Summary: Due to political and economic reasons (e.g. rising energy prices) a strong expansion of energy crops is taking place in many regions of the world. In this context the extend and distribution of energy crops as well as the retrieval of crop parameters, e.g. biomass and biomethane potential, are of interest for different entities. Moreover in many (agricultural) applications the user is interested to retrieve information on one specific crop type, e.g. the spatial extend, the biomass or total yield of energy crops in an specific area.

The project aims on the development of methods to quantify the biomethane potential of crops. The IGG sub-project deals with the development of adequate classification and regression strategies for an enhanced mapping of energy crops and retrieval of biophysical parameters by combining SAR and hyperspectral images. The specific aims of the projects are:

• Development of a one-class-classifier (OCC) for mapping energy crops
• Adaption of recent regression methods (e.g., support vector regressions) and further development of ensemble based regression methods.
• Development of innovative concepts for sensor fusion to estimation biophysical parameters with higher accuracy.

Project duration: 07/2010 – 06/2013

Principal Investigator:

Björn Waske

Projects staff:

Benjamin Mack

Cooperation partners:

Prof. Dr. T. Udelhoven, Trier University, Faculty of Geography and Geosciences, Remote Sensing Department, 54286 Trier, Germany

Dr. Holger Lilienthal, Julius Kühn-Institut (JKI), Federal Research Centre for Cultivated Plants, 38116 Braunschweig, Germany

Funding:

This study is funded by the Space Agency of the German Aerospace Center (DLR) with federal funds of the German Federal Ministry of Economics and Technology (BMWi) under FKZ 50 EE 1011.