Calibrating geosynchronous and polar orbiting satellites: Sharing best practices
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Abstract
Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of the Earth at the same local time. Although similar in instrument design, there are enough differences in these two types of missions that often the calibration of the instruments can be substantially different. Thus, respective calibration teams develop independent methods and do not interact regularly or often. Yet, there are numerous areas of overlap and much to learn from one another. To address this issue, a panel of experts from both types of systems was convened to discover common areas of concern, areas where improvements can be made, and recommendations for the future. As a result of the panelist’s efforts, a set of eight recommendations were developed. Those that are related to improvements of current technologies include maintaining sun-synchronous orbits (not allowing orbital decay), standardization of spectral bandpasses, and expanded use of well-developed calibration techniques such as deep convective clouds, pseudo invariant calibration sites, and lunar methodologies. New techniques for expanded calibration capability include using geosynchronous instruments as transfer radiometers, continued development of ground-based prelaunch calibration technologies, expansion of RadCalNet, and development of space-based calibration radiometer systems.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Calibrating geosynchronous and polar orbiting satellites: Sharing best practices |
Series title | Remote Sensing |
DOI | 10.3390/rs12172786 |
Volume | 12 |
Issue | 17 |
Year Published | 2020 |
Language | English |
Publisher | MDPI |
Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
Description | 2786, 22 p. |
Google Analytic Metrics | Metrics page |