Exploring the optimal geometry of satellites Himawari-8/9 to monitor seasonal variation in vegetation dynamics across Southeast Asia

Dados Bibliográficos

ID15548877
AutoresMisaki Hase (0009-0000-7581-9959, Chiba University, autor correspondente), Kazuhito Ichii (0000-0002-8696-8084, Chiba University), Yuhei Yamamoto (0000-0002-8456-5345, Chiba University), Wei Li (0000-0002-3581-849X, Chiba University), Beichen Zhang (0000-0001-9378-0250, Chiba University), Wei Yang (0000-0001-7249-4386, Chiba University), Tomo’omi Kumagai (0000-0001-8331-271X, University of Hawaiʻi at Mānoa), Yoshiaki Hata (0000-0001-7703-0863, The University of Tokyo), Naoya Takamura (0000-0002-1925-7784, The University of Tokyo), Chandra Shekhar Deshmukh (0000-0003-2660-4315, Asia Pacific International University), Masahito Ueyama (0000-0002-4000-4888), Hiroki Yoshioka (0000-0002-0977-434X, Aichi Prefectural University), Tomoaki Miura (0000-0002-0882-3568, University of Hawaiʻi at Mānoa)
Ano2025
Volume20
Fascículo12
Páginas124001-124001
Data de publicação2025-10-03
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoEnvironmental Research Letters (JOURNAL)
Identificadores do periódicoISSN: 1748-9326 • E-ISSN: 1748-9326
EditoraIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ae0f42
OpenAlexW4414797509
IdiomaEN
Referências citadas50

Dense and widespread tropical rainforests across Southeast Asia are crucial for the global carbon cycle. A new generation geostationary satellite, Himawari-8/9, and onboard sensor, the Advanced Himawari Imager (AHI), enables hyper-temporal vegetation monitoring in this cloud-prone region. However, AHI’s fixed viewing geometry varies spatially, making consistent vegetation monitoring challenging across a wide area at a seasonal scale. This study evaluated four different sun-target-sensor geometry conditions using two-band enhanced vegetation index (EVI2) to achieve near-uniform geometry and enhance the ability to monitor vegetation activities: (i) nadir condition, which used nadir viewing and solar geometry at local solar noon; (ii) local solar noon (LSN) condition, which used pixel-by-pixel fixed viewing and solar geometry at local solar noon; (iii) temporally-constant scattering angle (T-CSA) condition, which used pixel-by-pixel fixed viewing and solar geometry corresponding to the scattering angle which meets the criterion (Gao et al 2024 Remote Sens. Environ. 315 114407); and (iv) spatially-constant scattering angle (S-CSA) condition, which used pixel-by-pixel fixed viewing and solar geometry corresponding to a uniform scattering angle of 140°. Among these, the S-CSA condition most effectively mitigated angular artifacts. The derived EVI2 showed higher correlations with tower-based gross primary productivity (GPP), indicating it better captured seasonal variations in vegetation activity. It also demonstrated spatially consistent temporal variations, least affected by AHI’s unique observation geometry. Applying a near-uniform sun-target-sensor geometry based on the S-CSA condition improves monitoring capability in Southeast Asia and enhances our understanding of vegetation dynamics

Leaf area index · Nadir · Noon · Scattering · Seasonality · Vegetation (pathology · Land Use and Ecosystem Services · Remote Sensing and Land Use · Remote Sensing in Agriculture