Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)



First Advisor

Warren Hein


Current monitoring of rainfall and soil moistures is being done by ground collected data. This method is time consuming, expensive and impractical for remote regions. A method which could use data for a large area collected from an orbiting platform would greatly ease the task and assist in predicting oncoming droughts and desert expansions. Since the soil temperature is affected by many factors such as vegetation coverage, slope, texture; composition, and soil moisture levels, measurement of soil temperature would then be an ideal method of determining some of these variables. Surface temperature in turn can be monitored by its thermal emittance since thermal emittance is proportional to the surface temperature raised to the fourth power. As stated earlier, a great number of variables affect the surface temperature of the ground. This study was restricted to rainfall, soil moisture, and other variables readily available for use in the model calculations. These other variables include the length of time the ground is exposed to the sun, cultivated vegetation coverage, air temperature, and normalized difference. It is true that more variables can be added to increase the accuracy of the model, but this would not be practical for a remote region where these parameters are not known. Previous experimental and theoretical work on a model to predict surface temperature changes has been done at South Dakota State University. A theoretical heat flow model to predict the soil temperature for a profile from surface to a depth of 50 cm as a function of time was developed. An experimental study to provide qualitative proof of the theoretical model using field collected data showed a good correlation. Further enhancements were done to the original model to include soil characteristics and solar and plant canopy parameters. After a series of experimental calculations, a quadratic relationship between soil moisture and surface temperature resulted. Further experimental work was carried out to determine the effect of these parameters on the model and their significance. Results of this study indicated that these parameters added no significance to the model for the field collected data but resulted in a significant linear relationship between soil moisture and surface temperature. This study was an attempt to use the previous relationships developed between soil moisture and surface temperature and to apply these on a broader scale. Using experimental data collected by satellite and ground collected data for the entire state of South Dakota, a relationship between satellite gathered thermography and ground collected moisture and rainfall data was found. Significant differences between this study and previous studies result from the scope of the data being used (small field plots as compared to the entire state) and the attempt to reverse the model to predict soil moisture, instead of predicting surface temperatures.

Library of Congress Subject Headings

Artificial satellites in remote sensing
Rain and Rainfall -- Measurement
Rain gauges
Soil moisture -- Measurement



Number of Pages



South Dakota State University


No Copyright - United State