Measure Ground Control

Assignment Introduction:

Measure Ground Control is a UAS software that incorporates operations, maps, data, reporting, and camera settings on one application. This helps UAS operators during operations by lowering the amount of time that the pilots need to check operating parameters. Measure also has cloud storage so that flight plans can be accessed from multiple devices. This helps with efficiency because if a flight plan is already flown, new plans won't need to be created. This single source of truth that measure provides ensures that everyone is using the same information when flying missions.

Assignment Methods:

One of the main features of Measure is the integrated maps that shows any flight restrictions within the area. Figure 1 shows an area with the restrictions shown on the map.

Figure 1. Rules and Advisories in the Measure App

Measure also adds easy access to LAANC (Low Altitude Authorization and Notification Capability) which authorizes flights within permitted areas. You must have the AirMap app on the device where you request. This is important to UAS because some commercial operations might need to be flown in airspace where a regular flight isn't permitted. This makes the whole mission planning process much easier.

Measure integrates sensor settings into one app, this helps with mission execution because pilots can access flight parameters in one app. Checklists are an important part of flight safety, Measure can help this process by having all the checklist objects in one app. The settings tab is shown in Figure 2. 

Figure 2. Settings Tab of Measure App

The flight screen on Measure is mainly used for autonomous flight. It has all the information you need for flight monitoring on one screen, this will eliminate the need for the pilots to take their eyes of the flight parameters or switch applications. Figure 3 shows the flight tab.

Figure 3. Flight Plan Tab of Measure

Measure also has a section to create easy flight plans. These flight plans can be reused at a later date, so different pilots can fly the same plan. A certain person can assign pilots to different flight plans, this helps to manage a team of pilots all on the same project. Figure 4 shows a flight plan over a field.

Figure 4. Flight Plan on Measure

The settings on the left-hand side will change the flight path, one of these settings is altitude. Changing this will make sure that you can fly above all the obstacles on the flight plan. Figure 5 shows how the setting affect the mission.

Figure 5. Flight Plan on Measure with Settings Changed. 

Assignment Conclusions:

UAS operations rely heavily on mission planning. The level of detail that goes into mission planning usually dictates how the operation will go. Measure Ground Control app helps mission planning in multiple ways by incorporating maps, sensor data, flight plans. The in-flight tab also allows pilots to see all flight parameters on one screen. The SSot that measure provides is important because it allows for multiple pilots to draw information from the same source with greatly improves safety and efficiency.

Using Arc Collector

Assignment Introduction:

Arc Collector is a GIS tool that is used to collect data in the field. It allows multiple people to contribute to the data collection process. This data can be integrated into any other ArcGIS maps. Some of the uses of this app include ground control points. This can allow for better processing as it relates to UAS data because you know the GPS location on the ground. Figure 1 shows GCPs on the ground.

Figure 1. GCPs Collected on the Ground

Assignment Methods:

For this assignment, I followed this tutorial: https://www.esri.com/arcgis-blog/products/collector/field-mobility/make-your-first-collector-map/

The first step is to prepare the layer, this has to be done on ArcGIS Online before moving it to the Collector app.  Figure 2 shows how to create these fields in ArcGIS. Three different layers were created: paths, places, and areas. After creating the layers, assets are created to represent the types of amenities in the park. These are created and the symbology is changed to represent the object. Figure 3 shows these amenities and their symbols.

Figure 2. Type of Amenity Field

Figure 3. Types of Amenities 

After your objects are created, you can go into Collector and places the objects in the field. Figures 4 and 5 show how this is done.

Figure 4. Adding Dirt Paths in Arc Collector

Figure 5. Adding Picnic Tables in Arc Collector

Assignment Discussion:

Another use of Arc Collector is collecting Ground Control Points, this helps when trying to get more accurate processing as discussed in previous posts. These GCPs could be collected with a phone but should be collected via GPS survey. The following map shows GCPs that I have collected.

This map is only a small glimpse into what can be done with Arc Collector, another way to use it is assessing damage after storms, fallen trees or downed power lines can be marked on the map to come up with different routes.

This map layout is shown in Figure 6.

Figure 6. GCPs of a Proposed Construction Project

Value Added Data Analysis

Assignment Methods:

The first step was extracting the spectral bands, this function on ArcGIS changes the band combination to see the urban features. This band change can be seen in Figure 1.

Figure 1. Band change of Area

Once this is done, you have to better segment the image. To do this, classes were created for the different terrain in the image: Gray Roofs, Roads, Driveways, Bare Earth, Grass, Water, and Shadow. The classified image can be seen in Figure 2.

Figure 2. Different Terrain Types

The next step performed was to merge the classes into two master categories: pervious, and impervious. These two categories represent land cover. After this, errors were found and the image was reclassified to help with the images. This newer image with the classes merged can be seen in Figure 3.

Figure 3. Pervious vs. Impervious Terrain

The final maps, as shown in Figures 4 and 5 below, show the pervious and impervious terrains of an area. The second map shows this area further separated into specific terrains.

Figure 4. Pervious vs. Impervious Terrain

Figure 5. Classification of Terrain

Assignment Conclusions:

The maps shown above are an example of how versatile UAS data is, this particular data set can be used to calculate how much of a certain area is being taken up by houses or roads. This type of spectral analysis could also be used for other industries as well, such as forestry.

Volumetrics with UAS Data

Assignment Introduction:

Volumetrics is a tool used to calculate the volume of a designated area. It is typically used when trying to calculate stockpiles of materials. Do do this type of analysis, you need a few things, the first being a DSM of the area that you're trying to analyze. This DSM may require you to filter out some things that are going to mess with your output value. UAS platforms are very good at collecting volumetric data. Figure 1 Shows an example of a stockpile that could be analyzed.

Figure 1. Example of a stockpile

Assignment Methods:

Pix4D
The methods section of this post will show how to do volumetrics using ArcGIS Pro and Pix4D. Pix4D will be covered first. You must first have already completed a DSM of the area prior to doing volumetrics. Figure 2 shows the volume function on Pix4D, this will allow you to create a boundary around the analysis area, figure 3 shows an example of the total selected area.

Figure 2. Volume Tool Icon in Pix4D

Figure 3. Total Selected Area

After the area is selected, Pix4D will calculate the volume above the plane. The elevation plane can be changed inside Pix4D. The output value will look similar to figure 4. 

Figure 4. Volume Output in Pix4D

ArcGIS Pro

The other way to compute volumetrics is using ArcGIS Pro. This method may take more time but is easier to put into a digestible format for viewers. Similar to Pix4D, you must have a DSM of the area on your map. The first step is to create a clip of the area you want to analyse. Figure 5 shows an example of a clip inside ArcGIS Pro. You need to make sure that the clip has the same coordinate system as your DSM. 

Figure 5. Clip of the Selected Area

The clip is currently just an ordinary polygon, you need to extract whats inside the boundary before continuing. ArcPro GIS has a tool do do this, "Extract by Mask". This tool will allow you to only select whats inside the clip. After performing this feature, you can now calculate your volume. Use the tool "Surface Volume" to do this, again, similar to Pix4D, you can adjust your elevation plane. For sake of comparison, both elevation values used were 292.85 m. After computing the volume, ArcPro should output a text file with all of your values, this should look similar to figure 6. Figure 15 shows a full analysis of wold creek.

Figure 6. Text File Output

Figure 15. Volumetric Analysis of Wolf Creek

Assignment Discussion:

The following table are the results from the volumetrics analysis that was completed in this lab. Figure 7 shows the comparison of methods between Pix4D and ArcGIS using the Wolfcreek Data set. Both methods seem to get roughly the same outcome but Pix4D does take a longer time to process the data.

Figure 7. Comparison of Volumetric Analysis Processes

The next data set that will be discussed is the Litchfield Dredging Operation. The volumetric analysis of this data was completed using ArcGIS. The data set in question is split into 3 different dates with different sampling distances and DSM heights. Figure 8 compares the different dates.

Figure 8. Comparison of Layers

For the data to be more accurate, the DSMs needed to be re-sampled so they had similar properties. There are many re-sampling methods that have advantages and disadvantages but here are some of them:

• Nearest Neighbor - Uses nearest pixel to calculate the output 
• Majority - Uses majority pixel value in the nearest 16 pixels to calculate output
• Bilinear - Uses the distance-weighted value of the four nearest pixels to calculate output
• Cubic - Uses a pixel based on a smooth curve through the 16 nearest pixel to calculate output

The default resampling method is not the best option in terms of the resolution but it might take less time to process. 

After being re-sampled, the next step was to create the clips of the pile areas for each date. This clip creation use the same process as covered in the methods section of this post. Figures 9, 10, 11 show the different areas used for the volume analysis.

Figure 9. Area of Pile on 07/22/18

Figure 10. Area of Pile on 08/27/18

Figure 11. Area of Pile 09/30/18

After the clips were created, the "extract by mask" function was used on all 3 clips as was done in the methods section. The results were then compiled and put into a table. Figure 12 shows the results of the volumetric analysis. Figure 13 shows these results in a single map.

Figure 12. Results of the Volumetric Analysis

Figure 13. Volumetric Analysis of Litchfield Dredging Operation over Time

Another function was also used in this data set, a cut-fill. This process is very qualitative as it shows the gain or loss of a pile. Similar to the volumetric analysis, the common base level needs to be established so that can be the neutral level. The cut-fill operation contains a lot of noise, such as trees or other foliage, so the map must be taken with a grain of salt. Figure 14 shows a map of the cut-fill operation.

Figure 14. Cut-Fill of Litchfield Dredging Operation

Assignment Discussion:

Volumetrics can be a useful tool in UAS as mission can be flown a lot easier than planes or larger rotorcraft. This type of analysis can also be applied to other situations such as trying to calculate the volume of a retention pond to make sure that it can fit all the water. 

Using GCPs to process data in Pix4D

Assignment Introduction:

This assignment is an overview of processing Pix4D data with Ground Control Points (GCPs). GCPs are a marked point on the ground where you know its true location. This point can then be identified in the image in Pix4D to make sure that your data is accurate. GCPs are not to be confused with check points. Check points only show error but do not correct the data like GCPs do. Figure 1 shows a GCP in the imagery.

Figure 1. Ground Control Point Marking

Assignment Methods:

The first step when processing Pix4D Data is to have correct file structure. This should be done by creating separate folders inside your project folder: Collection, Processing, Analysis. Metadata should also be included in the project folder. Figure 2 shows a proper file convention. 

Figure 2. Correct File Convention

Inside the collection folder should be the imagery and your GCP data. Once you import your imagery data into Pix4D, you should complete the initial processing. This should generate a quality report so you can get an idea of how well your data will process. Figure 3 shows an example of how a quality report should look. 

Figure 3. Quality Report

Once this is done, you will need to use the Raycloud Editor, this will allow you to correct the images to your GCPs. Figure 4 shows what the Raycloud Editor should look like.

Figure 4. Raycloud Editor 

Once your GCPs are corrected you can continue with the DSM and orthomosaic processing. Figure 5 will show the final product after correcting the GCPs

Figure 5. Final Product with GCPs

Assignment Conclusions:

This assignment used GCP corrections, this differs from the previous post where the imagery was processed without GCPs. You can see where the map that used GCPs are a lot more accurate than the map that did not. This is because the corrections were not used to ensure that that data is correct. Figure 6 is the map that was processed with GCPs. Figure 7 shows the map that was processed. Figures 8 and 9 compare the two elevation values, note that the GCP value is a lot more accurate.

Figure 6. Processed Image with GCPs

Figure 7. Processed Image without GCPs

Figure 8. Elevation without GCPs

Figure 9. Elevation with GCPs

Getting Started with Living Atlas

Assignment Introduction:

This lab is an introduction to ArcGIS Living Atlas. Living Atlas is an online layer catalog that can be used in making maps or analyzing data. The tutorial followed in this assignment was created by ArcGIS to teach users how to use the program. Figure 1 shows the home screen for the Living Atlas Website.

Figure 1. Living Atlas Website 

One of the layers explored in the tutorials is Soil Moisture 2000-Present. The layers located in the atlas must meet certain requirements set by ArcGIS, such as metadata. Figure 2 shows the soil moisture, which was curated by NASA. Another example of a layer located in the atlas is the National Land Cover Database (NLCD). This layer classifies land cover into different categories. This layer is shown in Figure 3.

Figure 2. Soil Moisture 2000-Present

Figure 3. NLCD of Las Vegas

The Living Atlas can be very useful when combining different layers to convey data. The example used in this tutorial was using ArcGIS to help decide where to allocate resources during hurricanes. To do this, the path of Hurricane Irma was used. Another layer, Nursing Homes, was also added to show which nursing homes were going to be affected by the hurricane. Figure 4 shows this layout showing which nursing homes are in the risk area. 

Figure 4. Nursing Homes in the path of Hurricane Irma

One other good resource is Learn ArcGIS. This online website has many different lessons that can teach the program. Some of the lessons that I found interesting are:

•   Estimate Storage Capacity with Drone Imagery
• This lesson teaches you how to convert drone imagery into elevation layers using Drone2Map, this lesson interests me cause I think that its something practical that i could use. 
• Prepare for Search and Rescue Incidents
• This lesson teaches how to create a boundary map used in SAR operations. This relates to me as I am involved in a search and rescue organization. 
• Create an App
• You can use ArcGIS to create apps which can be utilized to show data more easily, this lesson shows how to create a app from using an online map. this could be useful to show clients data in a unique way.
• Georeference Imagery in ArcGIS Pro
• This lesson shows how you can slightly adjust raster data using photogrammetry which will line up with other GIS data. This is important because you need your data to be accurate before doing anything else. 
• Estimate Solar Power Potential
• This lesson shows a user how to show how much solar radiations the rooftops receive each year. This also seems that it could be very practical, something that could actually be done. 

Assignment Methods:

Another task included in this assignment was to created a map that used at least 5 layers from the Living Atlas. Here is the list of layers used in my map:

• US State Borders
• US Airports 
• US Healthcare Facilities
• US Major Interstates
• US Private Schools

Figure 5 shows the map created, which is select infrastructure in the state of Rhode Island. 

Figure 5. Select infrastructure in Rhode Island 

Assignment Conclusions:

Overall, this assignment showed exactly how useful the Living Atlas can be when creating maps, it can save you the time of having to gather certain information yourself. 

Processing Image Data In Pix4D

Assignment Introduction:

What is Pix4D?  What Products does it generate?

Pix4D is a popular software that is used to generate point clouds from UAS data. It utilizes GCPs and photgrammetry to create point clouds and DSMs.

Why is it so integral to UAS data processing?

Pix4D is so integral in processing UAS data because it produces DSMs from simple pictures, this DSM is the baseline for all other processing.

Assignment Methods:

The first step in processing an image in Pix4D is initial processing of the images. This will report a quality report that is integral in the accuracy of further processing. You perform ONLY the initial processing first because the next two steps (point cloud and orthomosaic) take a long time to process, so if your initial report comes back with bad data, you do not have to waste time processing the next two steps. Figure 1 shows an example of a quality report. Take note of the processing time.

Figure 1. Initial Processing Quality Report

Some of the things the quality report checks for is georeferencing, pixel matching, and camera settings. After confirming your data is correct in the quality report, you can continue with point cloud processing. Figure 2 shows the final point cloud.

Figure 2. Final Point Cloud

When dealing with Pix4D data, the number out outputs can become confusing. That is why it important to have a proper file system. An ideal system would have 3 separate folders for collection, processing, analysis with metadata placed in the master folder. Figure 3 shows an example of this file naming convention. 

Figure 3. Correct File Naming System

After the DSM has been created from the point cloud, the next step was to create a deliverable product that was easy to consume for the customer. This was done by creating a video of the actual DSM itself. To do this, you needed to chose the trajectory point in the DSM, figure 4 shows the video trajectory points that were created. An actual video of the DSM can be found in the figures page of this portfolio. 

Figure 4. Trajectory Points 

The DSM created in this assignment is similar to the one used in Lab #3, the difference is that this DSM did not utilize GCPs. This allowed for not accurate elevation values as shown in figure 5.

Figure 5. Comparison of DSMs with or without GCPs

Assignment Conclusions:

Pix4D is important in processing UAS data because it takes the pictures that are taken by a drone, and processes them into manipulated DSMs and point clouds. this, however, takes alot of time to get accurate results if trying to process a large area, for example, if trying to process a folder of 6000+ images, it could take upwards of 24 hours depending of how accurate you want the DSM.