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MISAR

MISAR

Wolfgang Wagner (ORCID: 0000-0001-7704-6857)
  • Grant DOI 10.55776/P16515
  • Funding program Principal Investigator Projects
  • Status ended
  • Start November 1, 2003
  • End December 31, 2006
  • Funding amount € 199,815

Disciplines

Other Natural Sciences (10%); Geosciences (10%); Environmental Engineering, Applied Geosciences (80%)

Keywords

    Synthetic Aperture Radar, ScanSAR, ENVISAT, Soil moisture, Biomass

Abstract Final report

On February 28, 2002 the European Environmental Satellite ENVISAT was launched. lt carries a Synthetic Aperture Radar (SAR) operated in C-band (5.3 GHz) which will ensure continuity with the SAR an board of the European Remote Sensing Satellites ERS-1/2. The Advanced SAR (ASAR) an ENVISAT features enhanced capability in terms of coverage, range of incidence angles, polarization, and modes of operation. This opens the possibility to study new approaches for retrieving geophysical parameters such as biomass or soil moisture. The interaction of a radar signal with vegetation and soil is dependent an a number of system and target parameters. The frequency, polarization, incidence angle, look direction and resolution all influence the sensor capabilities, while important target parameters are surface roughness, dielectric constant of soil and vegetation, and structural geometry of the vegetation. Various approaches to retrieve geo-physical parameters from radar data have been tested, ranging from simple regression models to elaborated theoretical models. More recently, approaches involving change detection and neural networks have gamered attention. Experience has shown that essential elements to improve retrieval capabilities are to use multi-dimensional data such as offered by the new radar systems (multi-polarization, multi-incidence, multi-temporal) and to constrain the problem to reduce the number of influencing parameters. One of the ASAR operation modi is the ScanSAR modus which acquires backscatter data over a swath of more than 400 km. Such the instrument is capable of providing frequent measurements over a wide range of incidence angles. As work with the ERS scatterometer has shown multiincidence, multi-temporal backscatter measurements provide important information about vegetation and soil moisture changes, it is the goal of this project to study the capability of the ASAR ScanSAR modus for biomass and soil moisture retrieval. Study areas are located in Siberia, Spain, China and Western Africa where high-quality reference data are available through international research collaboration.

Europe`s largest environmental satellite ENVISAT was launched in 2002. It carries a large number of earth observation sensors for monitoring the global environment. One of ENVISAT`s sensors is the Advanced Synthetic Aperture Radar (ASAR) which sends electromagnetic waves towards the earth`s surface and measures the energy of the waves scattered backwards to the satellite. ASAR works in the microwave region of the electromagnetic spectrum and is able to acquire radar images day and night under all weather conditions. But ASAR can do much more than just providing nice images. Using physical models the ASAR measurements can be inverted to provide information about the properties of the land surface, oceans and ice sheets. In the MISAR project it was investigated how ENVISAT can be used for monitoring soil moisture and wetlands. These two parameters are of fundamental importance for society because of their important influence on agricultural production, catchment hydrology, water resources, ecosystem functions, wildlife, etc. The MISAR project demonstrated that global scale monitoring of soil moisture and wetlands at 150 m and 1 km scale is possible using ENVISAT ASAR. The scientific methods developed within MISAR have already been applied in an international project funded by the European Space Agency which aims at developing an soil moisture monitoring system for southern Africa.

Research institution(s)
  • Technische Universität Wien - 100%
International project participants
  • Xingmin Mu, Chinese Academy of Sciences - China
  • Christiane Schmullius, Universität Jena - Germany
  • Rob Beck, Netherland Geomatics and Earth Observation B.V. - Netherlands
  • Jose Martinez-Fernandez, University of Salamanca - Spain

Research Output

  • 401 Citations
  • 4 Publications

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