GIS Gazette

 Isarithmic Mapping This week's exercise was hands-on application of isarithmic mapping, using Washington State's annual precipitation data.  Isarithmic mapping is a technique used to illustrate smoothly varying phenomena across a geographical area through the use of isolines- lines that connect points of equal value. The term "isarithmic" is often used interchangeably with "contour mapping," with specific types of isolines named according to the type of data they represent (e.g., isobars for pressure, isotherms for temperature, and contour lines for elevation). This dataset was derived with point data and interpolated using PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM is is an analytical tool that leverages point-specific data and a foundational grid, such as a digital elevation model (DEM) or a 30-year climatological average (for instance, from 1981 to 2010), to create grid-based estimates of monthly and annual precipitation a...

 Choropleth Mapping This module was all about practice using proportional symbol maps. We created a map of European wine consumption per capita using graduated symbols on an overlay of population density. The biggest challenge in this exercise was figuring out how to fit all the elements into the layout without generating conflict between different symbologies. The biggest hack I found to mitigate overlapping labels was the conflict resolution feature in labelling properties. As always, the font choice is custom, and the color scheme is selected with user legibility in mind. The projection used was the  Europe Albers Equal Area Conic projection. This cartographic projection is specifically designed to represent Europe with minimal distortion. It belongs to the family of equal-area conic projections, which means that areas on the map are proportionally accurate, though other properties like shapes and angles may be distorted. Hence, being ideal for modeling European wine consum...

Data Classification   This week, we learned about different data classification techniques, how to calculate them and how/when to implement them in our ArcMaps. The methods used were equal interval, natural breaks (ArcGIS default), quantile, and standard deviation.  The equal interval class system breaks the data classes up into equal ranges. In our census data, the range is 15.83 percentage points. The only advantage that this offers is a set of classes with a comprehensible division, but the large disadvantage is the occurrence of classes with few or no values present. For example, the two middle classes in our census tract data (31.68-47.50 & 47.51-63.33) have no visible presence on the map, leaving out important information that could be used more wisely.  Quantile distributions have the same number of values in each class. This eliminates the empty class problem present in our equal interval distribution, and reveals some more valuable information about the ...

 Module 3: Cartographic Design The objective of this module was to establish a tangible grasp and produce a deliverable using the principles of Gestalt: Visual hierarchy, contrast, figure-ground, and balance. These aesthetic rules dominate the visual arts and are solid guidelines used to create great maps. The lab assignment was to create a map of Washington D.C's Ward 7 neighborhood school district. The most important part was to clearly distinguish elementary, middle, and high schools with unique value hierarchal symbology. The figure implements a strong visual hierarchy, clearly distinguishing elementary, middle, and high school symbology-wise. The information on the map of interest (schools in the area) is clearly conveyed with a strong contrast between the symbology and the basemap. The basemap is subtle enough and light in color so as to not distract the  viewer from the information of focus.  I used a visual hierarchy scheme in my symbology for different school typ...

 Typography: The mega-importance of labelling!  The focus of this module was on aesthetic controls over written information on a map display. We learned various techniques to make information more visually pleasing in ArcGIS, such as annotated labels, and also noted the acceptable time/place for font iterations like italics (water bodies or source info). I learned a lot in this module, and my maps are already looking a LOT better.  We did a map of Florida and labelled county seats, populated places, rivers, and swamps. Note the river labels that curve around water bodies and the customizations in polygon color, fonts and a clean, white base map.