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A Shared Computing Platform for Remote Sensing Community: The Framework Setup and user Interface
Retrieving key climate variables such as soil moisture and snow water equivalent from remote sensing data requires representative physical models. Up to date, there is no integrated remote sensing computing platform dedicated to modeling brightness temperature, backscatters, and relevant parameters...
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Main Authors: | , , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Retrieving key climate variables such as soil moisture and snow water equivalent from remote sensing data requires representative physical models. Up to date, there is no integrated remote sensing computing platform dedicated to modeling brightness temperature, backscatters, and relevant parameters based on microwave electromagnetic scattering mechanisms for complex soil, vegetation, and snow scenarios. In this paper, the Remote Sensing Hub (RSHub), a shared cloud computing platform is introduced to close the gap. The platform integrates multiple physical scattering models into a unified framework that supports soil/vegetation/snow scenarios, offering options for radiative transfer and full wave approaches. We demonstrate the use of the RSHub to predict brightness temperatures corresponding to vegetated land surface scenarios. |
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ISSN: | 2153-7003 |
DOI: | 10.1109/IGARSS53475.2024.10642599 |