Hello and welcome to my first blog post!
In my first week of learning GIS in my Introduction to GIS course at UBC, I have started to learn how ArcGIS works and also come across a few major concepts: Coordinate systems and Landsat data.
Coordinate systems
Coordinate systems are fundamental to GIS mapping as they determine how longitude and latitude coordinates of places on Earth are displayed in mapping. They are basically the way for your place coordinates to be communicated in digital analysis. That said, in my first GIS assignment, I had to fix misaligned data layers that were improperly referenced – meaning, my data did not all have a common coordinate system, and misrepresented where my coordinates were in relation to eachother.
To fix improperly referenced data in ArcGIS you can:
- Use the ArcToolbox Project command.
This should let you change the coordinate systems of your data layers so they are displayed in a common coordinate system. - Tip: ArcGIS has a built-in function called Projecting-on-the-fly and this actually makes your layers look like they're aligned for the ease of viewing, even if your layers are actually misaligned and not in the same coordinate system. Therefore, you should always check the coordinate systems of your layers first (by clicking on the "Properties" of the drop-down menu of the layer) to make sure your data is in the right coordinate system.
Why do coordinate systems matter?
Projecting the uneven world into a digital sphere is always a challenge in GIS, therefore, with each different coordinate system chosen, properties of distance, area, shape, and direction of places is distorted.
Landsat Data
Landsat is a remote sensing program that uses a satellite to scan and capture images of the surface of the Earth. In this assignment, we have used Landsat images of Mount St. Helen from before and after it's eruption to observe vegetation and water body changes.
Disadvantages:
Landsat data is very useful to document large-scale topographical changes, however, there are problems of representation at such a large scale, as each pixel represents several meters of surface in real life. For example, looking at a road or a river from Landsat images, you may not be able to see the actual curves and angles of it. Instead, you may be looking at a computed average mixture of gravel, grass, and asphalt that cannot be discerned in its full detail at such a scale.