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Hourly GPP Estimation In Australia Using Himawari-8 AHI ProductsWe extended the MODIS 17 algorithm to hourly Gross Primary Product (GPP) estimation for Australia in 2018. AHI 1-km data are available at NASA Earth Exchange (NEX) facility. The high-frequent observation of Advanced Himawari Imager (AHI) enabled us to calculate hourly GPP, which is corresponding to ground observation of carbon flux measured by TERN OzFlux. We interpolated the weather observation data to 1-km grid over Australia ingesting AHI reflectance and radiometric temperature data (NEX-Gridded Hourly Meteorology (NEX-GHM)). Then, we applied MODIS 17 algorithm to each grid with optimized climate regulation functions. The estimation of climate and GPP were well correlated with OzFlux ground observation data.
Document ID
20205004726
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Hirofumi Hashimoto (California State University, Monterey Bay Seaside, California, United States)
Weile Wang (California State University, Monterey Bay Seaside, California, United States)
Andrew Michaelis (Bay Area Environmental Research Institute Petaluma, California, United States)
Hideaki Takenaka (Chiba University Chiba, Japan)
Atsushi Higuchi (Chiba University Chiba, Japan)
Ramakrishna Nemani (Ames Research Center Mountain View, California, United States)
Date Acquired
July 20, 2020
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
20205004726
Meeting Information
Meeting: 2020 IEEE International Geoscience and Remote Sensing Symposium
Location: Virtual
Country: US
Start Date: September 26, 2020
End Date: October 2, 2020
Sponsors: IEEE Geoscience and Remote Sensing Society
Funding Number(s)
CONTRACT_GRANT: NNX12AD05A
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
Keywords
Himawari-8
AHI
Australia
GPP
MODIS 17 algorithm

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