depth-function aggregated mean +- 1 standard deviation

linear model (piece-wise splines), conditioned by clay content, fit + 95% CI

linear model (piece-wise splines) fit + 95% CI

Examples with Some Real Data

 
Notes:

• See attached files at bottom of page

Premise

Soil color generally varies in a predictable pattern with depth according to surface vegetation, clay mineralogy and parent material. Highly contrasting parent geology influences soil color within Pinnacles via four main processes:

1. Original color of parent material
   sedimentary sources: grey, yellow, white
   granitic sources: yellow to orange
   volcanic sources: pink, orange, white, green
2. Landscape age
   older landscapes generally have redder hues (Fe-expression) from longer chemical weathering
3. Particle size distribution of parent material and the resulting field capacity of a soil formed from it
   coarse textures result in lower field capacities, limiting vegetation growth and subsequent accumulation of organic matter in the surface horizons
4. Weathering rate of parent material
   sedimentary materials derived from granitic sources (grey to yellow hues) have high levels of quartz and are therefore less susceptible to chemical weathering than volcanic rocks (redder hues)

 
Overview
Google Earth provides a flexible and open ended vizualization system for geographic data. We intend to present PINN soils data thorugh our own, 2 dimensional, interface (to avoid dependence on a quasi-free setup like GE). However, there are considerable extra features that can be added onto our presentation of the data through GE. For example, synthesized pedon data, photographs, and even geologic diagrams can be presented to the user in a 3D environment with little work on our end: we have the data, GE does the hard work of presenting it in 3D. Some early examples of what this might be like, along with links to the actual data, are presented below. Download GE and our data to give it a try for yourself.

Misc. scanned images from work at the Pinnacles National Monument, in collaboration with the NRCS and NPS. These images are the prototypes for many of the new educational materials being developed for the visitor's center and online interface to soils information. Over 300 pit descriptions were collected by NRCS staff and myself, and are currently being digitized with our own pedon management system, PedLogic. Numerous techniques for the automation of soil survey operation, digitial soil mapping, and field assistance are currently in development. Many of the detailed features which will not appear in the final soil survey product will be featured in bulletins written up for the PINN interpretive staff. It is our goal to assist the park staff in communicating the importance of soil resources as the active junction between the biosphere and the lithosphere. GIS tools used include: GRASS, PostGIS, R, GMT, and many others. A digital version of the pedon description form illustrates some of the visualization capabilities of PedLogic.

Hierarchical clustering methods can be used to create a series of nested groupings of data based on the interplay between variables associated with an observation.

Figure 1: Munsell color chips.

Figure 2: Common soil colors.

Figure 3: Commom soil colors in RGB.

Figure 4: Soil colors in multiple color spaces

Figure 5: Soil profile colors.

The Munsell color system was designed as a series of discrete color chips which closely approximation to the color sensitivity of the human eye. The description of color via three variables tied to perceptible properties (hue, value, and chroma) under a standardized illuminant (sunlight on a clear day) makes the Munsell system a good choice for recording and interpreting soil color data. However, numerical analysis of colors encoded in the Munsell system is difficult because they are from a discrete set of color chips and referenced by values that include both letters and numbers. Rossel et. al. (2006) give a good background on various color space models and their relative usefulness in the realm of soil science. The conversion of Munsell soil colors to RGB triplets, suitable for displaying on a computer screen or printing, is made complicated by the numerous operations involved in converting between color spaces. Figure 1 shows all possible (both real and unreal) Munsell color chips in the L*U*V color space. Figure 2 shows some of the common soil color chips in the same color space. Figures 2 through 5 depict common soil colors in the RGB color space, visualized both in R and POVRAY. Example R code on the conversion is given below.