Processing Multi-Spectral UAS imagery For Value Added Data Analysis

Introduction:
Due to the advancement of technology UAS imagery can now be used to do things that could never be done before.  The advancement of camera technology allows for a very accurate assessment of vegetation health to take place.  This lab goes through processing and creating images taken with the MicaSense RedEdge sensor for further data analysis.  Imagery taken with a normal RBG sensor can be manipulated to see vegetation health, this is done by creating a false color infrared image.  The RedEdge sensor has an additional band between the red and near infrared, they call it the RedEdge, this allows for some of the most accurate vegetation health analysis.  In this lab a series of images and maps will be created to show the differences between a normal false color IR and a false color RedEdge. The images were taken at a house in Fall Creek Wisconsin.

Methods:
The first step of the process was to load the images into Pix4D to create an Orthomosaic Geotiff of the study area.  This was done similarly as previous lab with the exception of using the Ag-Multispectral Processing template. The second step was to create a composite image of all the bands together.  This was done in ArcMap by using the Composite Bands Tool.  The resulting image can be viewed with a variety of different band combinations. The final step to creating maps that can be used for value added analysis was to create a permeable/impermeable surface map using ArcGIS Pro.

Results:
The first thing to be noted is that only 69% of the images were calibrated successfully when processing the imagery in Pix4D, this is due to pilot error.  The camera was turned on when the UAS was still climbing to the proper altitude.  This resulted in images that were not successfully tied into the image.  If this was a real world application the site would be flown again to get better data.

The .tif files were then brought into ArcMap and combined together to create a composite image.  The bands can be combined in a number of ways to create a number of different images.  This first map is in RGB and is how we see through our eyes. The band combination for this image is 3,2,1.

The second map uses bands 5,3,2 to create a false color infrared image.  This uses the infrared, red and green bands to show vegetation.  Vegetation in the image show up as red because the IR band reflects off the vegetation at a cellular level.  The darker the red the vegetation is the healthier it is.

The final composite map was created with the RedEdge 

Conclusion:
The RedEdge sensor gives a more detailed analysis of vegetation health by providing an extra band.  From these images a Pervious/Impervious surface map was created.  The map is not perfect but it shows where the house and road are. The shadow on the upper left hand corner of the house is mistakenly labeled as pervious.  This map would have to be fixed to be used in a real world application.