Final Project

Relocation Options for the Smith Family

INTRODUCTION

The Smith family will be relocating from the East Coast to the Los Angeles area for Mr. Smith’s new job at the Los Angeles Times. As with any relocation, they will have certain parameters that must be met in order to make their transition as comfortable as possible. First and foremost, the Smith’s have a daughter, Cindy, who has a severe medical condition, which requires them to be within 15 minutes of a hospital to assure the best chances of survival. In addition to this crucial requirement, the Smith’s are somewhat limited as they have Kaiser Health Insurance, which requires them to seek treatment at a Kaiser hospital. The two above-mentioned requirements are of the utmost importance. Another important consideration is that Cindy will be entering the sixth grade and would need a middle school close to home and again, within 15 minutes of a Kaiser hospital. An additional parameter is the budget for the home that they will be buying, which is $450,000 - $550,000. Finally, Mr. Smith will be working in downtown Los Angeles at 202 West 1st Street and he would like to have a commute time of 30 minutes or less. Generally, meeting all of these expectations would seem to be a daunting task, taking into consideration the requirements that must be met as well as the desires requested. With GIS, this seemingly difficult assessment can be laid out in an easy to understand map.

Take into account the needs and desires of the Smith family:

1.     Home must be within 15 minutes of a Kaiser hospital.

2.     Middle school must be within 15 minutes of a Kaiser hospital.

3.     Home should be within reasonable distance of middle school.

4.     Home prices in neighborhood should be within budget of $450k - $550k.

5.     Commute time to Los Angeles Times should not exceed 30 minutes.

METHODS

We must first determine how time is a factor when driving in Los Angeles. As anyone who has driven in Los Angeles knows, it always takes longer than you expect to get around. When constructing buffers around selected features, I opted to grant 3 minutes per mile for the purpose of this analysis. Keep in mind that buffers are distances “as the crow flies”, therefore one mile “as the crow flies”, may in fact be two or three miles in a car.

The most important features in this particular relocation map are the Kaiser hospitals, which are vital to Cindy’s health. After adding the landmark shapefile from Tiger, I selected for hospitals. Within the hospital attribute table I selected the Kaiser hospitals and created a new data layer. As you can see, there are five Kaiser hospitals in the area around downtown Los Angeles. I created both a three-mile buffer and a five-mile buffer around these hospitals. Depending upon the Smith’s comfort level, they could choose to live closer or slightly farther from the hospital, but still likely within the required 15-minute drive to the hospital.

Using geocoding, I determined the location of Mr. Smith’s work at the Los Angeles Times. I then applied a 10-mile buffer to that location, which should comfortably get him to and from work within the 30 minutes he had hoped for. I added a neighborhood shapefile as a data layer that I acquired through Zillow. Many neighborhoods were included, but some areas did not include isolated neighborhood names (such as Burbank and Alameda). With the use of a website (schoolsK-12.com) that listed schools along with median home prices, I was able to construct an excel sheet that enable me to create a data layer with middle schools that were in neighborhoods that were within the Smith’s house budget.

To better orient the map user, I included major roads and freeways. In Los Angeles freeways are our best method for understanding where we are in this sprawling city. In addition, an extent rectangle was included to better orient the map user. By incorporating the hospitals, schools, neighborhoods, buffers, roads and Mr. Smith’s new office to the Relocation Options for the Smith Family map, an otherwise difficult puzzle was made simple with the use of GIS. 

RESULTS

Of the five Kaiser hospitals indicated on the map, three of them fall within the 10-mile buffer established around Mr. Smith’s new job at the Los Angeles Times. An additional one falls outside the buffer, yet a portion of the 3-mile and 5-mile buffers around the Kaiser Permanente Medical Center do fall within the work buffer. There were only nine schools in neighborhoods with median home prices between $450k-$550K, that fell within the 10-mile work zone AND within the 3 and 5-mile hospital buffer zones. There were two additional schools (East Central) that were outside the work buffer, but within the 3-mile hospital buffer for the Kaiser Foundation hospital, thus still an option.

Upon looking at this map, it is apparent that all of the neighborhoods that meet the Smith's requirements are to the north or the west of the Los Angeles Times office. I would suggest to the Smith’s that they focus their house hunting in the Mid City neighborhood. Not only is it the largest neighborhood, but there are two middle schools, one within the 3-mile hospital buffer, and the other just outside of it. As a matter of fact, both schools are within the 5-mile hospital buffer for two hospitals. The neighborhood has homes with median home prices that are within their budget. In addition, Mr. Smith will have a commute well within his desired 30 minutes or less.  

CONCLUSION/DISCUSSION

If we reflect back upon the parameters of the Smith family relocation we can see that we were able to find neighborhoods that met the needs and desires they hoped to achieve using GIS.

1.     Neighborhood within 15 minutes of a Kaiser Hospital.

2.     Middle school within 15 minutes of a Kaiser Hospital.

3.     Neighborhood within reasonable distance of middle school.

4.     Home prices in neighborhood within budget of $450k - $550k.

5.     Commute time to Los Angeles Times not exceeding 30 minutes.

The Relocation Options for the Smith Family map makes it much easier for the Smith Family to select a neighborhood and middle school for their daughter Cindy that meets her special needs. Even if the Smith’s are unfamiliar with the Los Angeles area, they can refer to the map when they make their decision as to where to purchase a home that falls within their budget.

The limitations of this particular map is, that the median house price may not be the best method to determine what the range of prices in a given neighborhood are. It would be very possible to find a home within the Smith’s budget in another neighborhood that indeed is within the hospital buffer and has a middle school nearby. However, it would be virtually impossible to include every home price in such a vast area for this particular analysis.  

Spatial Interpolation

Spatial interpolation is a process whereby with the use of known data we are able to predict values for areas where we do not have data for reasons such as shortage of funding, lack of access or missing data. Using spatial Interpolation techniques I designed a total of six maps for the County of Los Angeles. Using data from the counties Water Resources website, http://ladpw.org/wrd/Precip/index.cfm, I was able to create an excel sheet that contained the known rainfall totals for both the normal rainfall totals and the season rainfall totals based on stations around Los Angeles County. With this information I then created maps using two different Spatial Interpolation techniques; Inverse Distance Weighting (IDW) and Spline, which are more exact techniques. With maps created for both normal and season rainfall totals in each of these spatial interpolation techniques I was able to use the raster calculator to determine the difference between the normal rainfall and the season rainfall to create two new maps.

As you can see on the IDW Normal map the heaviest areas of rainfall are in the eastern central part of the state with very precise definition. In the Spline Normal map below, you see the higher levels of rainfall in the same area, but with larger areas, less defined. In the Season maps again you see more defined areas of rainfall in the IDW map and more general in the Spline map. We observe the comparison maps created using the raster calculator we see more variation in the IDW map than in the Spline, however they is a general pattern that they share with above average rainfall in the eastern portion of the county and less in the west.

When creating these maps I had to consider which spatial interpolation technique to use. I opted for the IDW and the Spline methods as they are considered more exact. When using the IDW method I opted to use the default power of 2 and the variable radius type. I considered my data after evaluating the locations of the stations and since some areas of the county had sparse data, I opted to use number of points for my evaluation and used the default of 12. When using the Spline method, I tried the default regularized type however the data seemed extreme, so I tried the tension type which gave me more reasonable results. Based upon the final results using these two spatial interpolation techniques, I would tend to use the Inverse Distance Weighting as I feel like it gave more specific results.

In this week’s lab we were to create a slope/fuel hazard model for the area within and surrounding the Station Fire. The Station Fire of 2009 was the largest wildfire in modern Los Angeles County history. Located 15-20 miles north of downtown Los Angeles, the Angeles National Forest bore the brunt of the flames. With fire suppression being the norm, there was plenty of fuel for the fire that was a result of arson. Beginning on August 26, the fire quickly spread over the following days and eventually was responsible for the death of 2 firefighters, the destruction of 209 structures and over 160,000 acres of once forested land was burned.

The purpose of this map is to incorporate slope data with land cover data to determine the areas with the highest threat of fire. I first acquired a digital elevation model (DEM) from USGS, which was used to create a slope in percent that was then calculated and modeled. I reclassified this data into ten ranges. The land cover (fuel) data, acquired from atlas.ca.gov, was reclassified into 10 categories, based upon the highest threat of fire (flammability). These two layers were used to create a slope/fuel model using the raster calculator. I then added additional information such as major roads and the perimeters of the 2009 Station Fire.

Upon analyzing the completed model it is apparent that the area within the previous Station Fire does in fact have a higher slope/fuel hazard. However, I also noticed that to the east of the fire there appears to be an even higher risk of potential fire. I must ask myself if the method I used for classifying the vegetation types might have been flawed. The vegetation shapefile used did not have the same breakdown of vegetation as the breakdown shown on the tutorial that I used as a guide. Thus, it is possible that my reclassification was incorrect. I would seek out a different shapefile that aligns better with the National Fire Protection Association’s NFPA1144 if I were to create this map again, and then compare it to this completed map.

Lab 5 Landfill Suitability Analysis

California has some of the most stringent environmental policies in the nation. The difficulty being, that it is hard to enforce these policies. In addition to the environment protections, the human population must be considered as well. Kettleman City, in the Central Valley is the home of a 1,600-acre landfill that has raised concerns for the local community, and now this small town is gaining political attention and support. At question is whether Chemical Waste Management, who is intent on expanding this site, has been neglectful in providing a safe environment for those exposed to some of the toxic waste within and running off the landfill. A thorough study must be made to ensure that the community does not suffer potential harm as a result of the landfill being expanded. A Suitability Analysis is one way to locate the best available location and potential expansion for a landfill. 

In this week’s lab we created and converted grid layers to produce an analysis model for a fictional county in Montana, Gallantin. We used the Spatial Analyst to assist in order to mask our area of study so we could better focus on the area of interest. We produced 5 individual maps identifying relevant factors of the area of study, as well as a final analysis incorporating the factors into one map.

We produced a map indicating the slope of the study area, which is relevant for potential runoff. The second map created buffers around the landfills in the area of study, of which there were two. Map three, indicated the soil drainage for the study area. The fourth map shows buffers around streams in the area. Map five, shows the land cover for our study area. Each of these factors play an important role in determining the best area suitable for a landfill with minimal impact on human life, which is our goal.

Using the raster data we created, we were able to produce our final analysis process map. We incorporated each of these factors, with weighted values placed on elements, to create a map that would provide information necessary to locate the best areas for a landfill. It is through careful analysis with consideration of key factors in relationship to landfills that the potential of human health and wellbeing can be preserved.

I enjoyed this lab, as through some of the repetitive functions it became second nature producing the maps showing the different factors involved in locating an acceptable place for something such as a landfill. Bringing all of these factors together into a final analysis was rewarding. ArcGIS is an invaluable tool for presenting visual aide in an easy to understand format.

Mid Term

Not in my backyard! I approve the legalization of marijuana for the tax revenues it would produce and accept the fact that for some, it brings needed relief to those suffering sever pain. However, I do not think that a mere 1000 foot buffer is sufficient enough distance from our children. It is quite apparent from the map above that schools are quite numerous in the city of Los Angeles. Upon a closer look (map below) it is obvious that much of Los Angeles is residential and it is difficult to find areas that fit within this buffer zone. I feel that areas prone to more industrial areas would prove to be safer on the whole.
In the area just to the west of the Santa Monica Blvd. label in the lower map shows a dispensary with a school within it's buffer zone, and yet another one further to the west. I recognize the honest need for alternative methods of pain relief, but does it need to be this close to a school with children? Marijuana is considered a "gateway" drug, and whether you support that theory or not, some of those who choose to use it are not always the sort of people you want around children. I feel a better alternative would be to allow dispensaries to operate in more commercial areas or industrial parks, places where children are not likely to be exposed to some of the less than attractive aspects of marijuana. Further GIS mapping could locate areas with a more significant buffer zone between children and marijuana.

Digitizing Iraq

I am a visual person and love playing with color. I enjoy playing around with the layout options and deciding how best to present information through GIS. I elected to keep this map simple, not too many colors, not too much clutter. Digitizing has been one of my favorite parts of GIS thus far. I'm certain some would find it tedious, but I enjoyed the challenge.
The Iraq map was a nice project. Not only did it get me familiar with the digitizing process, but also how to label attributes. Once I digitized the boundary for Iraq I used the Cut Polygon Features option to outline each of the provinces. Identifying each of the cities helped me become familiar with some of the cities I have heard of for the past 8 years since we have been in Iraq, but never bothered to identify their location.
The most difficult part of digitizing this map in particular was dealing in and around Baghdad. It got a little messy in that area and defining the flow of the river was difficult even magnified at 600%. The only other problem I ran into was that the scale bar was obviously not true to the map. Jida informed me that I would have to do some finite projecting to correct this. I would like to learn this when I have the time. Jida also instructed me on how and when I could use the Auto-Complete and Modify Features options.
Though I am not fully proficient with the commands and at times struggle with basic computer language, I am glad I have been able to complete, as best I can, the labs. I have enjoyed learning how to use GIS. I really wish I had the luxury of having access to the program at home on my own computer, not just remotely or during school hours.

Schools of the Westside

When considering a place to live one must take many things into account. If you have young children, schooling should be at the top of the list of considerations. Knowing which schools are available and the distances to the schools is important. For young children it is beneficial that they live near their school so that they may develop friendships and have access to friends they attend class with.

The Westside of Los Angeles is a very desirable place to live and has an abundance of schools to choose from. I produced a map showing the schools of the Westside. I selected schools, both public and private, in Pacific Palisades, Brentwood, Westwood and Santa Monica. I created three buffers around each school one at ¼ mile, the second at ½ mile and finally at a distance of one mile. Each of these distances are reasonable walking distances in a place where walking is rare.

As can be seen in the Schools of the Westside map, the schools, in general, seem to appear in clusters with many ¼ buffers overlapping. Not surprisingly the number of private schools outnumber public schools in this affluent part of Los Angeles. The densest cluster I found to be in the town I live in, Pacific Palisades. There are four schools within a 3-block area and it appears as a dense cluster in the Palisades Cluster map. Three of these schools are private and the other is public. Less than ¼ mile away is a Palisades Charter High School, where my daughter is a student.

It is important to consider schooling options when choosing a place to live if you have children. Maps such as these, produced using ArcMap, can help give a visual display of which neighborhoods offer the best options for those with school-aged children. There are of course many other considerations to bear in mind when finding a home to settle into. By adding more layers to this map, such as potential jobs, recreational desires, doctors, etc., one could find a home that will afford them the luxury of spending more time doing something they enjoy and less time on the road.  

Potential Wastewater Plant Site Lab 2

Lab 1 Geo 168