Diurnal Heat Patterns: Research and Training on the m600

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Research
To increase our understanding of our topic, we have set to create an annotated bibliography with scholarly sources pertaining to the topics of diurnal temperature patterns, remote sensing, removal of noise in thermal imagery, and applications of thermal imagery in UAVs (among other topics)

The culmination of our research can be found here

What did we do?
This week is the first week that we got to fly the m600 system. Due to the extensive nature of our data collection procedure, we thought it prudent to have a smaller outing to sort out any problems before we committed to a full day (sunrise to sunset) of data collection. Our main goal was getting trained on the M600 and learning how to use the XT2 thermal sensor. 
After ensuring that the team was capable of flying the m600 we set up a simple mission that captured the buildings and the gravel parking of the Purdue Wildlife Area. In order to fit a flight into a single battery life, we set the overlap of the images to be lower than the recommended 90%.  We flew at 61 meters but plan on flying at a much higher altitude to increase coverage.
We were unable to process the thermal images into an orthomosaic but here are two images comparing the RGB to the thermal images.
Figure 1: Thermal Image
Red is hot, blue is cold
Figure 2: RGB Image
Some interesting things from the images are that the roof is very cold in comparison to the surrounding area. It is likely that the roof is poorly insulated from the inside, and that the white color of the roof reflects most of the thermal energy. Another thing of note is that only one of the AC units is giving off a lot of heat which means that it is likely the only one running.
Challenges
Our inability to process the data may come from the relatively small area coverage. Thermal images require high contrast within the image to find tie points. We hope that increasing our altitude will allow us to capture more data in a single image so that it is easier to find tie points. We are also planning on increasing the amount of overlap in our images to assist in finding tie points. Perhaps a 90-95% overlap is necessary, and that is something that we plan to experiment with in the future.

What next?
Our plan is to plan a flight this week to experiment with different altitudes and overlap percentages to see if that aids in processing our data. We would like to be able to process thermal imagery into a 2D orthomosaic by next week.

Metadata
General
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Location: PWA
Date: 9/7
Vehicle: M600 Pro
Sensor: Sony A6000, FLIR XT2
Battery: blue
Flight Information
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Flight Number: 1
Takeoff Time: 5:35
Landing Time: 5:45
Altitude (m): 61m
Sensor Angle: nadir 
Overlap: 80
Sidelap:80
Weather
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No wind
Clear skies
78 degrees
Crew
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PIC:Luke 
VO: Tim, Jarrett

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