Geospatial and EO data analysis

Thanks to the unique composition of the team at mundialis we are able to offer more than a decade of experience in the analysis of massive geodata and Earth observation data. Over the past years we gained notable knowledge in gap-filling and aggregation of daily MODIS Land Surface Temperature time series. This knowledge our team members apply to environmental modelling, especially related to invasive species like the tiger mosquito expansion in Europe and other topics.

Skyview analysis from LiDAR data

Which data processing does mundialis offer?

Analysis of GIS data, preferably open data:

transport networks used for routing and flow analysis
elevation models, merging of heteorogeneous data used for terrain, erosion, flood risk analysis, solar radiation estimation
sensor network data from meteorological stations
cadastral information which are needed for detailed risk assessment of potential property loss in case of hazards
LiDAR data from laserscan flights in order to assess urban morphometry

Analysis of Earth observation data:

Landsat8 – River Rhine – EU-DEM 25m

images from UAV like octocopters in the visible, infrared or thermal spectrum
aerial imagery, from historical aerial data to modern multispectral imagery
satellite data with focus on time series processing used for the extraction of NDVI over time, assessment of urban heat islands, landuse/landcover identification with OBIA and machine learning approaches. We explore Landsat, Sentinel-2, Pleiades, Worldview and other data

For us combining geospatial and Earth observation data is the key!

Our approach of combining geospatial and remote sensing data enables us to not only e.g. identify urban heat islands but to also estimate the number of people being affected. This leads to informed decisions which will be more cost effective and strategically targeting the problem.

Download: mundialis flyer DE (PDF)

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