|| 要旨トップ | 目次 |||日本生態学会第64回全国大会 (2017年3月、東京) 講演要旨
一般講演（ポスター発表） P1-P-430 （Poster presentation）
Leaf area index (LAI) is indicator of terrestrial ecosystem structure, which is largely responsible for ecosystem functions, such as carbon cycle by light absorption and photosynthesis and water cycle by leaf transpiration. Estimation of LAI by satellite remote sensing is crucial for evaluating the spatial distribution of ecosystem processes over large areas and for analyzing ecosystem functions by ecosystem simulation models.
This study aimed to estimate spatial variation of LAI over River Basin of the Daihachiga River (Takayama, Gifu, Japan) with fine spatial resolution. We applied LAI model based on Monsi-Saeki theory for LAI mapping on a Landsat image of 2013/05/26, validated the map at 4 sites of deciduous broadleaved, deciduous coniferous and evergreen coniferous forests.
Application of elevation dependent dark object subtraction for atmospheric correction and Minnaert correction for topographic normalization allowed reasonable estimation of LAI in 30 m resolution. These analyses revealed a spatial pattern of LAI, distinctive for mountainous terrains, with higher LAI in lower altitudes and south-facing slopes and lower LAI in higher altitudes and north-facing slopes in spring season.
The Landsat based LAI map has fine spatial resolution, which is essential for ecological studies in areas with complex topography and high vegetation heterogeneity. Although the presented approach requires further development, it could contribute to ecosystem studies of carbon cycle, phenology and forest dynamics and it could improve existing LAI estimation algorithms.