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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GIS+Architectural scenaries. Awesome!

Even from scratch or from dgn/dxf vectorial format’s contour lines you create your own scenario. Then import your model previously created using Sketch-up (this time i used google’s 3d warehouse, thank you Dilbert). Stamp your house using sketch-up sandbox tools. Then fur your scenario as if it was grass… A little of photoshop like clouds and […]

Read More GIS+Architectural scenaries. Awesome!