My Introduction to Remote Sensing and Aerial Photo Interpretation

This was the first lab of the first week of my first remote sensing class.  I previously worked in a municipal urban planning office and regularly used aerial imagery to help gain information for site-specific situations.  This section articulated some of what I already knew and had a lot of information that I had not known.  Really useful tips like observing the length of a shadow to understand a feature's height is a simple enough concept that I hadn't thought of before diving into this module's lecture and readings.

For the lab, we were asked to identify varying tone and texture for different areas in one image and identify several features based on different recognition elements.  The first image looks to be a coastal city with considerable residential development as well as natural landscape surrounding an airport.  Being that the picture was taken in 1965, I would imagine this area looks completely different now.  The lab instructions explained to provide uniform polygons, so I went back and reshaped all of the polygons to look similar.  After adding two feature classes and creating the polygons, I had to add a field in the attribute table and turn on the labels to get the descriptions to show.  The darkest areas were the areas with dense vegetation (probably hardwood trees), and the lightest area was an area under development adjacent to the airport (probably some sand reflecting the Sun).  I marked to coarsest area as the residential area near the center of the picture, and finest the calm body of water near the side of the picture.

For the second photo, we were to plot several distinct points that could be identified based on certain recognition elements i.e. association, shadows, shape and size, and context.  This looks like an awesome place to be back in the '70's!  There is a lot of sand over the roadway's and parking lot, so this may be imagery after a coastal storm blew through.  Clues like long shadows and an understanding of coastal areas helped me identify a lot of these features.

Lastly, we compared a true color image and several features at random with a false color infrared image of the same area.  The table below was also provided.