Saturday, August 12, 2017

Final Project - Water Quality and Population Growth in the Lower Cape Fear River Basin

The conversion of pervious cover to impervious cover increases stormwater runoff and thus, stormwater pollution into our creeks, rivers and streams resulting in impaired or degraded water quality.  Low Impact Development (LID) and Living Shorelines are effective best management practices for decreasing stormwater pollution and erosion.  Increased population is associated with increased impervious surfaces (rooftops, parking lots, decks, etc.) as the development of land is required with increased population growth.

This project focuses on waterbodies in the Lower Cape Fear River and the adjacent population within Brunswick County.  Brunswick County has seen considerable population growth and an increase in impervious surfaces and, in turn, increased degradation of water quality and closed shellfishing areas. This project attempts to find a correlation between increased population and water quality.

A New File Geodatabase was opened in ArcCatalog and appropriately named.  The 2012 Impaired Water Quality dataset was downloaded from NCDEQ and the 2016 Impaired Water Quality dataset was downloaded from the USEPA both of which contain data from the entire State.  Each dataset required a “select by attributes” function to capture only the impaired water from the Cape Fear River Basin.  A new shapefile was created for each year 2012 and 2016.  Both of these shapefiles were then clipped to the Brunswick County Block Group shapefile layer that was downloaded from the US Census Bureau.
US Census Block Group Population data downloaded from American Fact Finder for the years 2012 and 2015 were downloaded to an Excel spreadsheet and saved as an Excel workbook. It was necessary to prepare the spreadsheet for use in ArcMap (ESRI) which included deleting spaces and periods in the headings and changing the formatting for each column to “delineate” – “comma”, and then changing each column from “general” to “text”.  Proper headings were entered for the columns.  The spreadsheet was then imported to ArcMap.  Once the table was in ArcMap, it was then joined to the Brunswick County shapefile using the GEOID and ID2 as the common key for the join.  “Total Population” was the field used to symbolize population data for the block groups in ArcMap.

Wednesday, July 26, 2017

Module 8 - Damage Assessment

Our module this week covered different types of models for damage assessment.  Lab 8 tasked us with first creating a map that shows the different storm categories of Hurricane Sandy's path.  The map below shows the storm path from the Caribbeean into the East Coast of the United States.

In the second part of the lab we conducted a damage assessment using pre and post storm imagery. This also required us to create new feature classes in our geodatabase and create domains which include the categories of "no damage, affected, minor damage, major damage and destroyed".  We then digitized the parcels within the study area by using the create features in the editor toolbar which allowed us to then see the attributes for each of those features.  Unfortunately, I must have done something must wrong when creating my domains in the new feature because all of my digitized parcels indicated "no damage" which I know is incorrect from viewing the post storm imagery.  The second screenshot of my map below represents the storm damage assessment however it is not accurate.

Wednesday, July 19, 2017

Module 7 - Coastal Flooding

This week our lab focused on sea level rise and coastal flooding.  The first part of the lab required us to map the predicted six foot sea level rise along the coast of Honolulu which is shown below.  We also looked at the population density to determine social vulnerablity associated with a 6 foot rise along the coast line.

Wednesday, July 12, 2017

Module 6 - Crime Analysis

This week's lab module covered GIS in crime analysis.  Specifically, we focused on creating Hotspot Maps which are maps that reveal areas where there is more crime relative to other areas or relative to the average crime rate.  This week we were tasked with creating three different hotspot maps of Burglaries for the year 2007 in Albuquerie, New Mexico which include a Kernel Density, Local Moran's I and a Grid-based  map.  We then created one final map that includes all three maps for a comparison of three different ways to analyze crime hotspots. I overlayed each of the maps to complete the final map shown below.  The map reveals that crime is clustered in the center of the map or the center of the city.

Wednesday, June 28, 2017

Module 5 - Spatial Accessibility

This week we learned about spatial accessibility and how to use the network analyst extension.  Our lab started with completing an ESRI tutorial on the network analyst extension.  We learned about conducting a closest facility analysis and network analysis based on travel time.  Part B involved a basic spatial accessibility analysis which I had trouble with so I decided to move on to Part C and come back to Part B but I ran out of time. I struggled with the before and after closest facility analysis in Part C and ran into time constraints here and therefore could not complete Part B.  Part C involved a comparison of the accessibilty of the Austin Community College System in Travis County, Texas.  The first analysis scenario involved all 7 campus locations and the second analyis scenario invovled the closure of the Cypress Creek Campus.  The map for this part of the lab is shown below.

Wednesday, June 21, 2017

Module 4 - Visisbility Analysis

This week's lab tasked us with several deliverables one of which required us to conduct a visibility analysis of the finish line for the Boston Marathon.  Specifically, we were required to examine the viewshed and determine where best to place two additional cameras for optimal surveillance coverage.  I placed the two additional cameras on tops of buildings and created an offset of 100 using the field calculator in the attribute table.  I first placed a camera in the lower right corner of the map on top of a building but it was angled the wrong way and looking down the street in the wrong direction.  I could not figure out how to change the angle of the cameras so I placed another camera on the opposite side of the street from the existing camera. Part of the viewshed for this camera appears to be over tops of the buildings in the opposite direction of the finish line but part of it does appear to be on the finish line. I will have to revisit how to adjust the angle but I had to move on due to time constraints.  I placed the other camera at the other end of the street on top of a building.  The screenshot below shows the Boston Marathon finish line with a red X mark and the three cameras appear on rooftops with the corresponding viewshed shown in green.