Near-real time forecasting and change detection for an open ecosystem
figshare, July 2020
Slingsby, Jasper, Wilson, Adam, Moncrieff, Glenn
Presentation given for the GEO BON Open Science Meeting, July 2020 https://conf2020.geobon.org/ - complete with narration!We present a hierarchical Bayesian modelling framework that allows us to forecast remotely sensed vegetation indices in a fire-dependent and seasonally fluctuating ecosystem, the Fynbos of South Africa. This framework allows several applications including: 1) detecting near real-time changes in the state of the ecosystem by comparing observed vegetation signal with the model forecasts; 2) determining the influence of plant traits on vegetation productivity and seasonality; 3) forecasting changes in vegetation productivity and seasonality under altered climate or community composition; and 4) estimating ecosystem properties like leaf area index (LAI) or above ground biomass. As such, it provides the means to draw linkages across and/or monitor several EBV classes.
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