A New and Automated Method for Improving Georeferencing in Nighttime Thermal ECOSTRESS Imagery
Author:
Affiliation:
1. Department of Applied Earth Sciences, Faculty ITC, University of Twente, Hallenweg 8, 7522 NH Enschede, The Netherlands
2. Department of Computer Science, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
Abstract
Funder
Dutch Research Council
NASA-ECOSTRESS Science and Application Team membership
Publisher
MDPI AG
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Link
https://www.mdpi.com/1424-8220/23/11/5079/pdf
Reference33 articles.
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2. Smyth, M., and Logan, T.L. (2023, February 07). ECOSTRESS Science Meeting L1B Geolocation Review, Available online: https://ecostress.jpl.nasa.gov/downloads/science_team_meetings/2020/fall_pres/day1/05_Ecostress_L1B_Geolocation_01DEC2020.pdf.
3. Automatic and precise orthorectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements;Leprince;IEEE Trans. Geosci. Remote Sens.,2007
4. Logan, T., and Smyth, M. (2022, January 15–17). L1 Calibration and Geolocation Review. Proceedings of the ECOSTRESS Science Meeting November, Virtual.
5. Long, T., Jiao, W., He, G., and Zhang, Z. (2016). A fast and reliable matching method for automated georeferencing of remotely-sensed imagery. Remote Sens., 8.
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