AT 319 Week 13 - More Object Based Classification
This weeks lab continues the previous week's work on object based classification. The area of interest in this lab is a county park in West Lafayette, Indiana. I started by working with the larger dataset. The smaller dataset will be involved later. The instructions for the large dataset are as follows:
Engage in object classification of the image where you create a minimum of 8 classes. Examples of classes might include:
Roofs
Concrete
Asphalt
Forest Deciduous (no leaves an brown)
Forest Coniferous (green)
Grass
Bare ground
Run the following two geoprocessing tools to clean up your data:
Add a field and generate a field calculation to determine the square meters of each land cover.
Generate a cartographically correct map of your classes. Include on the map a table showing the square meter coverage of each class (Figure 1).
Now reclassify and create two classes from the ones you have: Permeable and impermeable.
Add a field and calculate the square meters for each of the classes.
Generate another cartographically correct map of your classes. Include on the map a table showing the square meter coverage of each class (Figure 2).
Part 2 involves performing object based classification on a smaller area containing cracks in the pavement. The instructions are as follows:
Use the Crackdetection mosaic and generate 3 classes:
Pavement
Cracks
Vegetation
Run the following two operations to clean up your data:
The majority tool helps to fix problems
The boundary clean tool also helps to clean up the image
Add a field and generate a field calculation to determine the square meters of each land cover.
Generate another cartographically correct map of your classes. Include on the map a table showing the square meter coverage of each class (Figure 3).
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