Paper
19 November 2012 Land validation for GCOM-C1/SGLI using UAV
Yhosiaki Honda, Koji Kajiwara, Ram Sharma, Akiko Ono, Keiji Imaoka, Hiroshi Murakami, Masahiro Hori, Yusaku Ono, Dim Rostand
Author Affiliations +
Proceedings Volume 8533, Sensors, Systems, and Next-Generation Satellites XVI; 853308 (2012) https://doi.org/10.1117/12.975802
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom
Abstract
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yhosiaki Honda, Koji Kajiwara, Ram Sharma, Akiko Ono, Keiji Imaoka, Hiroshi Murakami, Masahiro Hori, Yusaku Ono, and Dim Rostand "Land validation for GCOM-C1/SGLI using UAV", Proc. SPIE 8533, Sensors, Systems, and Next-Generation Satellites XVI, 853308 (19 November 2012); https://doi.org/10.1117/12.975802
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Unmanned aerial vehicles

Bidirectional reflectance transmission function

Reflectivity

Sensors

Algorithm development

Vegetation

Satellites

Back to Top