Getting to Know ArcGIS Pro

Introduction

In this lab, we were introduced to the software, ArcGIS Pro.  Using the tutorial on their website, we were able to create a map of the predicted deforestation in the Amazon Rainforest.  This rainforest spans to nine countries and millions of square kilometers; however, it is currently estimated that only about 80% of the rainforest still remains today.  Through this introductory project, we were able to predict how much deforestation would be caused by a road proposal that would be built across the state if approved. Before we get to that, the questions below provide a good introduction and background that would be beneficial before continuing onto the project:

What makes data geospatial? That is, what makes the data you worked with today geospatial in nature (think coordinates)?

• Data is geospatial when the units of information have geographic data such as forms of coordinates.  It can originate from GPS data, satellite imagery, and geotagging, and it can identify the geographic location of features and boundaries on Earth, such as natural or constructed features.

What makes data in a GIS different than a digital map?

• Data in a GIS is different than a digital map, as GIS is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data.  These types of data contain portions of spatial data along with tabular data known as attribute data, and with this, it can have additional information such as the name of the location, what goods and services are there, and the average number of people visiting that location.  A digital map cannot have these types of data collected with it; rather, it is more traditional with cartographic information.

Why is having an understanding of geospatial concepts and geospatial data so fundamental to working with UAS data?

• It is fundamental to have an understanding of geospatial concepts and data when working with UAS data, as it allows the user to more effectively and efficiently couple and present the data.  The two pairs nicely together and can provide a better overall picture of the project.

What are some of the key geospatial concepts and fundamentals that this lab addresses?

• This lab addresses the basics of how GIS contains the data mentioned above in the maps, as well as the different layers that can exist within a project.  To add to this, the different layers could have their symbology customized in order to make it stand out easier and provide further information on the project.  This then showed how these layers interact with the basemap of the rainforests.

Methods/Lab Assignment

The goal of this lab as mentioned in the introduction was to predict how much deforestation would be caused if the proposed road was to happen.  Not only did we have to predict it, but also present the data in a clear and understandable method for anyone to be able to understand. To effectively do this, multiple layers needed to be added to the basemap in order to communicate this.  Below are the steps taken in order to complete this goal.

First, the map of the Brazilian Rainforest had to be imported as the basemap of the project.  These files were provided to us. Within this basemap, three layers existed on top of it which were the Brazilian states, an outline of the Amazon ecoregion, and the cities in the state of Rondônia. This can be seen below in Figure 1: Basemap with the 3 Layers.

Figure 1: Basemap with the 3 Layers

The basemap was then changed to imagery in order to better see the details in the region.

Second, the road layer was added.  The road layer contains a dense network of roads that cover most of the state.  The layer doesn’t extend past the Amazon Ecoregion boundary. This can be seen in Figure 2: Road Network.

Figure 2: Road Network

Within this layer, it contains data of the present roads.  In Rondônia, there are two main types of roads, official roads that are built by or with the permission of the government, and unofficial roads, built independently of the government.  The official roads connect municipalities and facilitate travel between population centers, whereas unofficial roads access deeper areas of the rainforest and connect rural properties. With the power of Geoprocessing, these two kinds of roads can be separated based on the data attributed to them.  In Figure 3: Official Roads vs. Unofficial Roads, the official roads are the bright blue roads whereas the unofficial roads are still green.

Figure 3: Official Roads vs. Unofficial Roads

Third, the deforestation is explored.  This is done yet again by adding another layer to the map.  Below, in Figure 4: Exploring Deforestation, this can be seen by the light purple area being the affected area.  As seen, there is a strong relationship between roads and deforestation. In fact, the tutorial mentions that 95 percent of the deforestation in the Amazon rainforest occurs within 5.5 kilometers of a road.

Figure 4: Exploring Deforestation

Fourth, the image of the proposed road was added to the map.  This proposed road would connect the two official roads, with cities near both endpoints of the road.  The image added can be seen below in Figure 5: Image of Proposed Road.

Figure 5: Image of Proposed Road

Due to this only being an image, no data is attached to it, nor can be.  Because of this, the proposed road will have to be digitized. This feature uses the image as a reference and then the user has to trace the desired image.  After tracing the image, the proposed road now exists on the map and data can be collected from it. Below in Figure 6: Digitized Proposed Road, the proposed road can be seen connecting the two official roads.

Figure 6: Digitized Proposed Road

The next step involves finding the potential deforestation of the road.  This involves estimating the possibility of land that would become deforested.  As mentioned previously, a large percentage of land that was deforested is 5.5 kilometers from a selection of existing roads.  A buffer tool was used in order to add a layer on top of the proposed road that if it was to happen, the area would become deforested.  This can be seen in Figure 7: Potential Deforestation.

Figure 7: Potential Deforestation

Due to some unofficial roads existing nearby the proposed roads, some deforestation already occurred.  If this area was counted with the new estimate, the number would not be accurate on what would occur. As a result, the existing deforestation needs to be subtracted.  This is done with the Erase tool by subtracting parts of the buffer layer that overlaps with the deforestation layer. This can be seen in Figure 8: Subtracting Deforestation that already occurred. 

Figure 8: Subtracting Deforestation

Now, the area of the potential deforestation can be calculated.  This is done with the Calculate Field pane. The expression was calculated with the area of the buffer (converting from square meters to square kilometers) and then multiplying it by the percent of deforested area that was calculated earlier with the buffer.  This expression can be seen below in Figure 9: Expression of Potential Deforestation.

Figure 9: Expression of Potential Deforestation

According to this analysis, approximately 650 square kilometers would have been deforested if this proposed road happened.  Fortunately, this proposed road did not happen, saving the 650 square kilometers of the rainforest. [Due to slight differences in the digitized road, my value was slightly off by 2 square kilometers from the value mentioned above]

This project is almost complete, however, a visual printout would be beneficial to share.  Due to the map not being exactly centered, it had to be adjusted slightly. This was done with the Layout tool.  This can be seen below in Figure 10: Adjusting the Map for Print out.

Figure 10: Adjusting the Map for Print out

Lastly, since the focus is on Rondônia, the map was adjusted to show this.  To add to that, because most people do not know the location of Rondônia in Brazil, a world map was added to the view.  This can all be seen in Figure 11: Final Presentation

Figure 11: Final Presentation

Conclusions

Summarize how ArcPro as a GIS software. What makes it stand out?

• ArcPro is a GIS software because it uses coordinate systems.  It can capture, store, manipulate, analyze, manage, and present all types of geographical data. ArcPro stands out due to all of the useful analytic tools that can allow for proper data collection such as the measurement of the deforestation that a proposed road can cause.

We talked about all the issues that can come up when working with UAS data in a GIS. After this intro to the software, reflect on how its complexity could create problems with using UAS data.

• One of the more common issues that can come up when working with UAS data in GIS can be the wrong coordinate system used with different data.  If the UAS user does not state the system used, this can cause problems when using the UAS data, as the coordinates will be thrown off.

Speculate how the data you worked with in this tutorial could be supplemented with UAS data

• The data in this tutorial could be supplemented with UAS data to get a more specific and centralized area.  It would have similar results, but images off how the area looks currently could be added in and could lead to a more accurate estimation.