ArcGIS Earth

 Introduction

By using drones to take images and then geotag those images you can create a mosaic of data gathered over a large area. One of the software that helps with this is ArcGIS Earth, similar to Google Earth but with much more data packed into it. It not only contains satellite images but also has elevations and distances built into the software allowing a pilot to really look into the fine details before a flight. By finding out elevation and distances a pilot can figure out flight time, required battery life, how many missions they will have to run, and a safe operating altitude.

Agriculture

ArcGIS also allows for layers to be added in over the Earth based on data that has been gathered. For example, there are some standard agricultural photos that are taken by aircraft every year in order to track vegetation health. There are two types of layers that can be helpful for those in agriculture asides from the general satellite view. There is a normalized difference vegetation index (NDVI) and thermal. Both kinds of them show the same information but the NDVI gives a greater depth of information to the exact health of the fields. Seen in Figure 1 where the bright orange/red fields are up in the corner and the urban and forest areas are green. Whereas Figure 2 has one of two colors really and it's teal and pink, Pink for any vegetation and teal for urban areas.

Figure 1: NDVI

Figure 2: Thermal

Wildfires

For wildfires, there are a few different layers that can be added to ArcGIS. There is one that is provided by NASA where they use satellites to look for hotspots and track where they are (Figure 3). The other is a live view of current wildfires in the US. This is seen as California is ablaze and that is currently true (Figure 4).

Figure 3: Satellite detected hotspots

Figure 4: Current Wildfires

Accuracy

The software is very accurate. Figure 5 is an RGB photo stitched together taken by the Bramore PPX and Figure 6 is the satellite view that ArcGIS provides. Looking at them side by side it is clear how accurate the software is and how well it can be relied on.

            Figures 5 and 6

Conclusion

ArcGIS is a great software that works on a very accurate scale. By having software that is so accurate one can plan missions to a foot and guarantee the safety of the mission. They can also get an accurate idea of the scale of a mission and how long it will take to complete it.

UAS and the Digital Transformation

 Introduction

As drones are being used more and more within the workforce there becomes more of a demand for them. As more companies realize how useful these platforms are they also require greater data processing requirements and greater autonomy requirements. With cloud computing and IoT, these requirements can be met and exceeded. By sending the Data off the drone via an internet connection to a data processing facility there can be greater turnaround times for almost real-time data processing for use out in the field. By also applying the cloud computing options there is greater accessibility as now that data can be accessed by any approved device connected to the same interface.

By taking machine learning and applying it to all the data that a fleet of drones can collect it will allow an AI to learn and soon make its own decisions based on events. By also incorporating flight controllers and 4G LTE connection the platform can be swarmed and controlled from basically anywhere. This will provide greater data gathering and thus add more to the whole system.

    IoT 

For the internet of things the amount of data coming in is critical. The more data that comes in the more information that the system gains. It has lately been restricted to static sensors but by applying drones to this IoT system those data-gathering sensors now can move and gather more data for the system. The next step after having this single moble data collector is to have more collectors to gather the most data possible via a swarm.

    Cloud Computing

There are many companies looking to take the data processing side and speed it up as quick as possible. One way that they look to combat this is through cloud computing. All that is required is a small computer with an internet connection that can upload the collected data to the cloud. Once in the cloud, the data can be processed and stitched together with other datasets and created a finalized dataset that can be used.

    Big Data

With many drones starting to populate the airspace a big question is how to track them. In one source that was found I discovered a company that wished to use big data processing to gather all the data on drones that were currently in the air, weather, TFRs, and other hazards. Then manage the drone flights based on this. Currently, the hardest part of this process is the data processing and soon it might be made easier with cloud computing.

    AI

By linking all these processes with artificial intelligence it allows that system to start making the decisions for itself without human interaction. Currently the military is able to have a drone autonomously avoid obstacles and plan missions without human interaction. The one drawback of this system is that the drone requires 3D perception and AI capabilities.

Conclusion

As the future cloud-connected cities come into existence a greater need for connectivity will be required, not only to maintain safety but to process all the data and ensure a redundant program.