The Masterloop Geo Analytics software can process high volumes of sample points which have an associated position and provide grids and geometric shapes such as polylines and polygons for further visualisation.

A pre-processing feature lets you filter the input data to achieve high performance calculations without losing out on data precision.



Left: The actual data model, where a sensor has sampled 1 million samples along a given path.

Right: Resulting image after processing of 1 million samples. Notice how precise the model is outside of where there is no data.

Output of the process is a regular grid, or contoured data provided in GeoJSON / KML data formats for integration with other GIS tools or tools such as Google Earth, ESRI ArcView, PostGIS, QGIS and more.



Masterloop Geo Analytics supports the following methods when processing irregular datasets:

  • Ordinary/Simple Kriging

  • Moving Average

  • Nearest Neighbour

  • Inverse Distance

  • Polynomial Regression

  • Triangular w/linear interpolation


Advanced point reduction algorithms, which for example can be used for simplifying a track, thus reducing amount of data to be transferred from device to cloud, or reduce requirements for storage and processing.

You can specify maximum error in meters, and the point reduction module will remove all points that are not needed. The algorithm will ensure that the track is lower than the specified error tolerance threshold.