Remote Sensing

Remote Sensing is the innovative key technology for surveying, analysing and controlling forests and open landscapes at a macro scale. At the Centre of Life and Food Sciences Weihenstefan, where research is conducted across the spectrum from nano-level to the point of application, remote sensing assures projection to the macro scale. The Workgroup Remote Sensing tests methods and technologies in the ‘Green Sector’; this promotes hands-on externally funded research at the Centre.

Current major fields of development and research are the following:

• Deduction of bio-geo-chemo-physical parameters from FE data (strategic target of ESA for the current decade),
• Synergy and complementarity of radar and optics in the forestry sector
• Formalisation of expertise and integration into hierarchical bodies of rules and regulations (development of scenarios by means of and with a view to the interpretation of remote sensing data)
• Analysis of mixed pixels, problem of scale jumps, field spectroscopy for modelling reflection functions
• Development of devices and systems (measuring installations, goniometer systems, etc.)
• Reflection models and their inversion, interface with growth models
• Definition and testing of sensors (90s: MOMS_02, SIR-C/X-SAR; today: spectrally, radiometrically, geometrically high resolution systems for local applications, multi-sensor systems)

Fields of application are, among others:

• Forest inventories and monitoring with special emphasis on alpine protective forests and for the purpose of catastrophe monitoring, precision farming and precision forestry
• Appraisal of biodiversity in forests and open landscapes
• Mapping of wetlands and macrophyte identification
• Evaluation of vitality and stability of ecosystems
• Creation of foundations for planning, etc.

Through applying these topics the Workgroup Remote Sensing holds an important key position. This is the case, because the introduction of innovative and efficiency enhancing methods of remote sensing is not limited by technical feasibility, but rather by the absence of practical application as well as by a lacking feedback between the improvement of methods and the application.