WSU Commuting Times

As a second project for our class this week, we had to find out the average distance and time that commuter students attending Westfield State University traveled in one trip. Again, we could not use maps in our visualization of the data so below is the document that I've prepared for this assignment and then below that is the link to the website where I created the infograph! Check them out!

Click here to go to the website where I created the infograph and see my inforgaph in it's unedited format!

Enjoy and stay posted for more!

*UPDATE*

Hey everyone! I recently went through the data for the commuter students to figure out what the average straight-line distance is for commuter students to see if it would be different from the OD Cost Matrix tool that I ran to get the above information. As it turns out, there is quite a big difference. See, the OD Cost Matrix tool uses the network dataset, so the main streets for this project, to calculate how long it would take to get there but with a straight line distance, you are calculating it "as the crow flies" so you are not taking into account road distances. The average distance for commuter students using straight line distances is about 6.16 miles traveled for one trip to school. On the other hand, the average mileage traveled using the Cost Matrix was 15.6 miles. So you can see that there is a difference between the two tools. Neither tool is better than the other, you just need to keep in mind what you need to know from your data - maybe straight-line distance is a better choice for you or the cost matrix would be best - it all depends on your need!!

Fire Department Response Times

This week in class, we were asked to analyze the Fire Department response times for any city we want and see how the city would be affected if we removed one of the fire stations. Our challenge was to visualize our data without using a map. I chose Worcester, MA, as my city and removed the Tatnuk Square Fire Station (TSFS). I chose the TSFS because it was one of the outlier fire stations (located on the West side of the city) and I wanted to see a dramatic change in coverage. I analyzed the data from the US Census Bureau for population in the city along with the Network Analyst tool to determine how many people would be affected by the closing of the TSFS, mainly taking into account the critical 6 minute sudden cardiac arrest response time.

As stated in the document, one of the flaws with this analysis is that it does not take into account the surrounding cities' fire departments. The next town over's fire department may be able to respond to a victim with sudden cardiac arrest within 6 minutes, therefore reducing the impact of closing the TSFS. Another flaw with the analysis is that it assumes equal distribution of the population over each block group in the town. This is obviously not true; some block groups are very heavily populated on one end and very rural at the other end but this is the only way to fairly represent the block group.

*Block groups are clusters of census blocks created by the Census Bureau as a geographic level between blocks and census tracts. Block groups have anywhere from 600 to 3,000 people located within them and has the most detailed population data available.

Below is the document that I created for this project.

Also, you can click here to see the actual infograph on the web!

I hope you enjoy it and keep posted for more!

MA Community College Proximity

For class this week, we were asked to use two different tools to find out what towns are within 20 miles of the 15 community colleges in Massachusetts. The two tools were the Euclidean Distance tool and the Network Analyst tool. The Euclidean Distance tool measures straight-line distances, so from one town to the college "as the crow flies." The Network Analyst tool measures distances by road networks. Each tool has its advantages/disadvantages. Perhaps you don't need to know the distance on the roads or you are looking at what colleges would be closest to your house where you would need to know the distance by road networks. It's all about what you need to know from the map.

As you can see below, there is a noticeable difference between the two tools.

Enjoy and stay posted for more soon!

Mt. Tom Wind Turbine Project

This week for class, we were asked to show what areas in Easthampton, Southampton, and Holyoke would be able to see a 400ft wind turbine placed on the highest peak of Mt. Tom. We were also asked to calculate the degrees of visibility - which areas would see 100% of the turbine, 75%, 50%, or 25%. On top of that, we also had to see which areas may be somewhat protected by the screening effect of trees - what areas were forested. Below is the poster that I created for this project.

I also created an ArcGIS Online web application to show this:


View Larger Map
And to top it all off, below is a Google Earth map to visualize the viewshed.

You can also click here to see the flowchart/report that I created for this project.

Straight-Line Distances

Good Wednesday evening, everyone! I seem to be a bit behind on posting recent class assignments but on Monday, the class was asked to calculate the straight-line distances from one point to several other points. This was accomplished using ArcGIS Desktop 10.1 and the Point Distance Tool. Simple enough, right? Using this tool, I was able to calculate the straight line distance from my house to several horse farms in Western Massachusetts.

Below is the map that I've created for this assignment.

I also created the same map with a grey background to better see the location of the points in Western Ma. You can choose which you find more appealing.

An important thing to keep in mind when looking at this map is that these are straight-line distances...that is, it is the distance "as the crow flies" as the saying goes. This is not the same as driving distance, which in reality is longer than a straight line distance. Nonetheless, I hope you enjoy it!!

Mt. Tom Wind Turbine Viewshed

For class this week, we were told that we have an upcoming project that is siting a fictional wind turbine on Mt. Tom in Holyoke, Massachusetts, and seeing how visible it would be to the surrounding towns. Before any GIS work can be done, though, a flowchart must be created. This will help keep us organized along the way with our project and help keep us from pounding our heads on the keyboard in frustration or saying "um...now what do I do????" Flowcharts make you think about the process before you even touch the mouse so that you won't get stuck..hopefully. So below is the flowchart that I have created for this upcoming project. Keep in mind that this is what is called a "living document." I will be making changes to the flowchart as I go along in the project as we do not know the specifics of the project, so different criteria will be specified or different tools will be used. This is just the very basic flowchart that I will be using.

Wind Turbine on Mt. Tom

Hope you enjoy it and stay posted to see the project and final flowchart!

Solar Wind Farm

For class this week, we were asked to do a site selection analysis for a Solar Village (wind farm) project on two different towns using three specific criteria:

1) The site had to have a slope angle of 20 degrees or less
2) The slope of the site had to have a southerly aspect (135 to 225 degrees)
3) The wind speed at 30m had to be above 5 m per second.

The towns that I did my analysis on were Adams and Peru, both in Massachusetts.

Below is the map of the two towns side by side showing the suitable parcels.

Also, you can see these suitable parcels on ArcGIS online by clicking here. 
Or see below


View Larger Map

Below is a quick map of the suitable parcels of Adams, Massachusetts.

You can also click here to download the KMZ file for Adams, Massachusetts, and open it with Google Earth.

Below is a quick map of the suitable parcels of Peru, Massachusetts


You can also click here to download the KMZ file for Peru, Massachusetts, and open it with Google Earth.

Enjoy!