Development of geospatial data infrastructure for customers

Mastering tools, such as Geographical Information Systems (GIS) or EO tools which can be operated after a short induction period, is sufficient for implementing small projects. The continuous production of satellite information, meaning the regular monitoring of a large number of agricultural areas or the simulation of crop yields, presupposes the industrial organization of processes for preparing information products. These processes commence with the automated management of customer enquiries, the selection and downloading of satellite images, their automated processing, and computerized quality control. The entire workflow involves procedure controlled intersection with other spatial information, such as statistics, weather, and soil data, and finishes with sophisticated backup methods.

SBI operates these highly automated processes on the most powerful parallel computers using highly scalable databases such as Oracle and Oracle Spatial, and develops infrastructure to the highest standards, both in-house for its own use, as well as for its clients’ implementation purposes.

High availability Spatial Data Infrastructure

SBI operates highly available and scalable Spatial Data Infrastructure (SDI) based on Oracle Database (11.0, 12c), Oracle Spatial and Graph, Oracle Application Express (APEX) and WebLogic Server (i. e. MapViewer), which are hosted on a distributed network of massive parallel computing systems.

SBI has developed its own packages (procedures) for handling ETL processes (Extract, Transform and Load) in a scalable and automated fashion, which ensures the quality of the data stored in the database and that the database is continuously updated. In addition, SBI runs procedures for spatial operations (spatial-temporal intersection), disease-triggering algorithms (PL/SQL procedures), crop-specific, extreme-event adjusted yield prediction models, and phenology detection algorithms, to name a few. These operations enable SBI to provide its clients with cost-effective services.

In order to ensure that non-geotech scientists can access spatial information efficiently, geospatial data is presented via an existing ICT infrastructure, for example an Oracle Application Express (APEX), without the use of any specialized GIS software. This approach maximizes the use of stored data and information by adapting them for visualization and the working processes of users.

SBI’s Spatial Data Infrastructure in a high-speed distributed network ensures that non-geotech scientists can access spatial information efficiently.

SBI’s scientific computing libraries facilitate process automization and thus enable SBI to provide competitive and scalable services with global coverage

Highly scalable scientific computing

The SBI team took up operations at a very early age of geospatial information (mid-80s). Since then SBI has developed its expertise in GIS/GDI/GDM with the aim of integrating spatial data into business processes. Consistent and coherent spatial data which are globally available necessitates highly scalable, parallelized computing systems. Against this backdrop, SBI has established a massive parallel system (up to 240 cores) dedicated to efficient scientific computing. This system uses cross compiled python libraries and R statistical software, which allows for analytical intersection of any kind, dynamically modelled computation, and all types of simulation using spatial data within a short time frame. Moreover, it is highly scalable on demand. This capability allows SBI to run industrially organized processes (e.g. delivery of EO products < 24 h after satellite overpass).

Integrated back-office solutions

Competence in geospatial technologies (GIS, Remote Sensing, GNSS) combined with SBI’s efficient image processing and information service algorithms are what make the company unique in earth observation assisted agricultural monitoring, management, and development.

SBI updates and maintains spatial information continuously and globally in a 25 km by 25 km grid. Several types of spatial information, such as land use, climate, soil, phenology, satellite image information, agrostatistics, crop disease, pest risk, weather, among other components, enable efficient spatial operations (intersection, clustering etc.) for the purpose of deriving information and directives in real time.

SBI’s efficient and interactive ways of communicating with cutting-edge technology in the decision-making process puts clear blue water between the company and its peer competitors. Agronomists at SBI always use spatial information with user-friendly web applications in assisting their customers with their decisions and in providing them with consultancy services.

The preparation of a Biological Assessment Dossier is one click away through SBI’s continuously updated and maintained spatial information and highly automated procedure.

SBI develops Spatial Data Infrastructure (SDI) and back-office solutions which combine earth observation information, agrostatistics, weather and soil data, along with other data, and feature user-friendly interfaces.

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