Lab 8

Introduction

In this lab we did quick calculation of an impervious surface area using Arc Pro. I did this following the instructions of this web link. throughout the whole lab we used that website to help show us what to do and learn form it.

Methods

First we downloaded the data set and uploaded it to ArcPro, after doing so it showed us neighborhood in Louisville Figure 1

Figure 1

Next we changed the bands to 4, 1, 3, and Figure 2 and figure 3 was the output of that.

Figure 2

Figure 3

The next step was to draw in highlight areas and assign values and name for them which were in 2 sub classes first was Pervious which consisted of Bare Earth, Water, Shadows, and Grass. The second class was the Impervious subclass, Roof, Driveway, and Road. We assigned each subclass section a color follow instructions of the web page Then we hit RUN and the AI computed what was what. shown in Figure 4

Figure 4

Next we changed the output data set to Classified_Louisville.tif. Following this we merged the data sets and and classified them to be either Pervious or Impervious. Following that we hit run and Figure 5 was the end product.

Figure 5

Following this we made corrections to the data set by highlighting areas that were marked incorrectly and manually changing them form Pervious to Impervious, or the other way around. I did not have any large errors so i moved on the next step. Figure 6 is showing some of the data that the tests gathered

Figure 6

Figure 7

Conclusion

Classifying imagery from data patterns allows the user to quickly tell different objects apart compared to regular imagery. Its a pretty cool tool to use but still had problems missidentifying objects and classifying them wrong, but with more work and manual imputes it'll be a lot more correct.
This tool is useful to show the growth of towns and city's over time, Also useful to show how roads change from construction and might be useful with more of an advanced AI to find man made objects in heavily wooded areas.

Lucas Adam UAS 319