A few more lines for leting you know again that i passed this other course just now in Instituto Geográfico of Spain (IGN). Remote Sensing, Photogrammetry, Lidar and Landuse, a comprehensive 40h update on relevant information i need tu use on a daily basis. This ‘update’ helps me to better understand what i am working with andContinue reading “Remote Sensing, Photogrammetry, Lidar and Landuse IGN Spain”
Category Archives: lidar
HTML High resolution DTM visualization using QGIS
This QGIS Plugin, Qgis2threejs, exports terrain data, map canvas image and vector data to your web browser!! All you have to do is opening the DTM in QGIS (2.4.0 Chugiak), go to plugins library and install Qgis2threejs. Once its installed you will see this icon on screen and you will need to clic on it. ThenContinue reading “HTML High resolution DTM visualization using QGIS”
RSME comparing LIDAR data with a third party’s 3D dataset
I would like to share with you an easy analysis i have been working in the last days. I had a vector dataset of buildings and i knew how high they were (there was a field called ‘AGL’ or Above Ground Level) and a LIDAR 2m resolution dataset over the city of London. My aimContinue reading “RSME comparing LIDAR data with a third party’s 3D dataset”
Airmap: UAV aerial surveying technology
The most efficient way to monitor our environment is from above. Traditionally, aerial photography and mapping is a costly and time consuming business. However, by using our UAV technology, we are able to offer a cost and time effective solution for your aerial photography and mapping needs. Obtaining high resolution Orthorectified image mosaics and DigitalContinue reading “Airmap: UAV aerial surveying technology”
Visualizing LAS LIDAR data with sketch-up
While trying to figure out the way to get a 3D model from raw Lidar data, I first opened my LAS file in Global Mapper, exported it to DXF, imported then into Sketch-up and after recording a few scenes, I saved the animation… this is it!. Alberto
Using Excel to calculate the RMSE for LiDAR vertical ground control points
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 reporting function built-in. However, plain Microsoft Excel can also do the job (except for extracting the elevation from the LiDAR data).
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