Comparación de DTM usando Global Mapper 17.0.1

Comparar, primero visualmente y después cuantitativamente dos DTM. Por un lado elegimos una fuente muy usual, SRTM con un DTM derivado de Fotogrametría Stereo.

Read More Comparación de DTM usando Global Mapper 17.0.1

DTM from SRTM? Let’s compare sources using RMSE (Root Mean Square Error) and a gaussian kernell density map

I guess we all can make a DTM out of many sources but SRTM is one of the most common ones, right?. Then let’s learn from this very simple approach how close we are from the SRTM raw data. Selecting a not very big representative area to be able to handle it, exporting raster to polygon (from […]

Read More DTM from SRTM? Let’s compare sources using RMSE (Root Mean Square Error) and a gaussian kernell density map

Using Excel to calculate the RMSE for LiDAR vertical ground control points

(source: http://dominoc925.blogspot.com/) The height accuracy of the collected LiDAR data can be verified by comparing with independently surveyed ground control points on hard, flat, open surfaces. It is essentially just calculating the height differences for all the control points and then determining the height root mean squared error (RMSE) or differences. Most LiDAR processing software have the […]

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