Unsupervised

This is the screenshot of the completed unsupervised lab.

Image Rectification

Image rectification is very useful because it allows the viewer to see actual structures and the lay of the land that is geographically accurate. A great example of this is when the landscape has been changed due to an extreme disaster and first responders need accurate maps to be used from the ground. As useful as image rectification is, there are pitfalls. If the image is out of date and the landscape has changed considerably, it could actually become an impedance. The same applies to images that have been rectified poorly.

Module 2 Lab

Answers to question 1:

Roads: have absorbed more heat and remain warmer through the night
Natural and man-made vegetation: did not retain heat though the night
Sidewalks and patios: have absorbed more heat and remain warmer through the night
Storage sheds in back yards: no internal heat source and heat from sun was not retained overnight
Automobiles: cars that have not been running recently appear dark, cars that have been running recently show hot spots on the engines
Bright spots on many of the roof tops: heat from chimneys or roof vents

SPOT Comparison

The image on the left is multispectral mode and the image on the right is panchromatic. The panchromatic image has finer resolution. It is easier to see individual buildings.

The multispectral mode image has lower resolution, but it is much easier to see differences between land and water.

Problems with the Orthophoto

A couple of the problems I inferred from the photo were:

1. It was difficult to determine what the buildings were used for.
2. I did not know the time and date of the photo, so it may make types of vegetation hard to identify.