GIS 5007 Module 6 - Isarithmic Mapping

 Module 6 of Cartography was based on Isarithmic Mapping. Isarithmic mapping differs from the other types of maps created in this course because it uses raster-based datasets. Raster-based datasets are pixel arrays, arranged in a grid pattern, where each pixel contains a data value. Therefore, each pixel can be individually mapped; this is why raster-based datasets are also called continuous data. Previously, this course has focused on vector datasets, which are comprised of points, lines, and polygons. 

To create raster-based datasets, sample data is taken at specific geographic points [stations] and the areas in between are filled in [interpolated] using various algorithmic methodologies. Essentially, this provides a mathematical estimate for the areas that lie between sampling stations, because it would be impossible to collect data [precipitation amounts in the state of Washington for this exercise] at every geographical point. For the Module 6 lab, we were given a data set that was created by the PRISM [Parameter-elevation Relationships on Independent Slope Model] Group, located out of Oregon State University; this data set included annual precipitation amounts for the state of Washington from 1981 through 2010. For background context, PRISM, unlike conventional interpolation methods, incorporates a regression function into each data cell that considers physiological characteristics of that geographic location, such as elevation, coastal proximity, and other factors. This provided a more accurate interpolated precipitation map than what was previously drawn by hand, and the PRISM model has been continuously evolving, and improving, since its initial introduction in 1991. 

Using ArcGIS Pro, the first half of this exercise was to map the dataset using continuous tones. This means that instead of creating classes of data ranges, there is a continuous color "ramp" between the highest data value and the lowest; each pixel's data value can fall anywhere on the spectrum between the highest and lowest data values. While this method is more accurate on a pixelated basis, it will only give a generalized estimate when viewed with the naked eye.

The second half of this exercise was to map the dataset using hypsometric tinting [using ArcGIS Pro]. This method employs the use of data classes where each pixel falls within the range of a single data class. Each data class is attributed to a different color, allowing the user to easily identify which range each pixel belongs. We also used a geoprocessing tool that created contour lines which outlined each of these data classes, further defining that boundaries of each area. While this method is not as accurate as using continuous tones, it does allow a quicker analysis by giving the user a generalized range in which the data for each area lies. 

This lab exercise was very straightforward, and no issues were encountered during the cartographic process. It was a great opportunity to use various tools included in the ArcGIS Pro software platform, including Hillshade Function, INT Tool, and the Contour List Tool. I was very pleased with the created deliverable, and believe that it effectively portrays the information in an aesthetically pleasing manner. 

Source:

     Daly, C., & Bryant, K. (2013). The PRISM Climate and Weather System—an Introduction. Corvallis, OR: PRISM Climate Group, 2.