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A Novel Approach to Modelling Mangrove Phenology from Satellite Images

Around the world, the effects of changing plant phenology are evident in many ways: from earlier and longer growing seasons to altering the relationships between plants and their natural pollinators. Plant phenology is often monitored using satellite images and parametric methods. Parametric methods assume that ecosystems have unimodal phenologies and that the phenology model is invariant through space and time. In evergreen ecosystems such as mangrove forests, these assumptions may not hold true. Here we present a novel, data-driven approach to extract plant phenology from Landsat imagery using Generalized Additive Models (GAMs). Using GAMs, we created models for six different mangrove forests across Australia.The GAMs allowed us to identify dual phenology events in our study sites, indicated by two instances of high EVI and two instances of low EVI values throughout the year. We contribute to a better understanding of mangrove phenology by presenting a data-driven method that allows us to link physical changes of mangrove forests with satellite imagery. About the speaker Dr Nicolas Younes is a remote sensing and geospatial scientist at the Australian National University. He finished his PhD at James Cook University (JCU) in Queensland, where he used satellite images to explore the natural growth cycles of mangrove forests across Australia. Nicolas stated that, while current methods for detecting growth cycles work well on deciduous forests, they may not apply to mangroves because mangroves are evergreen forests with one, two, and even three growth cycles per year. As a result he proposed a new algorithm for detecting mangrove growth cycles. Nicolas’ background is in environmental engineering. His skills have allowed him to work in various industries including oil and gas, construction, engineering, consulting, and education. Before coming to Australia, Nicolas was a lecturer at a top university in Quito, Ecuador, a passion that he continued to grow during his PhD, where he acted as lecturer and guest lecturer in subjects related to Remote Sensing and GIS. His current work involves measuring key leaf-level flammability traits in eucalyptus forests, and understanding how each trait is captured by terrestrial and spaceborne sensors. He is also involved in the development of OzFuel, a satellite sensor specifically designed to monitor eucalyptus forests and prevent the loss of lives and livelihoods to bushfires.