Masters Thesis

Soil profile development models using geographic information system and satellite image analyses in Mendocino County, California

Point data that are collected during a soil survey are aggregated into conceptual map units and portrayed on maps. There is no extensive geographic method to provide information about the relationships between soil-forming factors and soil properties. These relationships are developed and used intuitively by soil scientists during a soil survey to guide map creation. This project tested the use of statistical modeling techniques and point soil data collected in a National Cooperative Soil Survey project to estimate the functional relationships between soil-forming factors and soil properties. These relationships could help increase efficiency and reduce cost of sampling in adjacent soil survey projects. Point soil data and generalized linear models were used to estimate these relationships. A geographic information system was used to algebraically combine classified soil-forming factor data layers. The resulting maps are a continuous estimation of the probability of the presence of three different soil properties. The probability maps were combined with mapped soils to compare the probabilities to mapped likelihoods of soil properties. One of the models appeared to provide reliable insights into relationships. The other two did not. Additional soil-forming factor data are needed.

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