JpGU-AGU Joint Meeting 2020

Presentation information

[E] Oral

H (Human Geosciences ) » H-TT Technology & Techniques

[H-TT15] Environmental Remote Sensing

convener:Wei Yang(Chiba University), Akihiko Kondoh(Center for Environmental Remote Sensing, Chiba University), Carolynne Hultquist(Columbia University), Elena Sava(US Army Corps of Engineers Geospatial Research Laboratory), Guido Cervone(Pennsylvania State University Main Campus)

[HTT15-03] Update of GCOM-C/SGLI Leaf Area Index & fraction of Absorbed Photosynthetically Active Radiation products

*Toshiyuki Kobayashi1, Hideki Kobayashi2, Wei Yang3, Yoshiaki HONDA3, Yuhsaku Ono, Shin Nagai2, Tomoko Akitsu4, Kenlo Nasahara4, Masahiro Hori1, Hiroshi Murakami1 (1.Japan Aerospace Exploration Agency, 2.Japan Agency for Marine-Earth Science and Technology, 3.Chiba University, 4.University of Tsukuba)

Keywords:LAI, FAPAR

The Japan Aerospace Exploration Agency (JAXA) launched the Global Change Observation Mission - Climate (GCOM-C) satellite on December 23rd, 2017. The 1st version of the GCOM-C/SGLI Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) products were released on December 2018. LAI and fAPAR were estimated based on the look-up tables showing the relationships between the multi-angle atmospherically-corrected surface reflectance data and the LAI or fAPAR. The relationships between LAI/fAPAR and surface reflectance data at the top of canopy were simulated using a radiative transfer simulator, the Forest Light Environmental Simulator (FLiES) [1].

This year, we are planning to release the 2nd version of the products, in which the algorithms and the data quality will be improved. In this research, we introduce the current situation of the Leaf Area Index (LAI) product and summarize the updates for the 2nd version of the products.


[1] H. Kobayashi et al., A coupled 1-D atmosphere and 3-D canopy radiative transfer model for canopy reflectance, light environment, and photosynthesis simulation in a heterogeneous landscape, Remote Sensing of Environment, 112 (2008), 173-185.