Fixing Misaligned and Improperly Referenced Spatial Data
There are several ways that you can fix misaligned and improperly referenced spatial data. The first option is to simply let ArcGIS do its magic. Through a process called projecting-on-the-fly, ArcGIS will essentially take maps with different coordinate systems and align them together automatically as if they are on the same coordinate system without actually changing the coordinate system itself. The only downside to this method is that it is only for temporary display purposes. Projecting-on-the-fly is a band aid solution and will not solve the root problem (i,e, using differently georeferenced data), which will cause immense trouble when you start to geoprocess data and use spatial analysis tools. Alternatively, you could use the commands, Project from the ArcToolbox. The Project tool allows you to manually pick the specific data set that you wish to modify and convert its original coordinate system into a different one. Therefore, creating a new layer with the proper spatial reference system that you want to use.
Advantages of Landsat Data
In a nutshell, raster data represent features as a matrix of cells within rows and columns. This can be seen from remotely sensed Landsat imagery or other aerial photographs. Raster data models are very commonly used to represent the world because of several advantages. One of them is the fact that data can be represented at (nearly) its original resolution without generalization. This high resolution characteristic of Landsat data makes it a great tool for monitoring, tracking, and documenting changes occurring on Earth’s surface. These changes could range form land use and urbanization, to wildfires and drought, to river patterns and animal grazing. Landsat images are incredibly useful for geographic analysis because they inform us the of the current state of the world and point us in a direction to make decisions, draft policies, and bring a positive change to places near or far. For example, a team of researchers could use Landsat images to examine the impact of hurricane Maria on Puerto Rico and identify areas that need immediate attention in terms, let’s say, high landslide risks. Alternatively, it could also be used in conjunction with GIS analysis to pin point the most optimal locations for setting up resource distribution stations because so many people are suffering from a lack of access to roads, telecommunication, food, water, medical kids, sanitary products etc.