Remote sensing for ecological modelling

Introduction

I am a PhD student working on relating remote sensing data to plant traits. I was educated at Wageningen University, where I graduated in Geographical Information Sciences in January 2010, which provided me with a background in GIS, remote sensing, geostatistics and environmental sciences. My position was created and financed by KWR Watercycle Research Institute. Due to the interdisciplinary character, I have three supervisors who contribute their specific knowledge. Flip Witte from KWR is my promotor, Peter van Bodegom advises me on plant traits and Lammert Kooistra from Wageningen University acts as the remote sensing specialist. As such, I distribute my time over all three institutes.

My project

Plant traits are increasingly recognized as a tool to classify plant species on functional grounds. Plant trait values might be used to characterize vegetation in global climate models or as input values for ecological models to predict vegetation types. A model requires full coverage of plant trait values as input, while traits are always measured at point scale. To interpolate from point to area scale, a soil- and/or groundwater map, or plant functional types, are used as approximation of the spatial variation in trait values.
My research project aims to map and quantify plant traits, by developing a method that captures the actual spatial variation in trait values. Hyperspectral remote sensing is a tool with potential to do this, because it can link measured trait values in vegetation relevés to the reflectance values obtained from the same location to create maps of trait values. This technique has already been tested for indicator values (sensu Ellenberg), yielding good prospects. I will therefore additionally investigate which operational traits can be observed by remote sensing and quantify the relation between reflectance and trait values. Also, the influence of site conditions such as plant cover, seasonality and orientation, as well as the effect of measuring at different scales will be investigated. The results of this research will allow us to quickly make vegetation maps of any area, to derive information on site conditions and to validate plant trait values derived from soil, water and climate parameters.

Supervisors

Flip Witte
Lammert Kooistra
Peter van Bodegom

Links

KWR Watercycle research institute

Centre for Geo-information, Wageningen University