Study for Multi- footprint Observation Lidar and Image(MOLI) Project
JAXA Supercomputer System Annual Report February 2022-January 2023
Report Number: R22EDG20200
Subject Category: Research and Development
- Responsible Representative: Rei Mitsuhashi, Reserch and Development Directorate, MOLI Pre-Project Team
- Contact Information: Rei Mitsuhashi(mitsuhashi.rei@jaxa.jp)
- Members: Rei Mitsuhashi, Yoshito Sawada
Abstract
Develop algorithms for processing space lidar observation data in the ISS Onboard Lidar Demonstration (MOLI) project.
Reference URL
N/A
Reasons and benefits of using JAXA Supercomputer System
MOLI observes the entire globe with lidar, and its data can reach several billion shots per year. In addition, some of the algorithms for processing this data use deep learning, which requires more computation time than CPU calculations. JSS3 is the only system that can process such data in the limited time available for product distribution, and we are considering using it not only for algorithm development, but also as a processing system for products.
Translated with www.DeepL.com/Translator (free version)
Achievements of the Year
(1) Simulation of large-scale space lidar observation data was conducted using ALS data from the Izu Peninsula, and an algorithm for MOLI products was developed to use the data as teacher data for deep learning. This may enable us to measure tree height and biomass with higher accuracy than before, and we plan to publish a paper on the results in FY2023.
(2) Algorithms were developed to create global AGB maps by fusing GCOM-C/SGLI data with space lidar GEDI observation data. As an extension of the SGLI product ver. 3 development conducted last year, a land cover classification was conducted aiming at a classification related to plant volume density rather than plant type.
Publications
N/A
Usage of JSS
Computational Information
- Process Parallelization Methods: N/A
- Thread Parallelization Methods: Automatic Parallelization
- Number of Processes: 1
- Elapsed Time per Case: 12 Hour(s)
JSS3 Resources Used
Fraction of Usage in Total Resources*1(%): 1.19
Details
Please refer to System Configuration of JSS3 for the system configuration and major specifications of JSS3.
System Name | CPU Resources Used(Core x Hours) | Fraction of Usage*2(%) |
---|---|---|
TOKI-SORA | 0.00 | 0.00 |
TOKI-ST | 9080117.84 | 9.08 |
TOKI-GP | 49079.68 | 2.09 |
TOKI-XM | 0.00 | 0.00 |
TOKI-LM | 16949.10 | 1.14 |
TOKI-TST | 119760.35 | 3.16 |
TOKI-TGP | 0.00 | 0.00 |
TOKI-TLM | 622.92 | 1.29 |
File System Name | Storage Assigned(GiB) | Fraction of Usage*2(%) |
---|---|---|
/home | 10.00 | 0.01 |
/data and /data2 | 163890.00 | 1.26 |
/ssd | 100.00 | 0.01 |
Archiver Name | Storage Used(TiB) | Fraction of Usage*2(%) |
---|---|---|
J-SPACE | 388.55 | 1.72 |
*1: Fraction of Usage in Total Resources: Weighted average of three resource types (Computing, File System, and Archiver).
*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.
ISV Software Licenses Used
ISV Software Licenses Used(Hours) | Fraction of Usage*2(%) | |
---|---|---|
ISV Software Licenses(Total) | 0.00 | 0.00 |
*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.
JAXA Supercomputer System Annual Report February 2022-January 2023