Who are the target users of this service?
Farmers, Agricultural Holdings, Governmental Agencies, Certification bodies
How will these users access this service?
This is a commercial service, access to the products may be obtained through Vista
What products does this service provide?
The service is divided into two sub-services, which can be used together or separately. The outputs from these are:
- Economic sub-service: site-specific evaluation of crop yield potential
- Ecological sub-service: site-specific evaluation the ecological development potential
How will these products benefit users?
The complete site-specific information service (economic + ecological service) supports farmers in their compliance with EU Greening regulations. The economic service identifies the fields with the lowest returns over several years and several crop types while the ecological service identifies areas of high ecologic potential within the agricultural holding. The combination of both services provides farmers with information on which parts of their land are best suitable to reduce the intensity of production or to be left fallow in order to comply with EU greening regulations. Potential greening areas are areas that have a low yield potential but high potential ecological development.
Users can benefit from the individual services since it is possible to order them separately of each other. E.g. the economical service can support farmers and agricultural holdings in land purchase or renting decisions. Administrative government bodies can use the ecological service to choose areas that are optimally positioned to enhance biodiversity and stimulate ecological developments.
Which Open Data sources drive this service?
- USGS Landsat data
- Copernicus data
- Corine land cover maps
- Natura 2000
- Environmental data of Germany or of individual German federal states
What processing is performed on this data?
The service uses satellite data to retrieve information on biomass and chlorophyll content and other plant parameters of the vegetation. The methods used to get these data are physically-based and require some preparation of the data. For example, the atmospheric conditions and the position of the sun during image acquisition have to be considered to calibrate the data. When this is done, a radiative transfer model is used to retrieve the plant parameters. The results are maps that show the spatial variation of various plant parameters, e.g. the leaf area, which is related to the biomass. This is done for several years and crop types. A geo-statistical analysis is carried out on this data to derive persistent patterns of biomass. Subsequently, the yield potential for specific crops is derived by using the crop growth model PROMET.
The next step is the combination of these results with environmental information. Spatial analysis is applied to identify adjacencies and overlap of the field boundaries with areas that have a high ecological value or potential.
The integration of all available information identifies pieces of land that have a low yield potential and a high potential for ecological development. Those areas are best suitable to be designated as greening areas.
How does this service use Linked Open Data?
At the moment this service uses open data that are stored as standard raster formats or shapefiles. Most input data used for the service are open data (apart from the field boundaries), though they are not linked.
The aim of the project is to identify how to best use linked open data for the described services, with special regard to data exploitation and more efficient ways of data analysis. The semantic description of linked open data could be used to facilitate data mining and research. Different possibilities to use the newly developed linked open data tools (e.g. Strabon, Sextant or Ontop-spatial) are being tested for running analyses during the service calculation. E.g. the tools could be used to identify fields that fulfil certain criteria (E.g. which fields have the lowest economic potential and what environmental protected areas are next to or around them?).
In the long term, the input data needed for the service will hopefully be available as linked open data, meaning that the time needed for data mining and analysis will be significantly reduced.
How Open Data has improved this service
The availability of open data is fundamental for the Land Management Service.
The economic service is based on the analysis of multi-year satellite imagery. Only the availability of open satellite imagery makes it possible to use so many datasets and perform statistical analyses.
The same applies for the environmental data - the service profits from the diversity of available information on our environment, this could be Natura2000 areas that identify bird protection on EU level, or the information on local biotope areas available from the Bavarian Environmental Protection Agency. The more information available, then the better the assessment of ecological potential will be.
How the Shared Platform has improved this service
This service requires the processing of large amounts of satellite imagery - for the economical evaluation, all available satellite data from the last five to ten years is processed and analysed for the respective area of interest. This requires hardware resources and time. Cloud computing will accelerate the service calculation, allowing scalability and flexible use of resources.
Our biggest challenge so far...
... is the integration of all the different data sources. Both raster and vector data need to be integrated and processed. Additionally, the access to the data is very fragmented. A good example of this fragmentation is the German environmental protection data. The data are provided by the federal state agencies but there is no standardized access method - some datasets must be requested, others are freely and openly available. Apart from this, different licencing of different datasets has caused challenges - the licencing models for the data vary between datasets and frequently changing terms and conditions have to be accounted for.