As I had learned in our second lab, when using GIS data there can be misalignments and errors in the display of the information. As a result of more accurate methods of surveying the landscape we have older data that is not adjusted to these newer models. Often times when constructing maps we need to take data from a variety of sources and in doing so some of the data will not be in the same projection. This is where we start to see some data which becomes misaligned or improperly referenced. To fix the issue we must go through the metadata to look at the properties of the data and change the projection to a consistent type. Having a common projection allows the data to work seamlessly and using the metadata informs us of which projection will best represent the desired outcome.

One of the most important tool we learned about during our lab was the use of Remotely Sensed Landsat data. I saw first hand how it gave us the advantage of creating snapshots at different time intervals of an area that we can use to compare and show the changes in the environment. Landsat data has great potentials including mapping how an area restores itself after a devastation, how large scale development projects can affect the surrounding ecosystem and the effects of global climate change. All of these applications can help us make decisions about future conservation efforts, construction projects and recognizing areas that can have dangerous living conditions.