We engage in basic remote sensing research, developing methods for stepwise processing of remote sensing data from unprocessed instrument data (Level 0), geometrically and radiometrically corrected data in sensor units (Level 1), geophysical variables in imaging geometry (Level 2), to value-added dataproducts mapped on uniform space-time grids (Level 3 and 4). Because it is very important for us that our methods and data are being used we also seek the cooperation with other geoscientists with the aim to develop novel applications of our remote sensing data. This has allowed us to venture into other research areas such as hydrology, climate change, meteorology, agronomy and many others.

We focus our research and development efforts on a selected number of remote sensing instruments. Most importantly, we have developed in-house software written in IDL and Python for fully automated processing of data acquired by the following instruments:

  • Scatterometers (METOP ASCAT, ERS SCAT)
  • Synthetic Aperture Radars (Sentinel-1, ENVISAT ASAR)

Our main data products derived from these sensors are soil moisture, freeze/thaw state, and waterbodies. For several of our data products operational data services are now in place. These have been built up, and are now operated, within the framework of international programmes funded by ESA, EUMETSAT and Copernicus (formerly GMES).

Soil Moisture for Climate Applications

soilmoisture4climateapplications.png In cooperation with the VU University Amsterdam and other partners we have developed methods and software for merging soil moisture data derived from active and passive microwave instruments in order to create a long (> 35 years) Essential Climate Variable (ECV) data record for soil moisture. We keep on improving these methods within the framework of the ESA funded Climate Change Initiative (CCI). The ESA CCI soil moisture data are free of charge and can be obtained from the ESA Website . The CCI dataset is one of the core datasets in the EO WAVE project , which aims to better understand and model the role of soil moisture in driving global vegetation and carbon cycle dynamics. 


Global ASCAT Surface Soil Moisture Data Service

globalASCAT.png Since the mid-1990s we have been investigating and constantly improving algorithms for retrieving soil moisture data from C-band scatterometer measurements. As we have been giving these data out for free to any interested user, the data have found in the meantime many exciting applications, e.g. in numerical weather prediction, runoff forecasting or drought monitoring. The ASCAT soil moisture data services have found institutional support by EUMETSAT’s Satellite Application Facility in Support to Operational Hydrology and Water Management (H-SAF ).


Global ASCAT Soil Water Index Data Service

globalASCATindex.png By filtering the ASCAT surface soil moisture time series with an exponential filter the so-called ASCAT Soil Water Index (SWI) is derived which is an estimate of the moisture content in the soil profile down to a depth of about 0.5 m. Daily ASCAT SWI data are available on a regular global grid through the Global Land monitoring service  of the European Copernicus (formerly GMES) programme.


International Soil Moisture Network

ISMN_timeseries.png Soil moisture measurements made at the ground (in-situ) are pivotal to the evaluation of soil moisture products from models and remote sensing. The International Soil Moisture Network (ISMN) collects and harmonizes in-situ soil moisture measurements provided by a wide variety of locally and regionally operating networks and makes them available to the user community through a centralized data portal. In addition, methods are being developed to check the quality of the individual measurements and to characterize the suitability of individual sites for evaluating coarse scale soil moisture products.


Experimental 1 km ASAR Soil Moisture Data Service

asar_1km.png Sentinel-1 will be the first SAR satellite capable of delivering finer resolution (0.1-1 km) surface soil moisture data with a short revisit period (2-8 days depending on latitude and region). For scientific exploration and demonstration a pre-operational service for 1 km ENVISAT ASAR soil moisture data has been developed with the ESA funded SHARE  and TIGERNET  projects. These data are available for Africa, Australia and some other selected regions worldwide.


Permafrost Monitoring

permafrost.png Permafrost is an Essential Climate Variable (ECV). The objective of the ESA funded Data User Element project PERMAFROST was to establish a monitoring system based on satellite data. A circumpolar data set including soil moisture and surface status based on ASCAT and supplemented by ENVISAT ASAR basedmaps has been made available at the Permafrost Website . The ESA funded Support to Science Element Project ALANIS-Methane  supported these developments and also included wetland information across Siberia. These services are now utilized within the FP7 fundedproject PAGE21  'Changing Permafrost in the Arctic and its global effects in the21st Century'.


Global Backscatter Data Base

global_backscatter.png The Global Backscatter Model was generated from a more than 70000 ENVISAT ASAR (Advanced Syntethic Aperture Radar) images, acquired in the period between 2004 and 2010. These data were processed with the SAR Geophysical Retrieval Toolbox (SGRT), developed by TU Vienna. On average, a time series of 260 ASAR acquisitions were used per location for retrieval of the model parameters. Software for orbit propagation and sensor pointing are used to take into account the observation geometry for simulation of realistic radar images. The Global Backscatter Model is the first radar backscatter model for the global land surface at the 1 km scale.