This week our task was to process multi-spectral UAS imagery. The imagery that was provided to us came from a RedEdge sensor. RedEdge allows users to capture imagery in multiple bands within the electromagnetic spectrum. The MicaSense RedEdge Sensor is what was introduced to us in this lab. This sensor captures the imagery in 5 bands; Blue, Green, Red, RedEdge, and Near-Infrared.
Users are able to create different combinations of the bands that represent different types of data that can't be seen by the naked eye. For example, a false color RedEdge combines the green, Near-Infrared, and RedEdge bands to create a Normalized Difference Vegetation Index (NDVI), which can be used to help determine the health of vegetation captured in the imagery.
By presenting the data in various band-combinations, users add value to what's being represented.
Methods
Dr. Hupy once again provided imagery for our lab. In this case, the subject of the imagery is a rural, residential lot, just north of Highway 12 and west of Fall Creek, WI.
What was new to me in this lab was the creation of a composite image. A composite image is an image that includes multiple bands within the electromagnetic spectrum. Once composited, a user can manipulate the combinations of the bands to change the colors and add value to the imagery. By doing so, the user represents value-added data in their presentation of the imagery, to an intentional end.
The imagery was processed in Pix4D and the composite image was made with ArcGIS Pro.
Another task in this lab was to recreate the lab that pertained to adding value by identifying pervious versus impervious area within the imagery.
Once the composite image was made, I experienced difficulty in following the task list within ArcGIS Pro, that was followed in the previous value-added lab. I transferred the imagery to ArcMap, where I was able to find and complete the tasks individually.
Maps
Once complete, I was able to generate 5 maps. RGB, False Color IR, Traditional Color IR, a Composite, and a pervious versus impervious (or permeable versus impermeable) surface map.
It's easy to see that processing imagery in multiple spectral bands allows for increased functionality, and thus, an increase in the potential of the value added to data.
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