Japan Geoscience Union Meeting 2024

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-CG Complex & General

[A-CG35] Global Carbon Cycle Observation and Analysis

Tue. May 28, 2024 9:00 AM - 10:30 AM 301A (International Conference Hall, Makuhari Messe)

convener:Kazuhito Ichii(Chiba University), Prabir Patra(Principal Scientist at Research Institute for Global Change, JAMSTEC and Professor at Research Institute for Humanity and Nature), Akihiko Ito(University of Tokyo), Chairperson:Kazuhito Ichii(Chiba University)

9:45 AM - 10:00 AM

[ACG35-04] Analyzing the Effect of Different MODIS Product Versions Towards Long-term Terrestrial Carbon Cycle Monitoring in Asia

*Daniel Joseph Henri1, Kazuhito Ichii1 (1.Chiba University)

Keywords:MODIS, terrestrial carbon cycle, Remote sensing, Data-driven model

NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor-equipped satellites have been gathering data since the year 2000. Over this time, NASA has produced versions of this data, each of which apply different processing and calibration techniques to more accurately represent the data which the MODIS sensors transmit. There is also the issue of MODIS sensor degradation which, over time, has led to inaccuracies in the sensor readings, and consequently to the post-processing outputs of MODIS data. Because MODIS data are commonly used in environmental sciences, the changes in the data from version to version, as well as from sensor degradation, can have implications for our understanding of the terrestrial carbon cycle. This study will compare different product versions of MODIS data in two ways; by using long-term trends of MODIS land products, and by using modeled terrestrial carbon fluxes based on data-driven estimations using MODIS data and data from Eddy Covariance Flux Towers in the AsiaFlux network, with a support vector regression machine learning model. This will result in long-term carbon-flux estimations for all of Asia. This study will build on this previous research by taking into account the newest MODIS data version, and temporally extending estimations over previous studies. This will allow a better understanding of the changes in accuracy over versions and time of MODIS data in Asia.