In the software that we are using in class, ArcGIS, there are a lot of factors that contribute to the inaccuracy of the data displayed to make the maps. In the second lab that we did, it was mostly focussed on coordinate systems, and spatial data models.
The first part of the lab was determining the distance between two cities in Canada, Vancouver and Montreal. It was important to figure out the prime projected coordinate system for the region being studied as we’ve learned in lectures that some projections of the maps will distort different factors of a map, for example, distance, area, shape, and direction. It was important to keep in mind the features of ArcGIS as well. For example, the one that we’ve studied in this particular lab, Projection-on-the-Fly.
Projection-on-the-fly changes the image automatically, correcting to the existing projection already selected, whereas using the project and transform commands, the projection could be more suitable for the particular case, as it will be defined according to what you want. In the Projection-on-the-fly featured, the spatial data coordinates are not changed by the process, rater it just makes everything look like it’s under the same coordinate system, which will create a problem regarding accuracy.
Part two of the lab was about remote sensing Landsat data. Landsat is basically a satellite that goes around the earth, that captures images for elevation from sensors on the satellite. The advantages for Landsat is that is it a relatively cheap and efficient method of acquiring up to date information, as the satellite makes it around the earth every 18 days. Data can be collected at inaccessible places like Antarctica, or the middle of a dessert. And some of the data is easily accessible for everybody. What we did in the lab was assessing the difference on the forest covers after the Mount. St. Helens eruption. (See Below)
Landsat data would also be useful for analyzing landslides. The potential research question could be about how secondary succession and the changes in land use progressed after the landslide, the geographic location could be similar to the study done on Mt. St. Helen’s, where the area surrounding the landside as well where the landslide area has occurred could potentially be studied. The time interval could be done at bigger interval if measuring for plant and forest growth, preferably around the first year to the next decade. If studying land use changes, intervals could be smaller, around a month to a year, as it will take less time to change what the land is used for. Preferably for measuring forest growth after the landslide, measuring during the same time of year, or during growing season would be more favorable.