Efficient Examples of Earth Observation Satellite Data Processing Using the Jaxa Supercomputer System and the Future for the Next Supercomputer System

2021 ◽  
Author(s):  
Masaki Yamada ◽  
Akira Fujioka ◽  
Naoyuki Fujita ◽  
Makiko Hashimoto ◽  
Yoko Ueda ◽  
...  
Keyword(s):  
Data Processing ◽  
Satellite Data ◽  
Earth Observation ◽  
The Future ◽  
Earth Observation Satellite

​​Distributed Earth-Observation satellite data processing with Pytroll/Satpy

2020 ◽  
Author(s):  
Salomon Eliasson ◽  
Martin Raspaud ◽  
Adam Dybbroe
Keyword(s):  
Data Processing ◽  
Satellite Data ◽  
Computational Efficiency ◽  
Distributed Processing ◽  
Earth Observation ◽  
Data Volume ◽  
Cluster Environment ◽  
Performance Problem ◽  
Earth Observation Satellite ◽  
Sentinel 2

<div dir="auto"> </div><div dir="auto">As earth-observing <span>(EO)</span> satellite data volume is growing, servers struggle to keep up with the computational load needed to process even single segments of satellite data with reasonable performance. Pytroll is a suite of free and open-source python tools from which the Satpy package is made to easily and efficiently read, process, write EO satellite data. To obtain computational efficiency, Pytroll approaches the performance problem from multiple angles through optimized data processing, built-in support for out-of-memory computations <span>(using</span> the underlying Dask python library), and allowing distributed processing <span>(using</span> the Dask Distributed tools). In this work, we will show how large volumes of satellite data can be read, processed, resampled, and written swiftly and easily with the Pytroll/Satpy package, in a cluster environment. Specifically, examples of efficiently processing Sentinel-1, Sentinel-2, and Himawari/AHI data will be shown, along with performance figures.</div>

scholarly journals Application of Earth Observation Satellite Data to Public Health

2017 ◽  
Vol 83 (4) ◽  
pp. 126-133
Author(s):  
Kei OYOSHI ◽  
Yosei MIZUKAMI ◽  
Takeo TADONO ◽  
Hiroshi MIYOSHI
Keyword(s):  
Public Health ◽  
Satellite Data ◽  
Earth Observation ◽  
Earth Observation Satellite

scholarly journals Desert locust detection using Earth observation satellite data in Mauritania

2019 ◽  
Vol 164 ◽  
pp. 29-37 ◽  
Author(s):  
D. Gómez ◽  
P. Salvador ◽  
J. Sanz ◽  
C. Casanova ◽  
D. Taratiel ◽  
...  
Keyword(s):  
Satellite Data ◽  
Earth Observation ◽  
Desert Locust ◽  
Earth Observation Satellite
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