In Module 5 we learned to calculate the relationship between wavelength and frequency, and to calculate the energy based on the wavelength. The basic principle is that the shorter the wavelength the greater the energy of the particle.
Then we were introduced to ERDAS IMAGINE software, and learned some of its basic utilities, including how to save your work without the software crashing.
Last part of the exercise was to use ERDAS software to select an area of a larger project area, calculate land area of each feature in it, and export it. Calculating land area involved editing the attribute table and adding another column. Then we imported the file into ArcMap, and created a usable map out of it.
In lab 4 we did ground truthing. This involves checking and comparing the land use that we determined in Lab 3 to the actual land usage. This is done in a number of ways, but with the limitation we had (such as this being an online course) we used Google Maps. For most features in the mapped area street view was sufficient to determine the actual land usage. Some areas not adjacent to the road required zooming in really close and using associated features to determine actual land usage.
The points that were ground truthed were chosen randomly, though there are other, more methodical ways to select points for ground truthing.
This week's assignment was to identify general land use and land cover types from an aerial photo. I used the skills learned from Lab 2, and identify land features mostly based on tone and, more importantly, texture. Combined with recognizing features by size and association, I could narrow down and label trailer park, grocery stores, and small commercial buildings.
Module 2 lab focused on basics of visual interpretation of aerial photos. In the first exercise we identified different tones, or shades, of surface features. We also identified varying ground textures. These varied from very fine, smooth water surface, all the way to very coarse thick forest. Once the tones and textures were identified we had to outline them using ArcMap.
In the second exercise we had to identify surface features on an aerial photo based on shape and size, pattern, shadow, and association. Size and shape was useful for recognizing houses, cars, and roads. Shadow was useful for tall features, such as trees and a water tower. Pattern was very useful for identifying waves on the water, parking stripes in the parking lot, and a neighborhood with houses along a street. Last was association. A swimming pool, black rectangle of water in a neighborhood, and a pier, thin, long structure jutting out into the water. As in the first exercise, we used ArcMap to mark and label the features.
