Value Added Data Analysis with ArcGIS Pro

Introduction

         The purpose of this lab is to determine which parts of the ground are pervious and which are impervious using an online tutorial provided by ESRI that uses ArcGIS Pro. Throughout the activity images will be put into land-use types, comparing man made structures such as buildings and roads to natural surfaces including water or vegetation. The data used in this exercise is provided from the local government of Louisville, Kentucky. The map provided is a small neighborhood near Louisville and the map has 6 inch resolution. In this lab some steps will be laid out that were used to complete the tutorial along with screenshots that illustrate what was being done. Going into this lab it is important to understand what pervious and impervious means. Pervious means that it is permeable, or that water has the ability to pass through. In contrast impervious means that it is not permeable, or that water can not pass through it.

Methods

Lesson 1

        The first step is extract the bands from the raster, the goal here is to end up with three bands. The three bands being extracted are ones that are used to differentiate between impervious and pervious. Those bands are the red which is band 1, blue which is band three and near infrared which is band four. The red band shows man made objects and vegetation, the blue band shows water and the near infrared band also emphasis vegetation.

Figure 1

       
            Figure 1 above shows the map after the three bands discussed about were extracted and the parcels layer was turned off. Figure 2 below shows the initial set up, though the combination shown is bands 1, 2, and 3 rather than the 4, 3, 1 that was used.

Figure 2

           The next task in this lesson was to segment the image. Segmenting the image groups adjacent pixels with similar spectral characteristics in an effort to make the image more generalized and easy to define. The spectral detail can be set on a scale of 1 to 20, since the goal of this lab is to differentiate between impervious and pervious surfaces a low value of 2 to 8 was selected. Changing the default values means that there will be fewer segments created. Figure 4 shows what the output from this step looked like. The houses and roads show up a much more prominent blue than in figure 1. Figure 3 to the lower left shows the layers that are now available for use on the system. This lesson focused on extracting bands in order to be able to tell the difference between impervious and pervious land and it helped to clearly tell the differences in land use.

Figure 3

Figure 4

Lesson 2

Figure 5

          Lesson 2 of 3 in the online tutorial focuses on classifying the segments of the imagery. First the image will be classified into broad land use types and then finally the land use types will be classified as pervious or impervious surfaces. The first step was to classify the different types of land uses by inserting polygons in areas that represent the land cover in the imagery. This work was done mainly in ArcMap and there was a total of 7 different major types on land use identified as depicted by figure 7 below.

Figure 6

Figure 7

         Figure 7 to the right is the illustration that goes with figure 6. Each of the different types of land uses are very prominent and clearly visible. Thought this rough classification is not always completely correct it is what is used to figure out how much landowners will pay in regards to storm water fees. In figure 7 there is 7 land use types, the end goal is to get them into 2 land use types as shown in figure 9. To do this the reclassify tool was used and the impervious surfaces received a 0, while the pervious surfaces received a 1. Figure 9 shows a clear representation of whether or not the areas are Impervious or not impervious. The pink represents the roads, driveways and roofs, and the brown shows the bare earth, grass and shadows.

Figure 9

Figure 8

                   

                                                                                                                     Lesson 3

Figure 10

         In the third and final lesson the accuracy of the classifications in lesson two will be assessed by comparing it with the original image that was given. After it was determined that the data was accurate enough, there will be a calculated area of the impervious surface. The accuracy points are shown below in figure 12, they are 100 randomly generated accuracy points that are used to ensure the right type of land use is being identified. This was done using the create accuracy assessment points tool. The first ten points were gone through individually to make sure they are on what they say they are. Once the process was understood a master copy was available for use from ESRI in order to save time.

Figure 11

 

Figure 12

       Next came computing a confusion matrix that is shown to the left. To do this the confusion matrix tool was used and there is only an input and output available, the input was the Accuracy_Points and the output was placed in the Neighborhood_Data geodatabase and named Confusion_Matrix. The number in the bottom right corner of the table means that the data had a Kappa value of .92 that is the overall classification accuracy. A Kappa value of 85 to 90 should be re run because the data may not be accurate enough.















Results

          Figure 13 and figure 14 are two different maps that were derived from the aerial imagery that was processed using ArcGIS Pro. Figure 13 shows one of the end displays that shows what areas are impervious, as depicted by the brown and what areas are pervious, as depicted by the neon green. When looking at this alone a viewer would be able to tell that the area is a suburb. The lake is slightly unclear in figure 13, though it stands out really well in figure 14. Figure 13 is a good add on map to use with with other illustrations to help people to understand what areas absorb water and what areas do not.

Figure 13

   
          Figure 14 below clearly illustrates the differences in land use, this is done to give the viewer an opportunity to see what structures are in what places in relation to figure 13. Figure 14 clearly shows the lake in the center of the housing area. Then, breaking up the map into quadrants, there is an almost even distribution of structures or vegetation and each quadrant has a bit of water in it. There are a few large shadows denoted, that most likely are coming from trees. This is a good map to couple with figure 13 because the viewer will clearly be able to tell what is pervious and what is impervious.

Figure 14

Conclusion

         In closing, this lab was very informative and a really good beginning tutorial on how to use ArcGIS Pro. Aerial imgagery is very effective in finding out what areas are impervious and pervious to water. This was an important lab because what was done could be done by any city or government in an effort to better determine storm water bills. ArcGIS Pro online was much faster than expected and it looks to have a promising future in the geography field.


Sources

https://learn.arcgis.com/en/gallery/

https://learn.arcgis.com/en/projects/calculate-impervious-surfaces-from-spectral-imagery/

https://learn.arcgis.com/en/projects/calculate-impervious-surfaces-from-spectral-imagery/lessons/segment-the-imagery.htm