Cartographic Skills: Final Project

-
For the final project we were given two different scenarios to chose from:
  • Option 1- Display mean SAT scores and test participation rates for 2014 college bound seniors.
  • Option 2- Create your own project scenario.
I went with Option 2 to see how it would go. My scenario of choice focuses on observing the correlation between amount of crops harvested in the state of California for the year 2012 and the distribution of different Farmland types as defined by the Farmland Mapping & Monitoring Program (FMMP).

Methods Used: First thing to do was search for the necessary data sets: information on crop yields and data on farmland for California. USDA site was extremely helpful as was the California Department of Conservation website. NOAA was very helpful in providing national weather reports, maps, and graphs to see firsthand record of gradual change in different regions.

Next, was looking for a California counties shape file, which was found through ESRI and the U.S. Census Bureau. This counties shape file, along with other layers used for the map, was then projected to NAD 1983 California Teale Albers because it is the preferred statewide projection according to the California Department of Fish and Wildlife website.

Using data provided in the California Agricultural Statistics, 2013 Crop Year report from USDA, all crop types and total amounts (in acres) harvested in 2012 were acquired for each county and recorded in a single sheet to use in ArcMap. This dataset was then Joined to the county shape file in order to create a proportional layer based on Acres Harvested. Proportional mapping method was utilized for this layer using a standardized dataset to best communicate the value of some counties for crop production. This dataset is represented in the map through graduated symbolization using Natural Break (Jenks) and five classes ranging from 0 to 215,300 acres.

The California Department of Conservation’s Farmland Mapping & Monitoring Program was extremely helpful in finding information needed for Farmland type distribution. A merge was done in ArcMap to compile all county shapes into a single shape file. Once merged, this dataset utilized the choropleth mapping method based on Farmland types. The FMMP defines a total of eight Farmland types, but only seven are represented in the map because one of the types is water.

Results & Conclusion:  After reviewing numbers and the data fleshed out on the map, it was interesting to observe how much of the state’s crops come from the counties in the North Central region of California, what crops are common in this state, and which crops are harvested most. The most abundant Farmland can also be found throughout central California. 
Having selected scenario Option 2 for this final project was the right path to both challenge myself and test the skills learned throughout this course. Below is the map compiled for this assignment.


Comments

Post a Comment

Popular posts from this blog

Module 6- Proportional Bivariate

-
Image
This last module dealt with proportional bivariate mapping methods. Below is a proportional map reflecting negative and positive values for the increase and decrease in the number of jobs across the U.S. We had to convert the negative values into positive values for this purpose, which allowed to symbolize is proportional to the positive values for comparison. I selected a light bright blue hue to represent the loss of jobs and a warmer purple hue to represent jobs gained. For this particular symbology need, the challenge was not so much the quantity of the values I wanted to communicate. The challenge was finding a balance and gain a better understanding of how to use color themes for that purpose. Initially, I had considered using red and blue (as in hot and cold), but it felt too political and not related to the subject matter. The main exercise for this module demanded that we create a bivariate map displaying the relationship between obesity and physical inactivity perc
Read more

Module 4- Color Choropleth

-
Image
This week's module dealt with Choropleth mapping and color theory. Not being an artist, this was somewhat intense and thought-provoking. Our lab was great in walking you through the process of selecting the right color theme for a map. First, we covered some exercises in color ramp progressions. Below is an example displaying three varying gradients using the same base dark green hue. Original intervals: 51, 26, 31. In the Adjusted Progression, I reduced the previous intervals by -10 and added the values to each new set of RGB values. This appeared to make the hues above a shade darker. The adjusted progression is noticeably a shade darker in hue than both linear progression and ColorBrewer. ColorBrewer is also slightly more green, you can notice this change on the lightest color. I’m unsure what the formula used to produce those hues is, but they exhibit a bit more saturation within the hue. For the main lab exercise, we had to create a map displaying the change in the cou
Read more

GIS5100 Week10: Final Project

-
Image
My final project was dedicated to finding suitable areas for a new Elementary School site in Riverside County, California. I started out by compiling 5 pieces of key datasets: County Assessor parcel data, California Schools, Fault zones, Roads, and Public sites. First I performed euclidean distance analyses on four of them in order to produce zonal raster for preferred areas. A weighted analysis based on prioritizing safety shows that ideal areas fall within Hemet, Menifee, and Palm Springs Unified School Districts. Final analysis results show how active school sites are distributed, where all vacant parcels of at least 5 Acres or more lie, and recommended areas for a new school site. The two circled were determined to be the most suitable after analyzing results from weighted overlay analyses and locations of parcels. Additional setbacks are anticipated as more conditions are implemented to the list of mandatory criteria needed to finalize parcels. Looking b
Read more