Learning ArcGIS Online

Introduction

This project was undertaken as a way to learn how the program ArcGIS worked to better get to know the program. As the tutorial that was chosen to follow was based on the online version ArcGIS online was the one used. In this particular example, it was used to determine evacuation routes around Houston, TX before a hurricane.

Method

As the tutorial held the user's hand for the project it was pretty straight forward and walked the user through all the steps in order to have a developed map with all the features needed to asses where to focus resources. First, it took the routes which are published by the federal government and had them be overlayed onto the map. Second, it had the user look for Bayous, seen in Figure 1, which has a tendency to flood quickly during a hurricane.

Figure 1

After the Bayous were identified the next thing to see is the percent of households without a car. This is also important because those families will be needing extra assistance to be evacuated. This was obtained using census data collected by the government and then overlayed over the map once the desired subject (percentage of households without a vehicle) was selected. On the full map view, the dark blue parts are where the highest percentage of these families are and where most of the families are at risk seen in Figure 2

Figure 2

Discussion/ Results

This program can be a little tricky, by following the tutorial it allowed the user to not get confused by the complicated procedures that the program requires in order for data to be displayed properly. This program can be used to plan and design many different scenarios. Using all the data that was displayed after following the tutorial it is possible to plan an evacuation if needed.

Conclusion

As one uses this program it becomes apparent that it doesn't have a great user interface which can make using the program difficult as many things are not intuitive. Once the user follows the tutorial and gets a good understanding of the program it is possible to do all sorts of interesting comparisons and data analysis. 

Thermal Insulation

Introduction

When using an IR sensor it can be important to see what different types of insulation can do to affect the heat transfer to and from objects. In this lab, 4 plastic aircraft were put into 4 separate bags with different ways to insulate. One was placed in a bag with no air, another with air, the third was taken from a refrigerator and placed into a bag with air and the fourth was wrapped into a cloth. With these 4 types of insulation and the IR sensor, it is possible to view the effectiveness of each insulation choice.

Methods

First, the two pictured are the plain aircraft and the one that has been in the fridge. You can tell that number 2 in figure 1 is from the fridge because it was darker than 1 and they both hit the water at relatively the same time.

Figure 1

In figure 2 all 4 bags are in. 1 and 2 are the same as before but 3 is the airless bag and 4 is clearly the cloth bag. 

Figure 2

As the bags have sat in the sous vide bath they got paler on the IR sensor, meaning that they started absorbing heat from the water bath. the only plane that remains dark is 4. The other three are all about the same shade now seen in figure 3

Figure 3

Discussion/Results

As seen in the figures different types of insulations work for different amounts of time. The cloth worked the best for the longest, keeping the plane the coolest. This can be useful especially when using an IR camera.

Conclusion

When using an IR sensor it is important to keep in mind how insulation will affect the readings. If a flight is to take place in the morning before the heat of the day, some things will look different based on how they are insulated against heat.

Using an infrared camera

Introduction

Using a forward-looking infrared camera (FLIR) a series of images were taken in both standard visible light and in infrared (IR). This was to demonstrate the properties of an IR camera and to demonstrate some of the advantages and drawbacks of using an IR camera. In lab 2 IR sensors were used, one handheld device that was easy to walk around with, the other was a DJI Zenmuse XT2 on a DJI M600, the M600 was only used as a stable platform over a sous vide cooker (figure 1).

Figure 1

Methods

IR cameras allow for some interesting effects to be seen that otherwise wouldn’t have been. For example, seen in figure 2, there is a cold can of soda and a mug that is filled with boiling water. The water appears bright white on the camera indicating that it is the hottest thing that the camera is detecting. After lifting up the mug one can see that some of the heat was transferred to the table and made a bright white ring where the mug was previously (figure 3).

Figure 2

Figure 3

The next thing that the handheld IR sensor was used on was the air condition vent in the ceiling. The vent was outputting cold air which made the surrounding ceiling tiles appear orange and warmer. The image filter on the color purple/magenta indicates the cold surface that is being cooled by the air.

Figure 4, a filter was applied to color the image but the sensor still worked the same

A thermal camera can also be used to see hot exhaust out of a jet engine. It can see hot spots on  devices that are in use seen in figure 5 and 6

Figure 5, Hot jet exhaust

Figure 6, The FLIR camera generates a lot of heat

Discussion/ Results

An IR sensor can be very helpful in identifying heat or lack of in specific areas. This can be helpful where just visual light won’t help. Although IR seems to be very beneficial it does have some drawbacks. On surfaces that reflect light easily, there can be some issues, for example, a tree's leaves can appear black or white depending on the angle they are, which can make combing an area for specific heat values and signatures difficult with an unmanned platform. Another feature that can make IR sensors difficult to use is the fact that they cannot “see” through the glass. If one were to point an IR sensor at glass there wouldn’t be any heat signatures behind it. Glass can act as a mirror in this situation and reflect back heat that is behind the camera though, seen in Figures 7 and 8. Figure 7 is a normal camera view, while figure 8 is an IR view with an RGB overlay, seen in the outline of the student on the other side of the glass

Figure 8, the thermal view reflecting from behind the camera
The outline is the student behind the glass

Figure 7, a student standing behind a glass window

Conclusion

IR sensors are very helpful in many situations but they do have drawbacks. As they don’t typically include an RGB sensor distinguishing objects from one another solely based on the heat signatures given off can be difficult. Due to the difficulty of seeing through the glass and how plants can affect readings, there can be some difficulties in using IR sensors but as long as those are kept in mind when looking in at the data and if possible couple the IR sensor with an RGB sensor then the few drawbacks that are present can be mitigated.