Applications Module 6 Blog 1

 

Applications Module 6 Blog 1

    In our analysis for this module we primarily focused on raster datasets starting with a digital elevation models. In this scenario we were tasked with determining the most cost effective path of a pipeline passing through a mountainous region in Oregon. 

    The costs for slope were the first factors that needed to be set up by first taking the DEM and converting it to a slope raster giving each cell an elevation value. Once the slope raster was created a new raster was created by reclassifying all cells that fell within certain degrees such as 0 - 2 degrees would be assigned a value. That value represented the cost of travel for those cells, as the slope increased, so did the cost of the project to install. 

    We then were tasked with reclassifying four other raster's that considered landcover, rivers, roads, and soil types. 

    Once the classifications for each raster, we then combine all of these raster sets into one tool and applied an equally weighted value of 20% between all data sets. the values within each raster to be combined were either a 0 or 1 for certain things like rivers and roads, others were assigned a range of values which equaled cost. 

This is where the Boolean algebra comes into play, determining true or false. 

Then a tool is ran that creates a backlink from the classified Slope dem, and finally a tool that takes into consideration the backlink, source location, and destination, as well as the combined raster. 

This tool then takes all of the factors over this area and determines the lowest cost path for a line to travel from the source location to the destination. 

The layout above reflects the difference between different styles of weighted values, or in other words, putting more weight on some features of the topology than others.