Quantifying the Aspect Effect: An Application of Solar Radiation Modeling for Soil Survey

Aspect angle is commonly used by soil scientists and ecologists as a qualitative proxy for landscape-scale variation in microclimate and microclimate-induced phenomena. This property of the landscape is simple to measure in the field and has a direct interpretation. Aspect angle is not easily integrated into more quantitative, physically based measures of landscape-scale phenomena, however, because (i) solar geometry, not aspect angle, drives near-surface processes, and (ii) there are numerical difficulties associated with periodic variables. We used the European Solar Radiation Atlas solar radiation model to generate an annual radiation load surface for subsequent modeling of microclimate-coupled near-surface processes at Pinnacles National Monument in California. Estimated annual solar radiation load values coupled with a local geologic map were used as predictor variables in a logistic regression model constructed to predict the spatial distribution of upland Mollisols. A total of 185 field observations were used to build the model, which had an 83 percent correctly classified (PCC) rate and a receiver operating characteristic (ROC) area of 0.78 to 0.96. A 50-fold cross-validation (repeated refitting of the model with a subset of observations) procedure indicated a mean classification error rate of 22%. Solar radiation modeling offers an exciting new approach for linking geographic information system and field observation in regions where microclimate-coupled soil-forming factors dominate pedogenesis. In addition, the quantification of a previously qualitatively described phenomena (the aspect effect) leads to a continuous description of soil taxonomic features at a much finer scale than is currently possible in soil survey.

[1]  W. Kruskal Ordinal Measures of Association , 1958 .

[2]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[3]  C. E. Rogers,et al.  Symbolic Description of Factorial Models for Analysis of Variance , 1973 .

[4]  Ian Reid,et al.  The influence of slope orientation upon the soil moisture regime, and its hydrogeomorphological significance , 1973 .

[5]  P. G. Holland,et al.  Vegetational responses to latitudinal variations in slope angle and aspect , 1975 .

[6]  V. Matthews Correlation of Pinnacles and Neenach Volcanic Formations and Their Bearing on San Andreas Fault Problem , 1976 .

[7]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[8]  Jamie B. Kirkpatrick,et al.  Vegetation-radiation relationships in mountainous terrain: eucalypt-dominated vegetation in the Risdon Hills, Tasmania , 1980 .

[9]  J. Duffie,et al.  Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation , 1982 .

[10]  A. Louche,et al.  An analysis of Linke turbidity factor , 1986 .

[11]  A. Louche,et al.  Determination of Ångström's turbidity coefficient from direct total solar irradiance measurements , 1987 .

[12]  W. Beckman,et al.  Diffuse fraction correlations , 1990 .

[13]  W. Schlesinger Biogeochemistry: An Analysis of Global Change , 1991 .

[14]  A. de La Casinière,et al.  A spectral model of Linke's turbidity factor and its experimental implications , 1994 .

[15]  F. Kasten The linke turbidity factor based on improved values of the integral Rayleigh optical thickness , 1996 .

[16]  R. Schaetzl,et al.  Spodosol development as affected by geomorphic aspect, Baraga County, Michigan , 1997 .

[17]  A. Rapti Atmospheric transparency, atmospheric turbidity and climatic parameters , 2000 .

[18]  G. Pope Soils and Geomorphology, 3rd edn , 2000 .

[19]  L. Wald,et al.  On the clear sky model of the ESRA — European Solar Radiation Atlas — with respect to the heliosat method , 2000 .

[20]  M. Cucumo,et al.  A calculation method for the estimation of the Linke turbidity factor , 2000 .

[21]  D. Hendricks,et al.  The influence of slope aspect on soil weathering processes in the Springerville volcanic field, Arizona , 2001 .

[22]  S. R. Jammalamadaka,et al.  Topics in Circular Statistics , 2001 .

[23]  R. Gil Pontius,et al.  Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA , 2001 .

[24]  Lucien Wald,et al.  The European Solar Radiation Atlas: a valuable digital tool , 2001 .

[25]  Sunil J Rao,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .

[26]  W. Daniels,et al.  Soil organic carbon content in frigid southern Appalachian mountain soils , 2004 .

[27]  Kenneth B. Pierce,et al.  A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis , 2005, Landscape Ecology.

[28]  Randall J. Schaetzl,et al.  Soils: Genesis and Geomorphology , 2005 .

[29]  Randall K. Kolka,et al.  Soil carbon storage estimation in a forested watershed using quantitative soil-landscape modeling. , 2005 .

[30]  D. J. Brus,et al.  Sampling for Natural Resource Monitoring , 2006 .

[31]  V. D. Assimakopoulos,et al.  Comparative study of various correlations in estimating hourly diffuse fraction of global solar radiation , 2006 .

[32]  Tom Fawcett,et al.  ROC Graphs: Notes and Practical Considerations for Researchers , 2007 .