Using Vegetation Indices Developed for Sentinel-2 Multispectral Data to Track Spatiotemporal Changes in the Leaf Area Index of Temperate Deciduous Forests

The leaf area index (LAI) in temperate forests is highly dynamic throughout the season, and lacking such dynamic information has limited our understanding of carbon and water flux patterns in these ecosystems. This study aims to explore the potential of using vegetation indices based on Sentinel-2 data, which includes three additional spectral bands in the red-edge region of its multispectral imager (MSI) sensor compared to previous satellite-borne imagery, to effectively track seasonal variations in LAI within typical cold–temperate deciduous forests originating in rugged terrain in Japan. We evaluated reported vegetation indices and developed an index specific to Sentinel-2 data to effectively monitor the spatiotemporal changes of LAI in mountainous deciduous forests, providing more accurate data for ecological monitoring. Results showed that the developed index (SRB12,B7) was able to track LAI at both seasonal and spatial scales (R2 = 0.576). Further analyses revealed that the index nevertheless performed relatively poorly during the leaf-maturing season when LAI peaks, suggesting that it still suffers from a “saturation” problem. For high-resolution tracking of LAI in temperate deciduous forests at both temporal and spatial scales, future research is needed to incorporate additional information.