Introduction:
L ab 4's goal was to create a spatial question and use geoprocessing skills to answer the question. The project required using 4 tools using 3 different ones. The spatial question I chose was where is the best place to live in Denver, Colorado. In order to be a desirable spot the location needed to be at least 1 kilometer away from major highways, a majority of the residents needed to be between 20 to 34 years of age, and finally the location needs to be within 500 meters walking distance of a park. Multiple tools were used to achieve this answer. Buffer, Dissolve, and Erase were used to spatially answer the question. The intended audience for this spatial question would be people who are looking to live in Denver at a young age and be nearby outdoor recreational places.
Data Sources:
In order to answer this question it required using data showing highway locations, park locations, and block groups obtained from the city of Denver. the data i used was found in the states section of the metadata from ESRI, and block group information was obtained from the City of Denver (https://www.denvergov.org/opendata/dataset/city-and-county-of-denver-addresses). from the Block Group data set, i utilized the age ranges 20-24 and 25-34. Some concerns i have with the data is what year it came from, if it is older data the map may be off by the current years standards.
Methods:
In order to answer this spatial question information needed to be obtained, from previously listed data sources, that would be useful for applying to the criteria for a desired living area. The data needed was first the shape of Denver county, then a clip of highways running through Denver, block groups in Denver, and parks within Denver county. First off the Denver Highways were buffered b 1 Kilometer to satisfy the distance from highway criteria. Then the Buffer was dissolved to remove the lines in the buffer and make it smoother (Figure 1).
(Figure 1) This figure shows the flow model for the 1 kilometer highway buffer.
The block group clip was then used to select the age group that is desired to live around in this case age 20-34. this was performed by selecting by attributes the ages 20-24 greater than 200, and the ages 25-35 greater than 200. After selecting the block groups with the desired age range, they were dissolved to remove the dividing lines, this produced the layer "Maj_Age_Dissolve" (Majority age) (Figure 2).
Figure 2: This figure shows the attribute selection and dissolve of the Block Group age range 20-34.
Next the dissolved 1 Km buffer was erased from the Maj_Age_Dissolve to produce the Layer Maj_Age_Dissolve_1kmbuff. This layer is the desired living area with the correct age range and distance from highways. Before adding the final criteria of being within 500 meters of a park.
Figure 3: This figure shows the Erase performed between Maj_Age_Dissolve, and the dissolved_1km_buffer.
Next the Parks feature class was buffered 500 meters and then clipped and erased to form the Desired living area in Denver. The Parks Buffer was erased and then clipped to only leave the Desired location with an age range of 20-34 and within the buffer of the parks (Figure 4).
Figure 4: This is the entire flow model showing every step to produce the desired living space based on the criteria of 1 kilometer from highways, a majority age group of 20-34, and within 500 meters of a park.
Results:
The Result of the spatial question of where is the best place to live in Denver is shown in the map below that illustrates the desired locations away from a highway, around an age group of 20-34, and in walking distance of a park (Figure 5)
Figure 5: a Map showing highways parks and the desired living area in Denver based on the criteria for the projects.
Evaluation:
My impression of this project was that it is very useful in making us think about where to obtain information and how to use it without having step by step instructions explaining what to do. If I were to repeat the project I would probably choose a better spacial question that could have more criteria too it.
