In this lab, you will be processing drone data acquired on February 07, 2020 at the terraced section of the UGA Botanical Garden. The photos were captured with the DJI Phantom 4 Professional using the DJI Ground Station software running on an iPAD mini; the drone was set to fly at a height of 75 meters above ground level with a sidelap of 80% and an endlap of 80%. The mission resulted in 84 photos.
The You will use the LiDAR toolset in Global Mapper to generate an orthophoto, a bare ground “terrain” model and a “surface” model (includes trees, stumps, buildings, etc).
Pre-processing data management: Data management is a necessity. Sooner or later, you will need to develop a data management strategy – one that allows you to quickly browse your data directory and know what is there and where it was captured. I try to create a project folder with separate subfolders to store the unprocessed drone photos, outputs, and any other existing GIS data.
- Create a working directory on the E:\ Drive called BotGarden_Feb072020. Also create a folder called InputPhotos and another folder called OutputData
- Download lab data (HERE or from the class drive N:\FANR5640_7640\Spring2020\BotGardenTerrace_Feb072020.zip) and copy it over to your working directory. The compressed file size is 706,494MB.
- Unzip your data file. Move photos ‘DJI_0029.JPG’ – ‘DJI_0104.JPG’ to the InputPhotos folder. You can delete the other photos.
Open Global Mapper v21.0
- Set Coordinate System: Tools > Configure > Projection > UTM/Zone17N/NAD83/METERS
- Save your project to your working directory
- File > Save Workspace As…
Convert UAV photos to point cloud using the Pixels to Points tool
- File > Open Data Files load UAV photos
- For context, load a basemap
- File > Download Online Imagery…
- Select World Imagery
- Save your workspace
- Load Pixels-To-Points (PTP) tool (located on the LiDAR toolbar, last icon on the right)
- From the PTP tool
- Input Image Files: right-click > Add Loaded Pictures…
- Point Cloud/Orthoimage/Mesh/Log Output: Save “BG072020_pointcloud” (in GMP Global Mapper format) in your <working directory>\OutputData folder
- Orthoimage: Save “BG072020_ortho” in your OutputData folder
- Reduce Image Size: (use 8 to speed processing for lab) down-samples the original images which decreases processing time
- Analysis Method: means by which matching points are located on UAV photos
- Incremental: The Incremental method starts from two images, and progressively adds more, recalculating the parameters and locations of the points to minimize the error.
- Global: considers the keypoints across all images at the same time.
- This process will take about 12 minutes with the above settings.
Output of Pixels To Points tool
Remove the individual drone photos (shift-select > right-click > remove…)
Save your outputs in a common GIS-ready format:
- Right-click on the layer you want to export from Global Mapper > EXPORT… > select your file type > name your output & hit Apply/OK
- Save your point cloud as a LAS file
- Save your other raster layers as an ERDAS Imagine File
Create surface and terrain models
I reprocesed this data using high settings (resample by 1.2 instead of 8). Download the data (HERE) and lets explore the point cloud…
Explore the Analysis > ‘Create Elevation Grid from 3D Vector/Lidar Data’ tool…
- Grid Method ‘Maximum Value – DSM’ to create a surface model
- Grid Method ‘Minimum Value – DTM’ to create a terrain model
Explore the Analysis > ‘Combine/Compare Terrain Layers’ tool…