ArcGIS Earth Intro: Week 9

 The week 10 lab comprised of an introduction into ArcGIS data platform. Essentially, this platform allows UAS users to geo-survey the Earth in a number of different manners. It is somewhat like Google Earth on steroids.

Figure 1: Basemap options on ArcGIS Earth

Imagery hybrid, US topo maps, Imagery, USGS nat’l maps, nat’l geographic are the options within the Basemap toolbar. 
Figure 2: Basemap Interactive Analysis on ArcGIS Earth

Elevation profile, line of sight, view shed are the options you have within the Interactive Analysis option. Interactive Analysis allows you to survey different data that a conventional maps could not provide.
Figure 3: Profile Line view on Interactive Analysis

Figure 4: Profile Line Elevation Profile

Elevation Profile allows you to measure the changes in terrain altitude over a selected area. For example, the elevation changes pictured above are over a selected length of the Wabash River near the Purdue campus. This is helpful because you can safely plan missions based on the given altitude of the area of operations. Depending on the craft, you could use the elevation to your advantage when taking off, landing, and capturing imagery and data.

Viewshed and Line of Sight are also tools in the Basemap Interactive toolbar. These
helpful because when dealing with drastic or even minimal terrain changes these tools allow the flight crew and PIC to visualize their line of sight during a mission, helping them know if they would be able to see the drone or not during flights.


Figure 5: Add data tool within toolbar

This tool when navigated to brings up personally created map filters or it can access ArcGIS Online brings up a variety of user created map filters and tools.



Figure 6: Add Data ArcGIS Online

Figure 7: Add Data My Content Tab
Within the ArcGIS Online page, searching USA NAIP Imagery Natural Color brings up a map that uses colors to differentiate different characteristics on a map. There are large areas of green (most likely forests and prairie fields) and red areas are probably dried out crop fields. There are large areas of green (most likely forests and prairie fields) and red areas are probably dried out crop fields. Based off the color disparities, you can see differences in topographic heat sensors and vegetation.

Figure 8: USA NAIP NVDI (Normalized Vegetation Difference Index)

USA NAIP Imagery: Color Infrared measures vegetation health, the brighter the red color the better the vegetation, where as blue colors have very little to no vegetation visible. The map below is of the same area but with a different filter applied. Manmade structures are now more visible with this applied filter.

Figure 9: USA NAIP: Color Infrared

NASA Moderate Resolution Imaging Spectroradiometer, or MODIS for the application used in this lab was to monitor fire activity across the globe.
Figure 10: NASA MODIS Fire Activity in the US

The red areas on the map are locations of wildfires within the US. This tool is helpful for many environmental scientists, hikers, pilots, residents of nearby areas etc.

Another useful tool to measure wildfires is the US Wildfire activity web map. Below is a picture of California with this filter applied. The small areas of red are exact areas where wildfires are in California.
Figure 11: US Wildfire Activity Web Map

By adding Martell_ThermalIR and Martell_RGB in the Add Data search bar, you can see the difference between the density of vegetation. The darker the color on the map the cooler that area is, thus that area is more dense with vegetation.
Figure 12: Martell_ThermalIR and Martell_RGB

Assessment:

In this lab we dove deeper into the different feature of ArcGIS Earth. We used interactive analysis (elevation profile, line of sight, viewshed) to help understand differing elevations and the predicted viewpoint a PIC would have on the ground. Also, we started to add data that could help us better understand thermal readings, vegetation, and wildfires within given areas. Most importantly, we added data relevant to current flight at the Martell forest with new thermal readings and a detailed aerial picture.











Comments

Post a Comment

Popular posts from this blog

Defining More Features and Buffers

Image
 Features can also be defined measured with other forms of tools and highlighted with buffers. The pairwise buffer tool is helpful in creating zoning areas that can be visually appreciated. Below is a map that has highlighted roads of a flight area at Purdue Wildlife Area. The roads were manually configured using the draw polygon tool. That way, all roads can be accounted for with no error. The roads are still grass features, so the classification wizard querying did earlier would not be accurate, whereas the map above is. Now, I added a 20m buffer from all roads highlighted on the map. This gives you a visualization of the land that is further than 20 meters from all roads. Due, to the road grid pattern being tight, the amount of land is quite small. The buffer feature can also be used for other features. As seen below, I have put a buffer around mostly trees, but in total, all objects that exceed 10 meters in height. Another form of analysis can be found when the same buffers abo...
Read more

Pix4D Processing and Map Making with Ground Control Points

Image
 The usage of ground control points (GCPs) can be extremely useful when processing data and creating orthomosaic images of an area flown for data analysis. Below I have two instances of processing using GCPs, both of the Purdue Wildlife Area (PWA), and both used for independent and various analyses.  Once in Pix4D, the GCP data collected is set into a file location, and on a spreadsheet, the various figures collected from the GCP during the flight are brought and inserted into Pix4D to begin processing. Initial processing then is selected and let run completely. Make sure correct projection and GCP locations are used before processing is started. Processing varies in time length, but after completion a post processing evaluation should be done.  Next initial processing should be unselected and the next two steps should be run, that being point cloud mesh and lastly the creation of a DSM and orthomosaic model. Once processing is done, locate each GCP location and make sure...
Read more