Applications in GIS - Module 6 - Suitability & Least Cost Analysis

In Module 6, we learned about Suitability and Least Cost Path Analysis. We were introduced to performing suitability analysis using both vector and raster analysis tools. We prepared our data for suitability analysis using different approaches, such as Boolean and scoring, and adjusted specific parameters using scoring and weighting. Additionally, we performed least-cost path and corridor analysis using cost surfaces as well.

In Scenario 2, our task was to perform a suitability analysis for a land developer. We analyzed several variables including proximity to roads, elevation slope, proximity to rivers, and land cover type. These variables were reclassified and ranked based on the value of each cell in the raster. The raster layers were then combined using the overlay tool. Finally, we were required to create a map layout comparing the results from the two alternatives. Below is my final product.

Applications in GIS - Module 5 - Damage Assessment

In this module, we delved deeper into the impact of Hurricane Sandy, focusing on damage assessment. To complete this task we learned how to create raster mosaics for pre and post hurricane, created attribute domains to categorize damage, and utilized our skills to decide how to summarize the data from the damage assessment.

To begin we used meteorological data to create a storm track map showing Sandy's progression from below the Caribbean islands on October 22nd, 2012 until it made landfall on the northeast coast of the United States as a Category 1 hurricane on October 29th, 2012. 

To complete our damage assessment we used our pre and post imagery to assess the damage to structures in our study area. Each property in our study area had to be identified and categorized according to the domains that we created. Each domain provided a choice for what level of damage each property appeared to have based on our remote imagery. After assessing the damage and symbolizing the data we were tasked with creating a polyline feature class representing the pre-storm coastline. I then created a multi-ring buffer establishing a 100m, 200m, and 300m buffer. This was used to summarize the data and help discern and identify patterns. Below are my results:

Link to my StoryMap