ENVISAT Data Supporting to the Convention on Biological Diversity - the Case of Inland Waters
Brockmann, Carsten1; Philipson, Petra2; Odermatt, Daniel1; Paganini, Marc3; Wramner, Per2; Brito, Josť Carlos4; Stelzer, Kerstin1; Sorensen, Kai5; Greb, Steven6; Koponen, Sampsa7
1Brockmann Consult GmbH, GERMANY; 2Brockmann Geomatics, SWEDEN; 3ESA ESRIN, ITALY; 4CIBIO, PORTUGAL; 5NIVA, NORWAY; 6Wisconsin Department of Natural Resources, UNITED STATES; 7SYKE, FINLAND

ENVISAT data supporting the Convention on Biological Diversity - the case of inland waters Ecosystem functioning is known to be of major importance for the well-being of humans. The conservation of biological diversity is one key element in maintaining ecosystems in a healthy condition and is central to main objectives of the Convention on Biological Diversity (CBD). In order to meet the CBDís objectives the contributing parties have agreed on a Strategic Plan for Biodiversity 2011 - 2020. The plan is constructed around 20 headline targets, also called the Aichi Biodiversity Targets.

With the Diversity II Project, the Data User Element (DUE) of the European Space Agency (ESA) aims at contributing to the implementation of the Strategic Plan by exploiting currently available Earth Observation (EO) data and by preparing for the use of future satelliteís data for two important ecosystems: drylands and inland waters. The primary data sources are Earth Observation data from the ESA ENVISAT satellite, specifically from the MERIS, AATSR, RA-2 and ASAR instruments. Among these, the MERIS Full Resolution data are the most important dataset. The project will also pave the way for a future sustainable provision of information using future satellites, such as the Sentinel-3 and Proba-V. A central technical objective is to transform MERIS, OLCI and other coarse/medium resolution sensors observations into information such as the biogeochemical parameters (e.g. chlorophyll concentration) required to support the CBD Strategic Plan and to define and develop a number of indicators for showing the status and trends of biological diversity in inland waters and in drylands.

Deriving the basic water quantity and water quality parameters for inland waters is a challenge. In particular there are methodological problems, specifically for the atmospheric correction, that need to be solved to derive parameters for optically complex waters. Hence different pre-processing steps, atmospheric correction schemes, and in-water processing algorithm were evaluated over 10 representative lakes in order to design the processing chain. In the end, key parameters, status maps, associated change maps, status indicators and trend indicators are aggregated at different administrative and biome level. These key parameters are:

  • availability of freshwater;
  • quality of freshwater, reflected in its water constituents such as chlorophyll-a and/ or suspended matter concentration, as well as by its temperature;

    Eventually the global-scale products will produce results for 300 large perennial inland waters and cover a time range from 2002 to 2012. The software to generate the Diversity II Products is complex and has to work on very large amounts of data efficiently. The processing chain includes steps from child product generation, merging of data from different sensors and sources, cloud screening, atmospheric correction, bio-optical inversions, indices calculation, spatial and temporal integration, change detection, indicator calculation, and finally map generation. The production involves processing of more than 100 terabytes of input data. The new algorithms for inland waters will be developed largely using the ESA BEAM toolbox.

    A practical example will be demonstrated for Swedish Lakes: the CBD as well as many other internationally coordinated environmental protection programs require the assessment of the ecological status of habitats and the mapping of the distribution of species and habitats in Swedish freshwaters. These mandatory assessments are hampered today by the size of the largest lakes and the enormous number of lakes in total. However, prime ecological indicators (primary production, temperature, etc.) can be measured by remote sensing and assessed through spatial modeling. This auxiliary information can then be used to optimise fish monitoring programs and extend their coverage. Remote sensing can thus provide the key to the implementation of many of the directives and management plans at the desired spatial and temporal coverage.