Photo Sensing Module 2

In Module 2 I learned that the United States Geographical Survey created a Land Use / Land Cover (LU/LC) classification for remote sensor data collection and is used to promote uniformity of feature classifications. 

During lab 2 features of Pascagoula, Mississippi were identified, the features were then evaluated at LU/LC classification level II based on criteria such as, size, shape, color, texture, density and knowledge.  Next the attribute table was updated with the LU/LC code, code name, and then a description was provided.  Finally, a map was created to show Level II Land Use / Land Cover for the area of Pascagoula, Mississippi.  The the map created was compared to Google Earth to compare classification selection accuracy.  The comparison showed that 87% Land Use / Land Cover classification were accurately selected.

Remote Photo Sensing Module 1

In exercise 1, An aerial view of an area was provided and analyzed for different tones and textures. Then the polygon feature class was used to analyze the tones. Then repeated the steps with a point feature class to analyze textures.

In exercise 2, I analyzed different features on the provided .tif file, shadows, shape and size, patterns, and association. I did them by creating a point feature class. For shape and size I chose a building with a flat roof, a road, and a cluster of vehicles because they were easy to recognize by the shape and size. For the shadow feature, I chose a house, a building and the water tower because the shadows were easy to distinguish. For association I chose shoreline, pier, and the forest because they are easily distinguishable items. For the pattern category I chose a parking lot, a row of houses and a shoreline because they are distinguishable on the by its pattern on the map.