제목: Observing and modeling vegetation phenology using remote sensing and data-driven model​​​​​​​​​​​​​​​

장소: 과학관 B102호 

Abstract:

Vegetation phenology plays an important role in controlling seasonal variation in ecosystem processes and land-atmosphere exchanges, such as the timing and magnitude of carbon, water, and energy fluxes. As the only viable source providing time series of vegetation activity at local to global scales, and from days to decades, remote sensing has provided invaluable records in vegetation phenology over the last decades. Recently, new sources of remote sensing imagery collected at moderate to high spatial resolutions have dramatically expanded the scope and quality of data available for phenological research using remote sensing. In parallel, modeling studies using data-driven approaches have provided different perspectives compared to results from studies using conventional process-based models, in terms of how vegetation phenology will change in a changing climate. In this talk, I will synthesize findings from our recent studies focusing on two dimensions. First, I will introduce recent progress in observing vegetation phenology using remote sensing, especially from moderate (i.e., from Landsat and Sentinel-2 at 30 m) to high (i.e., from commercial PlanetScope imagery at 3 m) spatial resolution satellite imagery. Second, I will present results from model-based studies using a Bayesian approach that exploits remote sensing to improve understanding of how bioclimatic forcings control the start and end of the growing season.​