We process and analyze aerial and satellite images.
Aerial and satellite remote sensing imagery contains a multitude of geometric, physical, biological and social information. We identify the added value of geoinformation (objects, areas, units etc.) that you need. This also counts for its spatial and temporal relationships. Depending on the specific task, we offer geoinformation with different degrees of automation using other types of spatial and ancillary data and different GeoIT techniques.
Classification: We classify data, i.e. we subdivide the remote sensing imagery into useful segments.
Photogrammetry: We use remote sensing imagery, taken from different perspectives, to generate 3D data based on the principle of human spatial vision.
Data science: We combine geoinformation to create new geoinformation.
Cartography: We produce cartographic geoinformation products.
We use photogrammetry for 3D mapping.
By using photogrammetry, we evaluate remote sensing data three-dimensionally. This includes the derivation of digital terrain and surface models (DTM, DSM). This also includes the recording of the shape, size and position of objects in space.
We survey objects by means of stereoscopic aerial image analysis. For this purpose, we produce orthophotos that overlap up to 80% in order to best reduce visible dead areas and tilt effects. Using aerotriangulation, we achieve precise orientation and fitting into the coordinate system as well as linking of the aerial image material. The coordinates are determined via an iterative adjustment calculation. Position data by GPS (Global Positioning System) or INS (Inertial Navigation System) are integrated.
For 3D mapping on the screen, shutter glasses are used. Their function describes a high-frequency alternating eye squint. This enables the stereoscopic view.
We use this method to map 3D objects according to highly complex specifications, for example, in the creation of the German Amtliche Basiskarte (ABK) or for data acquisition according to the extensive VESTRA technical data scheme of the road authorities. For the VESTRA technical data scheme (code list, point and line signatures), the OKSTRA catalog (object catalog for roads and traffic) is the basis, according to which we usually record around 200 different line and point object classes.
We operate Soil Movement monitoring using radar interferometry (DInSAR) and other complementary data sets.
DInSAR (Differential Interferometric Synthetic Aperture Radar) is a satellite-based technology used to detect ground and infrastructure displacements over time. EFTAS' InSAR technology is developed on a customer-specific, tailor-made basis. Fusion with other sensor data is key here. This results in proprietary solutions and algorithms that generate InSAR information and results of the highest possible quality for our customers.
EFTAS specializes in innovation and continuous improvement of InSAR processing technology to address challenging situations and use cases in demanding terrain. The core methods are already Advanced DInSAR techniques (A-DInSAR) such as PSI (persistent scatterers interferometry) and SBAS (small baseline subset), which are further refined analyzed by means of the mentioned data fusion of different FE and in-situ sensors.
We will continue to invest in research and development to improve our technology, measurement accuracy and reliability for our customers.
We harmonize multiple data sources e.g. for geostatistical data analysis.
Geoinformation is not just geoinformation. You know it from day-to-day use of IT. There are various formats, protocols and other interfaces that often do not harmonise across systems. With geoinformation, this is often exacerbated by the spatial reference of the data within different map projection systems.
We prepare the information in such a way that it meets the requirements. We convert and transform the data. We harmonise and migrate entire geoinformation databases. We have a comprehensive knowledge of all standards and de-facto standards such as OGC (Open Geospatial Consortium) and ISO. We work in accordance with the legal requirements arising from the EU INSPIRE (INfrastructure for SPatial InfoRmation in Europe) directive.
Harmonized data are important in geostatistics, for example. This is the specialist discipline of statistics in which spatial data in particular are analyzed. We set up processes to integrate remote sensing, on-site surveys or other data into spatial statistical data analyses. Social media and smart devices are also integrated if required.
We realize AI-assisted and cloud-based Big Data analyses.
The increasing availability and volume of remote sensing data, in combination with new software and hardware technologies, has led to a steady shift of evaluation algorithms to cloud-based systems and thus close to data storage.
Cloud-based platforms such as Mundi, ONDA, Sobloo, CreoDias, and Wekeo are standardizing data access. These platforms are referred to as DIAS (Data and Information Access Services). CODE-DE is a national cloud platform that provides access to Sentinel data archives and Copernicus land data. In addition to these platforms, other private initiatives are available that enable cloud computing services in the GeoIT environment and provide access to data archives. These include Amazon (AWS), Google Earth Engine, and Euro Data Cube.
In order to perform cloud-based analysis, we implement analysis processes modularly in so-called containers based on technical solutions such as Docker, Kubernetes and Argo Workflow. These technologies are supported by the DIAS platforms as well as CODE-DE.
In particular, our machine learning methods are usually orchestrated in this way. In addition to classical supervised learning methods such as Support Vector Machines and Random Forest methods, we increasingly create and use artificial neural networks. For example, according to the Long-Short-Term-Memory (LSTM) architecture via so-called feedback networks for processing sequential data. Temporal dependencies in the classification of arable crops and agricultural grassland are thus well captured.
We map on site.
Remote sensing can cover a large number of tasks. On-site mapping by field staff will continue to remain important for the collection of in-situ reference data in order to calibrate, verify and validate mapping and monitoring results from remote sensing data, as well as for the enhancement of geoinformation with detailed knowledge as well as the fulfilment of legal requirements.
Field observations – complementary to remote sensing – are among our core areas of expertise. Our field staff use cutting-edge positioning and communication technologies and mobile GIS solutions to collect ground data. We harness the services of a proven Europe-wide network of experienced freelance surveyors and business partners. We offer consulting, planning and implementation – all fast and reliable.
