Introduction To Arc GIS-Pro and Multi-band UAS Imagery

 Introduction To Arc GIS-Pro and Multi-band UAS Imagery


In order to demonstrate ArcPro's capabilities and our use of multi-band UAS imagery, we were provided with data collected out at Purdue Wildlife Area before and after a controlled burn. 

Metadata:

  • Vehicle: Bramor ppX
  • Sensor: Altum set to 1ms and 16 bit TIFF
  • Flight Number: 2
  • Takeoff Time: 12:18pm
  • Landing Time: 12:35pm
  • Altitude (m): 121
  • Sensor Angle: NADIR
    It's important to collect this information because not always will the pilot be the one that processes the data. So, the metadata is basically mission notes from the pilot. This is useful because the person processing the data will need to know things like the altitude and overlap to create an accurate output.

Arc GIS-Pro:

When you first open the software, you want to open your project; in this case, it's called DoakBurn. You should see a basemap with no UAS layers yet. We are going to cover the data layers by referring to what band each layer covers (Figure 39).

Figure 39: Micasense RedEdge Peak Band Reflectance

Blue Band:

The brightest reflection will be bare soil like the roads. The darkest points are the thick vegetation, like areas surrounding trees. This makes sense because looking at Figure 39, the typical plant reflectance is very low for the blue band.

Green Band:

The bare soil and roads will still have the brightest reflection, but the vegetation will be lighter than the blue band. This makes sense because looking at Figure 39, the typical plant reflectance is higher for the green band than the blue band.

Red Band:

The brightest reflection will be bare soil which is mainly the roads, but there are some light spots in the fields which shows areas of low vegetation. The darkest areas are the healthiest areas of vegetation, mainly the surrounding trees.

Red-Edge Band:

When you turn on the Red-Edge band, something that stands out is that the whole area is a lot more reflective. The areas of healthy vegetation are still slightly darker than the bare areas, but overall much lighter. This makes sense because looking at Figure 39, the typical plant reflectance is much higher for the Red-Edge band. The red band is much darker than the red-edge band. The red-edge is much more reflective. The Red-edge band is much more sensitive to vegetation conditions.

NIR Band:

With the NIR band, the healthy vegetation has a higher reflection, this makes sense because if you look at Figure 39, NIR has the highest typical plant reflection. This means the healthy vegetation will appear slightly darker. 

LWIR Band:

The features that have the brightest reflection are the roads, they are basically glowing. The vegetation areas are much darker and show a major contrast between vegetation and no vegetation. Something that stands out is the resolution is much lower than the other bands. This band is sensing thermal imagery. NIR is typically for reflected infrared and LWIR is typically thermal infrared.


Data Layer Properties:

Now that we've gone through the data layers, it's time to explore the data layer properties. It is important to look over the details/properties before working with it in GIS/remote sensing because accurate and reliable data is vital in order to receive meaningful results. Spatial data quality is dependent on precise and accurate data so you’ll want to check and make sure all your data is correct.

Figure 40: Color Ramp Related to Pixel Reflection 

  • Radiometric Resolution: 16 Bit
  • Projected Coordinate System: WGS 1984 UTM Zone 16N

Band and Band Color Manipulation:

We are going to look at some false color IR imagery. We are going to assign band 5 to the color red, band 3 to the color green, and band 2 to the color blue. Data that was collected before the burn shows a few features that jump, the areas in the field's vegetation show up as pink. However, the extra thick vegetation areas like the tree lines show up as a deep red (Figure 41).

Figure 41: Shows PWA With False Color IR Pre-Burn


When you turn off the pre-burn and turn on the post-burn, several of the plots are now burned and appear a dark brown color. We are also going to convert this data using false-color IR. It can be difficult to turn the layers on and off to compare, a great way to look between two data layers is to use the Swipe tool. If you click on the Appearance tab and use the swipe tool, you can easily look at the pre-burn layer vs. the post-burn layer.

Figure 42: Shows The Swipe Tool In Use

Figure 43: Shows the Swipe Tool In Use


    Scientists often take multiband composite rasters and calculate indices as a way to simplify what the bands display. One of the most popular indices out there is the NDVI, which uses the NIR band as means to display healthy vegetation. Once I turned on the post-burn-NDVI, I changed the color scheme to multipart and inverted it to get a better contrast. This shows the dead areas as bright purple and light vegetation as yellow and thick vegetation as red.

Figure 44: Shows Post-Burn-NDVI With Inverted Color Scheme


We can compare the NDVI imagery with the regular post-burn imagery using the swipe tool.  One major pattern that can be seen between the two is that the burned areas stand out. In the regular post-burn, the areas are shown as they would to the normal eye like black, brown, burnt with the healthy areas in green. In the NDVI, the burnt areas are just straight black with the healthy areas in grey. If you zoom in, there is a section that is a good example of the benefits of NDVI. There is an area that didn't fully burn so in the regular imagery, it looks green, and in the NDVI it looks grey (Figure 46).

Figure 45: Shows The Regular Post-Burn And NDVI Post-Burn


Figure 46: Shows Zoomed In Plot That Didn't Fully Burn


    I decided to create my own band combination and noted what happened to the imagery. I set band 2 to the color red, band 1 to the color green, and band 5 to the color blue. Some features of this combination are that the dead areas appear bright green. This can be seen in the recently burned areas, and in the trees in the top left and right corners. It also shows the difference in vegetation thickness by the shade of purple. The areas of light vegetation are light purple, and the areas of thick vegetation are dark purple.

Figure 47: Shows The Color Band Combination I Generated









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