GIS 4035 - Module 4 Lab - Ground Truthing and Accuracy

In this week's assignment we were tasked to "ground truth" our Lab 3 map.   In lieu of "in situ" data collection, we used Google Maps to verify the classification codes we assigned to different areas on the image file in the Lab 3 map.  

1.   First I opened ArcCatalog and created a Truthing point shapefile with the same projection as the TIFF image and LULC shapefile from Lab 3.

2.   Next I opened up a copy of the Lab 3 map and added the Truthing layer and saved the new Lab 4 map.

3.   Next I reviewed the map and used sampling rules of thumb to determine my sampling requirements.

a.     Lab 3 was classified to Level II so sampling the transportation class was probably not important.

b.     Bodies of water and Level II wetlands I assumed were homogenous and decided not to locate samples in these classes.

c.     The large coverage area of residential classification (11) led me to choose the stratified random sampling method since this method is proportional to LULC type.

d.     I placed at least 1 sample in each classification code (except Water, Wetlands, and Transportation, see above).

e.     I added samples proportionately to each classification based on the coverage area size.

4.   I began creating point features in the Truthing shapefile after adding the required fields.

5.   I then added a field for coordinates of each point feature.  Using the Identify tool I recorded the degrees, minutes, and seconds of each point.

6.   Next, I opened Google Maps and began the ground truthing process using the coordinates of each point location.   I took notes in a comment field I had added so I wouldn’t get confused between points.  

7.   As part of this lab I realized that I did not maintain scale or MMU properly in Lab 3.  I tried to keep my scale to 1:10,000 in Data View when randomly locating my sample points.   Likewise, in Google Maps I tried to be aware of the scale in the bottom right before going into Street View.   I think if I had consistently applied MMU and scale in Lab 3 I would have had fewer classifications.   Fewer classifications may have improved my accuracy in Lab 4.

8.     The biggest issue for me in classification was that there were several “mixed use” areas on the map.   For example, while some areas would appear predominately residential my sampling point was on a large commercial building that was “mixed in” within residential.  Seven of the eight misclassified sample points should have been classified as either Residential (11) or Commercial and Services (12). I think this might indicate lax zoning ordinances and poor urban planning.

Ground Truthing of Lab 3 Map Using 30 Stratified Random Sample Points and Google Maps