Lab 4

 Introduction Questions Part 1 

What is the Ortho Mapping Suite in ArcPro? How does it relate to UAS imagery?

The Ortho Mapping Suite in Arc Pro is a program that enables you to to modify images to create orthomosaic imagery. This relates to UAS imagery by providing different options for modifying remote sensing data. 

What is Bundle Block Adjustment?

The Bundle Block Adjustment is a tool that  uses an existing surface such as a high resolution DEM,  to create an orthomosaic. However, although the processing time goes down significantly, the accuracy of an orthomosaic with Bundle Block Adjustment is only as good as the data that goes in. For example, if you are using a coarse DEM as your elevation surface, you will get what you ‘pay for’ in terms of data quality. 

What is the advantage of using this method? Is it perfect?

As stated in the last answer, the advantage of using this method is it can reduce the time it takes to process data. Because it saves time, the accuracy from the data you collect doesn't accommodate a Z axis well.

Please define the following terms/concepts:

•  Photogrammetery- Taking reliable images and meshing them together to create items such as maps, GIS layers, and 3D models.
•  Tools and capabilities of the ESRI ArcPro Ortho Mapping suite
•  Orthorectification-the process of removing the effects of image perspective (tilt) and relief (terrain) effects in order to create a planimetrically correct image.
• What Orthorectification accomplishes-corrects for geometric distorted remote sensed imagery
• Types of distortion affecting remotely sensed imagery
• geometric distortion- a deviation from a rectilinear projection
• tangential scale distortion
• relief displacement-(most pronlemetics to objects directly below a camera) offours when objects appear to lean away from the center of a photo
• haze distortion-a measuring error from the GPS
• Bundle Block Adjustment-are photogrammetric methods that adjust images based on editing overlaps, with reference to GPS and triangulation. 

Part 2 Methods

What key characteristics should go into folder and file naming conventions?

Characteristics such as having folder names run general to specific, along with specifying files in accordance to your preference are ideal methods of  organization. In addition, characteristics such as the date, project name and file type are important characteristics as well.

Why is file management so key in working with UAS data?

File management is key with working with UAS data, because if you do not manage your files correctly, sensitive information could be lost, unorganized files could result in poor data analysis, and you could lose overall time as a consequence of the mismanagement.

What key forms of metadata should be associated with every UAS mission?

Key forms of metadata include but are not limited to, the date of the flight, the pilot of the flight, the UAS platform, the sensor of the UAS, the altitude flown, the imaging angle, the ground control GPS, the ground control coordinates, and the UAS coordinates. Create a table that provides the key metadata for the data you are working with.

Figure 1: Metadata for every UAS mission

Part 3 Results

Describe you maps in detail. Discuss their quality, and where you see issues in the maps.

Are there areas on the map where the data quality is poor or missing?

Figure 1: Flight path with Orthomosaic

Figure 2: Flight Path without Orthomosaic

Processing time is time and money in the UAS world. Here you want to create a table that shows the time it took.

Figure 3: Data Processing Time

How much time did it take to process the data?

It took approximately 47 minuets to Process the data 

Part 4 Conclusions

Summarize the Orthomosaic Tool.
The on click Orthomosaic I uses a combination of geolocation and metadata to quickly create a bigger 3D imiage.

Summarize the process in terms of time invested and quality of output.
Depending on the mission and needs of the client, this process can be ideal to those who want a fast processing time at an affordable price.

Think of what was discussed with this orthomosaic in terms of accuracy. How might a higher resolution DTM (from LiDAR) make this more accurate? 
Given the fact that LiDAR penetrates to the surface, a higher resolution DTM orthomosaic has a greater potential to be more accurate. On the other hand, a photogrametric DSM without LiDAR wouldn't be able to penetrate to the surface resulting in less accurate data.

Why might this approach not work in a dynamic environment such as a mine?
Although I believe this approach could conceptually work, I think it would be ideal for a business stand point because mass amounts of new data would have to be saved, stored and constantly collected assuming that the mine is changing.