TY - GEN
T1 - Land validation for GCOM-C1/SGLI using UAV
AU - Honda, Yhosiaki
AU - Kajiwara, Koji
AU - Sharma, Ram
AU - Ono, Akiko
AU - Imaoka, Keiji
AU - Murakami, Hiroshi
AU - Hori, Masahiro
AU - Ono, Yusaku
AU - Rostand, Dim
PY - 2012
Y1 - 2012
N2 - Japan Aerospace Exploration Agency (JAXA) is going to launch new Earth observation satellite GCOM-C1 in near future. The core sensor of GCOM-C1, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for above ground biomass, canopy roughness index, shadow index, etc. In this paper, we introduce the ground observation method developed by using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRF model developed by using multi-angular measurement has been able to obtain structural information from vegetation canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary results of these observations are also be demonstrated.
AB - Japan Aerospace Exploration Agency (JAXA) is going to launch new Earth observation satellite GCOM-C1 in near future. The core sensor of GCOM-C1, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for above ground biomass, canopy roughness index, shadow index, etc. In this paper, we introduce the ground observation method developed by using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRF model developed by using multi-angular measurement has been able to obtain structural information from vegetation canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary results of these observations are also be demonstrated.
KW - Forest canopy
KW - Multi-angular observation
KW - Second Generation Global Imager (SGLI)
KW - UAV
KW - Vegetation productivity
UR - http://www.scopus.com/inward/record.url?scp=84900009666&partnerID=8YFLogxK
U2 - 10.1117/12.975802
DO - 10.1117/12.975802
M3 - 会議への寄与
AN - SCOPUS:84900009666
SN - 9780819492739
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Sensors, Systems, and Next-Generation Satellites XVI
PB - SPIE
T2 - Sensors, Systems, and Next-Generation Satellites XVI
Y2 - 24 September 2012 through 27 September 2012
ER -