Hans Edwin Winzeler, Purdue University,
withZamir Libohova (National Soil Survey Center, NRCS) and Phillip R. Owens (Associate Professor of Agronomy, Purdue University)
The purpose of our project is to provide a continuous classification of climate and a method for visualization of complex information using three color ramps combined in one red-green-blue visualization. We hope to provide a method of visualizing climate that can be used in models of soil moisture, wetland preservation, species diversity efforts, and other natural resource management tasks. A continuous classification avoids discreet boundaries, which often do not exist in nature.
The use of three colors in the visualization allows three values to be displayed congruently for each raster cell, thus allowing for a full range of color output, wherein an output color has an associated level of magnitude of the three colors of which it is composed. Because almost all colors can be depicted as some combination of intensities of red, green, and blue, our method allows for a very wide range of depiction of three values that are interrelated in a computationally complex, yet intuitive display. We chose to display temperature, rainfall, and seasonality (a Mediterranean index that measures the strength of annual precipitation imbalance) using red, green, and blue. These measurements have traditionally played an important role in the understanding and classification of climate. We first applied a standard deviation histogram stretch (n=2) to allow for greater visualization of contrasts between high and low ranges of the histogram of values. We then combined red, green, and blue rasters into a single climate raster for visualization.
The climate inputs will be applied to the Newhall Simulation Model -- which is a detailed simulation of soil moisture -- in order to estimate soil moisture for the coterminous U.S. at multiple scales. We are actively involved in modeling efforts to use PRISM climate data as inputs into soil moisture simulations. The understanding of soil moisture has important implications for wetland conservation, species diversity and management, and many other natural resource planning and management decisions. We are developing visualizations and estimates of soil moisture that can be used by natural resource planners at multiple scales.
It is our hope that discreet categories of climate difference can be surpassed in favor of more complex visualizations, such as what we provide here, allowing viewers to grasp greater complexity and nuance with a higher degree of accuracy than they would be able to given a choropleth map, or a map of isolines of climate variables. We also believe that increasing the complexity of visualization of maps does not lead to increasing the difficulty of understanding. Using choropleth classifications of climate, such as those of Koppen, with discree categories, requires detailed documentation of those categories, as well as conceptual realization by map users. Continuous classifications can consist of measured values, such as 30-year climate inputs, on a pixel-by-pixel basis that can be more meaningful and, we believe, easier to interpret. Continuous classification also avoids implied abrupt boundaries between natural zones that may, in reality, have gradual boundaries.