (Townshend et al., 1992; Roy, 2000). This chapter discusses the approach to obtaining and maintaining this accuracy through the use of finer-resolution Landsat Thematic Mapper (TM) and Enhanced TM+ (ETM+) GCPs.
- Type
- Chapter
- Information
- Image Registration for Remote Sensing , pp. 437 - 455Publisher: Cambridge University PressPrint publication year: 2011
References
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