The semester is accelerating and we move into the 6th lab covering Isarithmic Mapping! Following choropleth mapping, this thematic map type is the second most widely used in cartography. Isarithmic maps consider geographic phenomenon to be continuous and smooth, with measurements in the area of interest presumed to change gradually between data point locations instead of abruptly. There are two primary types of isarithmic mapping.
Often associated with meteorology, isometric maps depict smooth, continuous phenomenon, such as temperatures, rainfall, barometric pressure and wind velocity derived from data occurring at true points where values are actually measured at that location. The most common form of isometric maps are contour maps, which are lines marking equal value across a geographical area.
Collectively, contours used in isometric maps can be referred to as isolines. Iso in Latin means equal or the same. Variations of isoline terminology include isobars for lines of equal barometric pressure, isotherms for lines of equal temperature and isodrosotherms for lines of equal dew point.
Isopleth maps are comprised from data that occurs over geographic areas using conceptual points, where values are presumed to be at point locations. Isopleth maps show variations in quantity of features as a surface. The volume can be represented using contour lines or by filled contours with color shading representing quantitative values. Data for isopleth maps must be standardized to account for the area in which the data was collected.
Various interpolation methods on raster data sets are implored in the creation of isopleth maps. These methods generate data values over a given area using samples measured at control points. An algorithm in turn processes the data to predict the values of unknown points on an isopleth map. Values between the control points are predicted under the premise that spatially distributed objects are spatially correlated. Also referenced as the Concept of Spatial Auto Correlation, this basis of interpolation assumes that values of locations close together tend to share similar characteristics than those located farther apart.
The focus of lab this week is the creation of an isopleth map showing the average annual precipitation for a 30 year period across the state of Washington. The provided dataset was derived using PRISM, an inverse distance weight (IDW) interpolation method developed by the University of Oregon.
The Parameter-elevation Regressions on Independent Slopes Model (PRISM) stresses elevation as the most important aspect in a localized region for the distribution of climate variables such as rainfall, temperature and dew point. The model calculates a climate-elevation relationship for each cell of a raster data set based upon data from nearby weather stations. The regression function used with the IDW method weights station data points to incorporate a wide range of physiographic variables that have a direct correlation with precipitation amounts and other climatological aspects.
Two types of isarthmic maps were created in Lab 6. The first was a continuous tone map, where geographic surfaces represent the values that exist across an entire area. Data collected at sample points, by mapping the density of points or the values they represent, factor into the interpolation that generates the continuous surface. This method portrays a more fluid appearance where data values in a raster set gradually transition from cell to cell.
The second was Hypsometric Tint, which reminds of me of the Futurama character the Hypnotoad, that classifies data into bands. These bands represent a method of coloring different values to enhance changes, such as in elevation with a Digital Elevation Model (DEM).
Using contours, hypsometric tint separates raster data into bands with uniform data values. These bands can represent a single value, or a range of values with lower and upper limits. An advantage of hypsometric tint is that changes in data are more clearly visualized over the smooth transitions of a continuous tone map. A drawback is that local variation of data values is lost with the generalization between contours.
Reprojecting the Washington precipitation data into State Plane coordinates, I ran through the lab again to create a second map showing Washington in a more aesthetically pleasing projection. This both gave me more practice with creating continuous tone and hypsometric tint maps, but also some of the difficulties with projecting data, as the hillside shading values changed from using world statistics to local statistics.
PRISM
PRISM was initially developed in 1991. Enhancements over time garnered the interest of the USDA Natural Resources Conservation Service (NRCS), which sought improvements for updated digital precipitation maps. With funding support, PRISM precipitation maps were generated for the Pacific Northwest and Intermountain West region of the U.S., where topographic features made mapping precipitation complex.
State Climatologists evaluated the maps produced by PRISM, offering their own suggestions for improvements. Following two years of trial and error, they concurred that PRISM produced maps equaling or exceeding previous ones produced by hand. The result is that the NRCS utilized PRISM to map averages for temperature and precipitation nationwide for the period from 1961 to 1990.
Sources:
Daly, C., & Bryant, K. (n.d.). The PRISM Climate and Weather System – An Introduction. University of Oregon. Retrieved April 20, 2024, from https://www.prism.oregonstate.edu/documents/PRISM_history_jun2013.pdf
The Hypnotoad may or may not approve of hypsometric tint!
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