AT 319 Final Project

    The final project of AT 319 was a culmination of the labs of the course. First we needed to understand mission planning and how to operate a drone safely. Then we need to accurately gather the data and in the right projection. The project also called for the gathering data from ground control points for post processing. After the completing of the data collection the lab required good file management and meta data to maintain organization. Finally, we had to process the data and use the GCP data to correct the data in post processing. Then we were called to perform different types of analysis and represent that in generated maps. The first map generated did not require any analysis and was simply about outputting the processed data. 

The second map generated was to represent the ground control points and the coordinates recorded on or phone in comparison to the coordinates recorded by the ground control points themselves. 

The Third map generated was a comparison between original orthomosic and a hillshaded Digital Surface Model. 

The Fourth map generated was an orthomosic with an additional feature class used to digitize the roads between the fields. 

The Fifth map was generated by classifying the orthomosaic into four classes. 

The Sixth map generated was a DSM that showed all areas above 10m. This was done by using raster functions and the greater than tool to find all the area 10m above the lowest elevation.

For the last part of the lab we were required to generate a map that showed all grass areas that are within 20m of the roads and more than 20m away from the trees above 10m. To accomplish this we created two buffer maps that would be used with the extract by mask tool to find the remaining area of grass. The first buffer map showed all areas that were within 20m of the roads that we ditigitzed.

The second buffer map generated showed 20m around the areas above 10m. 

With these buffer maps we took the classified map and remove all of the classes besides grass. Then we took the first buffer map and used it to extract all the grass areas inside the 20m of the road. That new class was then used with the second buffer map of 20m near trees above 10m to extract the area outside of that range. Then we took that final class of the grass area with both buffers implemented and placed it on top of an orthomosic to provide an overview. 

 

Ground Control Points in the Field

 Previous labs have shown how to use ground control points while performing post-processing but this lab handles actually gathering GCP data in the field. We utilized ESRI Field Maps to create a feature layer over the already provided one. This new feature layer would hold the coordinates recorded on our phone for the ground control points. The feature layer provided had a sketch that provided recommendations for the GCP locations. Then we entered the field and recorded GCP points as precisely as possible in comparison to the sketch layer.   

As you look at the above generated map you can see the difference between sketch and the recorded ground control points. This highlights the importance of accurate ground control points and the ineffectiveness of mobile devices as equipment.