日本地球惑星科学連合2024年大会

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セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG37] 陸域生態系の物質循環

2024年5月28日(火) 13:45 〜 15:15 201A (幕張メッセ国際会議場)

コンビーナ:寺本 宗正(鳥取大学乾燥地研究センター)、加藤 知道(北海道大学農学研究院)、市井 和仁(千葉大学)、伊勢 武史(京都大学フィールド科学教育研究センター)、座長:寺本 宗正(鳥取大学乾燥地研究センター)

14:15 〜 14:30

[ACG37-03] Seasonal variation in vegetation activities across Southeast Asia observed by Himawari-8 AHI

*長谷 美咲1市井 和仁1山本 雄平1李 偉1、Beichen Zhang1 (1.千葉大学環境リモートセンシング研究センター)

キーワード:東南アジア、ひまわり8号、正規化植生指数

Seasonal changes in vegetation activity and their driving environmental factors over Southeast Asia remain unclear. One of the reasons for this is the heavy cloud cover, which limits land surface observations from space. Conventional polar-orbiting satellites have difficulty in monitoring below the seasonal scale due to their low observation frequency. In contrast, the Advanced Himawari Imager (AHI) onboard the Geostationary Earth Orbit satellite Himawari-8 has an observation frequency of 10 minutes and is expected to improve the acquisition frequency of clear-sky scenes. Furthermore, satellite-based solar induced fluorescence (SIF) can be an alternative observation. The purpose of this study is to capture the seasonal changes in vegetation activities using Himawari-8 and to evaluate the environmental factors that drive their seasonal changes. Furthermore, we compared differences between Himawari-8-based and the Tropospheric Monitoring Instrument (TROPOMI)-SIF-based analyses. First, to demonstrate effectiveness of AHI, we compared among AHI and MOD-/ MYD-09GA products from Moderate Resolution Imaging Spectroradiometer (MODIS). Normalized Difference Vegetation Index (NDVI) were calculated using surface reflectance datasets. Each NDVI was composited for 16-day using cloud-free observations. Furthermore, 16-day composited NDVI was compared with SIF from TROPOMI. The analysis at specific sites (AsiaFlux sites) suggested that AHI has over 50 times higher acquisition of clear sky scene than MODIS. This greatly reduced the missing values in the MODIS-NDVI, and AHI-NDVI correlated much better with SIF than MODIS-NDVI at each site. This indicates that AHI can capture seasonal changes in more detail than MODIS. In spatial analysis, the amplitude of AHI-NDVI showed good agreement with landcover. Also, the result of comparison between AHI-NDVI and climate variables showed that soil moisture had impact on seasonal change in cropland, temperature and solar radiation had impact on tropical evergreen forest. Furthermore, temperature tended to have more impact on it over low altitude areas, and solar radiation tended to have impact on it over high altitude areas.