Q's GIS Journey

 Our objective in this lab was to map Washington State's annual precipitation data using continuous tone symbology and hypsometric tinting with contours to illustrate the elevation. The data was derived from PRISM. PRISM starts with a large set of climate observations from thousands of monitoring stations. For precipitation, these are daily, monthly, or annual measurements from rain gauges. Precipitation patterns are highly influenced by elevation. PRISM incorporates a high-resolution digital elevation model (DEM) to guide its interpolation, modeling how precipitation increases or decreases with elevation based on local terrain. PRISM accounts for slope and aspect, coastal proximity, rain shadows, and temperature/humidity gradients. For time-series data, PRISM interpolates and smooths over time as well, ensuring consistency from month to month or year to year. It often uses a long-term climate normal (1981–2010) to help constrain short-term estimates.We used the Int tool to develop...

           Module 5 was about Choropleth and Proportional Symbol Mapping. The map we made this week showcases the population density of Europe population alongside their consumption of wine. I choose to use graduated symbology for the wine consumption as I had a hard time adjusting the size of the proportional symbols individually.  I choose Natural Breaks because it handles skewed or unevenly distributed data better than equal intervals or quantiles. Natural breaks help highlight extreme urban areas without forcing uniform groupings. It also effectively group data by identifying natural clusters and maximize differences between classes. Natural breaks also look the best visually out of all the schemes. I choose a green color ramp as it remind me of the grapes growing on the vineyards. I choose purple symbols because it reminded me of the color of wine.           For the map, I choose to omit countries with less than 2500 ...

           This module focus on learning the 4 common data classification methods: Quantile, Equal Interval, Standard Deviation, and Natural Breaks. By using one dataset but 4 different classification method, the dataset can be visualized differently. Below is how I interpreted the 4 classification methods.           Equal Interval divides a range of data values into equal-sized intervals (based on how many classes are given). It is excellent for uniform distributed data where values are spread out evenly. Extreme values are placed in the lowest or highest class. This can hide some values if some are not evenly distributed.            Quantile classifications divide a dataset into classes with the same number of data points, regardless of actual values in those data points. This ensures each class has the same number of data points, which can be beneficial for data that is evenly distributed. ...

            This week, Module 3 was focused on basic Cartographic Design principles. Some of the learning outcomes were to establish a visual hierarchy to emphasize important map features, apply contrast, employ figure-ground, and ultimately achieve map balance. This map was created in ArcGIS Pro with data from District of Columbia Open Data. Some of the tools I learned to use in this lab were the curve text, more SQL Queries, the dissolve tools to make better-looking roads, and the clip tool to only display schools in Ward 7.            To implement a visual hierarchy, I used several components. The title is the largest text on the map, in bold black with a white outline, making it prominent and eye-catching and introducing the map primary purpose, this is where the viewer naturally look first. The school symbols uses a visual hierarchy by using a more distinct red color to stand out against the pale white and gray b...

          This lab focuses on typography and specifically how to properly label point features in ArcGIS Pro. We used ArcGIS Pro in this lab to make a map of Florida's major cities, rivers, and swamps/marshes with the provided data from UWF. We learned to use 3 different ways to make labels via symbology, annotation, and the labeling tab. I choose to use a vanilla color for the counties as it is what I am used to seeing in traditional old maps. I learned that italics often mean "flowing" so it should be used for rivers. I learned that it is very important to carefully choose font and their sizes as it affect the legibility of your map.            For the customization, I made the following choices. For the river labeling, I made them bold italic and made the font blue. I also converted it into annotation so I can further edit “Suwannee River” to move into a better position. I used SQL Query to further only highlight t...