FIXING MISALIGNED AND IMPROPERLY REFERENCED SPATIAL DATA
We first have to understand that the earth is a sphere, and the map is a flat surface. When a map is created in GIS Software, a 3D surface is projected to a 2D surface in our map interface to make our analysis easier. Therefore we need to acknowledge that distortion will occur when map is projected. The distortion might affect angles, direction, areas, shapes.
Different spatial data layers from different sources might be based on different Geographical Coordinate System, when they are added to the map interface, the ArcGIS will automatically aligned them. This built-in feature is called Projection-On-The-Fly. However this does not modify the spatial coordinate information but just make it “look like” they are in the same coordinate system for display purpose.
When performing spatial analysis it is a good practice to change the projection for a layer into a common spatial reference system. Before the spatial analysis, it’s necessary to check each layer’s GCS by checking layers properties and take notes. For Data that’s missing the spatial reference system, we need to add the approbate coordinate system by in layer’s properties under the “XY Coordinate” tab.
If we want to perform a specific spatial analysis on a certain projected coordinate system, we need to transform the coordinates. This function can be toggled by: ArcToolbox > Data Management Tools > Projections and Transformations > Project. Select the appropriate Output Coordinate System and hit OK a new layer with different spatial reference system should be showing soon.
THE ADVANTAGES TO USING REMOTELY SENSED LANDSAT DATA FOR GEOGRAPHIC ANALYSIS
Remote sensing data has been quite powerful in performing geographic analysis especially for observing changes of an area over time. For example, Landsat is able to update the image every 16 days. Remote sense data enable us to analyze the topography, water, vegetation and etc easily due to the colour bands and multi-spectrum image. There are a lot of fields that remote sensing data can be applied: examining the change of topography after a disaster, observing the ice retreat of Antarctica and etc. On the other hands, since remote sensing data is digital now, it allows quick spatial analysis timelessly accessible everywhere.