< back to presentation overview

Details of the presentation
Presentation Poster presentation
Title Modelling spatial pattern of biodiversity using imaging spectroscopy

PDF Download ---
Short title Modelling spatial pattern of biodiversity

Author(s) Lieckfeld, L.(1); Oldeland, J.(2)

Presenting author Lieckfeld, L.

Institution(s) (1) German Remote Sensing and Data Center (DFD), German Aerospace Center (DLR), Germany; (2) Biocenter Klein Flottbek, University of Hamburg, Germany

Keywords remote sensing, hyperspectral data, Phytodiversity, ecological niche modelling, plant functional types, field spectroscopy

Abstract Biological diversity is a key resource for mankind which needs to be monitored for changes in order to understand ecological systems and to answer the questions posed by different scenarios of a changing world. Therefore, it is important to identify the status quo of the different aspects of biological diversity on different scales. Permanent plot designs coupled with modern remote sensing technology is a central step in providing the spatial and temporal cover which is needed to upscale ecological relevant information to a significant level.
The question that remains is how to measure or monitor biodiversity by means of remote sensing. Hyperspectral remote sensing data shows promising advances of supporting ecologists with highly detailed information on canopy chemistry, dry matter (important for semi-arid ecosystems) and soil characteristics, necessary when spatial extrapolation of ecological data is considered . Vegetation databases filled with occurrence data of thousands of species have to be linked to such remote sensing products by the means of spatial modelling techniques.
In the framework of two interconnected PhD theses the suitability of different ecological data sets for mapping phytodiversity with hyperspectral data were investigated.
We will present the results of the two PhD projects, focussing on different techniques suitable for mapping different levels of biodiversity, e.g. species diversity, functional diversity with different methods (Partial Least Square Regression, Ecological Niche Modelling techniques). Concluding remarks will highlight the opportunities and pitfalls that hyperspectral data offers as a monitoring tool and for extrapolating ecological information in space and time.

Congress Topic Observation System

Topic No. ---
Notes ---

Ref. No. 563