Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery / Springer Theses (PDF)
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This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.
Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.
The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
- Autor: Nasrin Nasrollahi
- 2014, 2015, 68 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319120816
- ISBN-13: 9783319120812
- Erscheinungsdatum: 07.11.2014
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- Dateiformat: PDF
- Grösse: 5.76 MB
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