Homeland Security - Preparing MEDS Datasets

This week we looked at how to prepare a set of data for use as Homeland Security's MEDS, or Minimum Essential Data Sets.  The purpose of this lab was to take base data and create a tailored MEDS package for the Boston Metropolitan Statisical Area (BMSA).  The goal is to used the data package that we created to conduct a pre-Boston Marathon Bombing assessment of the BMSA and determine what roadways, buildings, and infrastructure are classified as critical in the event of an emergency.

The MEDS dataset that I created contains different layer groups to help organize the data.  The groups that were created were Boundaries, Transportation, Hydrography, Land Cover, Orthoimagery, Elevation, and Geographic Names.  Each set of data was tailored for the BMSA.  To create the MEDS data, data was moved from a provided Geodatabase into the proper layer groups listed above.  Manipulation of data was necessary for certain datasets, such as roadways, to create the final MEDS dataset.  These group layers also had specific symbology and labeling features set to them. 

In the end, every group layer was saved as a layer file to preserve these settings.  This enables future users of the BMSA MEDS package to get right into doing data analysis without having to format a bunch of layers of data.  This also ensures that the formatting is standardized across all users. 

Below is a screen shot of my final BMSA MEDS package.  If you have any questions at all, leave a comment below. 

Crime Analysis in the DC Metro Area

This week focused on using different techniques within ArcGIS to analyze crime statistics and then create maps based off our analysis. 

The first map that was created was using statistical crime data to determine where there may be gaps in police coverage that could be filled by creating a new police station/substation.  This map also analyzed what were the most common forms of crime during 2011.  As you can see, almost 75% of all crimes happened within 1 mile of a police station.  Now despite this, there were a couple of potential gaps that I proposed new stations for.  The first one in the south-east would cover a large area that was outside of the 2 mile coverage and reduce some of the burden on the 7th District station.  The second proposed station is in the north west and would fill a small coverage gap, but more importantly, it could take some of the burden from the 2nd and 4th District stations. 

The second map I created focused on three types of crimes, burglary, homicide, and sex abuse.  The three map panels you will see show the different frequencies of the different crimes and that information is overlayed on top of a population density sublayer.  While it is a little difficult to see the population density clearly, you can gather by the dark undertones where there are more people and see whether population is more of a factor for certain crimes.  

That is all for now.  Let me know what you think and happy mapping.  

Tracking Hurricanes and Assessing Damage

This week in my Applications in GIS class we looked at how to apply GIS to hurricane tracking and damage assessments.  The scenario we applied the techniques this week involved Hurricane Sandy which caused unprecedented damage for a category 1 storm. 

The first map I made was a tracking map for the storm from start to finish.  The track shows what category the storm was as it moved north through the Caribbean Sea and Atlantic Ocean.  The points along the track also showed the wind speeds and barometric pressures.  Finally, the states that were affected by the hurricane were also highlighted on the map.  The final product is below:

The second map I created took a more involved look at assessing the damage that was caused in a New Jersey neighborhood when Sandy made landfall.  I analyzed pictures of a section of beachfront property that were taken before and after the hurricane blew through the north eastern United States.  The intent of the analysis was to determine what kind of damage occurred to the homes near the coast.  The types of damage that we looked at was structural, wind, and storm surge inundation.  The section I looked at appeared to have every house suffer storm surge inundation.  What was really difficult to determine was the effects of wind and structural damage aside from those houses that were completely wiped out.  The parcels were noted with the level of structural damage on the map.  A table was also created with the tallies of properties and the type of damage on them.  Finally, both the pre and post-storm imagery was used to show the extent of the damage.  The map that was created is below. 

Let me know what you think!

Tsunami Analysis and the Fukushima Disaster

This weeks focus for Application in GIS was Tsunami analysis.  While the analysis we conducted was based on the Fukushima tsunami incident in 2011 and wasn't exactly for preventative planning, the results of the analysis could be used for future planning.  In preparation for this lab, we also did a module focusing on how to create feature datasets in ArcGIS as well as going a bit deeper into adding feature classes and rasters into geodatabases. 

For the lab analysis of the Fukushima disaster, we conducted two separate analyses.  One focused on the radiation spread from the Fukushima reactor meltdown and how distance affected how at risk one was and where people really needed to evacuate from.  The second analysis focused on the tsunami itself.  Using raster imagery, masks were made from the coast to 10,000km inland.  Using these masks and the already known land area that was affected, an evacuation zone plan was made to provide a layout for where safe land could be found in the event of another tsunami. 

The evacuation zones for the radiation zones were created manually using ring buffers centered on the Fukushima II power plant.  However for creating the evacuation zones for the tsunami affected lands, more automation was used by implementing a tool within ArcGIS called model builder.  Again, once these zones were created, the final map was created and can be found below.  I do ask if anyone has any issues with my color choices, please comment below with suggestions.  Living as a color blind individual does not always translate well in full color mapping. 

Enjoy!

Lahars and Mt. Hood

This week in Applications in GIS we focused on applying our GIS skills to determining how a lahar would affect a population base using different tools within ArcGIS.  For those who don't know what a lahar is, it is a destructive mudflow that is triggered during a volcanic eruption.  When a volcano erupts, the intense heat melts snow packs and glaciers on the volcano slopes and the resulting flows pick up mud and debris that are then carried down slope destroying everything in its path.  Typically lahars will follow existing stream and river beds as they are the paths of least resistance.  Two somewhat recent lahar flows were those resulting from the Mt. St. Helens eruption in 1980 and the 1985 eruption of Nevado del Ruiz in Columbia whose lahar flow killed over 20,000 people in the town of Armero. 

Our lab this week had us replicate a study of the Mt. Hood stratovolcano and how/where the potential lahar flows would affect the surrounding areas.  The first step to this lab was to obtain the geodatabase that we would be working from.  The data provided within this geodatabase would serve as the foundation for all the processes we would complete in this lab.  A main point to using this geodatabase was keeping a naming convention for newly created elements that made sense and ensuring that we didnt keep useless files within the geodatabase.  The picture below illustrates how my geodatabase ended up at the end of the lab. 

The following steps were used within ArcGIS to create the basis for creating the map that you will see below.  First, a study area was created around the Mt. Hood area that encompassed the Multnohmah, Wasco, Clackamas, and Hood River counties.  This study area would serve as a clip feature to remove unnecessary features later on in the map creation.  

The next step was to create a mosaic raster out of the provided rasters files in the geodatabase.  This was done to make analysis easier by analyzing only one raster vice having to complete the analysis on multiple rasters.  Once the raster mosaic was created the following tools from the Spatial Analysis toolset in ArcGIS were used in the following order: the Fill tool, the Flow Direction Tool, and the Flow Accumulation Tool.  Appropriate file names were used for the resulting outputs.  So what did these do?  They basically identified the likely areas where liquid materials will flow to on Mt. Hood.  In essence, this amounted to a stream network flowing from the peak to the base/surround areas of the mountain.  

Next I used the math Int tool to convert our values from the previous steps to integer.  Originally the pixels had floating point values.  We would then determine what 1% of the value of the total number of pixels were in our stream network.  That would then be used in the Con tool to create what was more likely to be the true stream network.  This output was then converted to a geodatabase feature using the Stream to Feature tool.  

The remaining steps involved conducting the actual hazard analysis by creating a 1/2 mile buffer around our stream feature and determining which population blocks and schools would be affected by the 1/2 mile lahar buffer.  The results were then mapped and the output map is below.  Please let me know if this map works for you.  As a colorblind mapper, I always welcome comments and suggestions to make things better.  Cheers!