River Floodplain Vegetation Scenario Development Using Imaging Spectroscopy Derived Products as Input Variables in a Dynamic Vegetation Model

Abstract

River floodplains are becoming increasingly subject to multifunctional land-use. In this contribution, we are linking imaging spectrometer derived products with a dynamic vegetation model to improve the simulation and evaluation of scenarios for a river floodplain in the Netherlands. In particular, we are using airborne HyMap imaging spectrometer data to derive Leaf Area Index (LAI), spatial distribution of Plant Functional Types (PFT), and model dominant species abundances as input for the ecological model. We use the dynamic vegetation model (DVM) SMART2-SUMO to simulate vegetation succession under scenarios of changing abiotic conditions and management regimes. SMART2 is a soil chemical model whereas SUMO describes plant competition and resulting vegetation succession. We validate all remote sensing derived products and the DVM calibration independently using extensive field sampling. We conclude that the dynamic vegetation models can be successfully initialized using imaging spectrometer data at currently unprecedented accuracy. However, all efforts undertaken for validation in this contribution may significantly exceed capacities for national or continental scale application of the proposed method.