Phenological Inference from Times Series Remote Sensing Data

Phenology broadly refers to seasonal phenomena associated with biological cycles and activity of plants and animals triggered by changes in temperature, precipitation, daylight, and other environmental factors. While specific schedule and timing of these changes may vary from year to year due to natural variations in climate and weather, directional phenological shifts such as consistently earlier times of leaf flushing and flowering of plants may provide important early warning signals of major climatic transitions and global warming effects (Cleland et al., 2007). Such shifts may be observed not only in natural systems, but also in heavily human-dominated landscapes. For example, urban regions with higher temperatures compared to exurbia and wildlands may also display longer growing seasons (Zipper et al., 2016). The ability to monitor phenological changes is crucial for understanding the underlying physical transitions in the landscapes and dynamics of important ecosystem services such as productivity and uptake of atmospheric greenhouse gas CO₂ by plants, agricultural crop pollination, and biological pest control associated with plant-animal seasonal cycles and many other (Cho et al., 2017; Klosterman et al., 2014; Richardson et al., 2012; Toomey et al., 2015).