NEWS (see all)
2018/11/02: 11月27-28日に高松で開催される「日本リモートセンシング学会 第65回（平成30年度秋季）学術講演会」において、当研究室より3件の発表を行います。４年生学生にとっては、最初の学会発表です。また、「ひまわり」「クロロフィル蛍光」ともに、当研究室から初めての成果発表です！
http://www.rssj.or.jp/act/conference/65th_autumn/
1. 林 航大・市井和仁・村上和隆・吉岡博貴・奈佐原顕郎・秋津朋子・井手玲子，ひまわり8号データを用いた広域植生モニタリングデータセットの構築に向けて
2. 林 悠介・村上和隆・劉 治彦・市井和仁, 衛星観測クロロフィル蛍光の導入による光合成量推定精度の向上
3. 市井和仁・村上和隆・林 悠介・劉 治彦, 2018年猛暑における東アジアの植生パラメタ偏差の解析
2018/10/12: A new project "Improvement of machine-learning based GPP estimation using satellite-based SIF data", supported by the Sumitomo Foundation, is just accepted and started.
2018/10/10: An article on summer heatwave in 2018 is released in CEReS Newsletters (September issue in Japanese).
2018/10/06: K. Ichii will give a talk in 11th GEOSS Asia Pacific Symposium Oct 25 in Kyoto on how eddy-covariance network data (e.g. AsiaFlux, JapanFlux) constrain bottom-up CO2 budget estimation.
2018/10/06: K. Ichii will give a talk in ILTER EAP scientific conference on Oct 15 in Taichun, Taiwan with title as "Data-driven analysis of terrestrial CO2 fluxes using AsiaFlux data."
2018/10/02: New member joined, one PhD student (Mart Zaya) and one Master student (Liu Zhiyan - formerly research student in this group), Welcome !
2018/09/19: 本グループの研究報告として、プレスリリース「今年の夏は地表面温度も過去17年間で最高だった！～衛星リモートセンシングが捉えた７月の猛暑～」を千葉大学より配信しました。
http://www.rssj.or.jp/act/conference/65th_autumn/
1. 林 航大・市井和仁・村上和隆・吉岡博貴・奈佐原顕郎・秋津朋子・井手玲子，ひまわり8号データを用いた広域植生モニタリングデータセットの構築に向けて
2. 林 悠介・村上和隆・劉 治彦・市井和仁, 衛星観測クロロフィル蛍光の導入による光合成量推定精度の向上
3. 市井和仁・村上和隆・林 悠介・劉 治彦, 2018年猛暑における東アジアの植生パラメタ偏差の解析
2018/10/12: A new project "Improvement of machine-learning based GPP estimation using satellite-based SIF data", supported by the Sumitomo Foundation, is just accepted and started.
2018/10/10: An article on summer heatwave in 2018 is released in CEReS Newsletters (September issue in Japanese).
2018/10/06: K. Ichii will give a talk in 11th GEOSS Asia Pacific Symposium Oct 25 in Kyoto on how eddy-covariance network data (e.g. AsiaFlux, JapanFlux) constrain bottom-up CO2 budget estimation.
2018/10/06: K. Ichii will give a talk in ILTER EAP scientific conference on Oct 15 in Taichun, Taiwan with title as "Data-driven analysis of terrestrial CO2 fluxes using AsiaFlux data."
2018/10/02: New member joined, one PhD student (Mart Zaya) and one Master student (Liu Zhiyan - formerly research student in this group), Welcome !
2018/09/19: 本グループの研究報告として、プレスリリース「今年の夏は地表面温度も過去17年間で最高だった！～衛星リモートセンシングが捉えた７月の猛暑～」を千葉大学より配信しました。
MISSION
Mission of our group is "monitoring and modeling of earth system toward better prediction of our future earth." Our approach is to integrate and synthesize of available data and models to understand earth system in more comprehensive ways. Our main target is 'terrestrial biosphere' from regional to global scales. We use network of ground observation (e.g. FLUXNET, AsiaFlux), remote sensing data, numerical models (terrestrial ecosystem models), and atmospheric observations.
RESEARCH
Environment Monitoring and Modeling Group
Understandings of Terrestrial CO2 Budget Changes at Global Scales by SynthesisUsing bottom-up approach (e.g ecosystem models) and top-down approaches (e.g. atmospheric inversions), we are working on quantification of terrestrial CO2 budget at various scales (e.g. global, southeast Asia, Asia). These works can become a contribution to global projects such as Future Earth. [Kondo et al. 2018 Nature Comm.; Kondo et al. 2018 GRL; Ichii et al. 2013]. 
Data-driven estimation of terrestrial CO2 fluxes
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Development of a Terrestrial CO2 Flux Product for GCOM-C SGLI Sensor
Using a diagnostic terrestrial biosphere model, AsiaFlux/FLUXNET observation network data, our group is developing a terrestrial CO2 flux (GPP, NPP, NEP) product for GCOM-C SGLI sensor (JAXA's satellite). Our product will be an official research products and released to public.
Satellite-based Monitoring of Vegetation Changes from Regional to Continental ScaleUsing long-term data of satellite remote sensing, we analyzed and detected vegetation and land cover changes from regional to global scales [Sekizawa et al. 2015; Ichii et al. 2013; Ichii et al. 2002; Kawabata et al. 2001]. |
Data-Model Integration toward refinement of terrestrial ecosystem modelsBy integrating satellite data into terrestrial ecosystem model, we estimated unknown ecosystem parameters and successfully improved models. [Kondo et al. 2017; Ichii et al. 2007, 2009].
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Top-down and Bottom-up Synthesis toward Better Understandings of Global Carbon Cycle
We are working on synthesis of multiple independent estimations of terrestrial CO2 fluxes. Estimations include top-down approach (atmospheric inversion model) and bottom-up approach (process-based model, data-driven model, satellite products). [Kondo et al. 2015; Ichii et al. 2017].
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Earth System Modeling
We demonstrated that future projection of CO2 budget and climate might change if terrestrial carbon cycle model was improved using FLUXNET data. [Suzuki and Ichii, 2010]. |
Model-data intercomparison in Asia etc.
We conducted model-data intercomparison project (Asia-MIP, CarboEastAsia-MIP, and Japan-MIP) to test current model performance using multiple models and observation data [Ichii et al. 2013; Ichii et al. 2010]. |
Keywords:
Terrestrial Biosphere, Remote Sensing, Model, AsiaFlux,Model-data Integration, Synthesis, Carbon Cycle, Water Cycle, Machine Learning
Terrestrial Biosphere, Remote Sensing, Model, AsiaFlux,Model-data Integration, Synthesis, Carbon Cycle, Water Cycle, Machine Learning
