Dr. Pei-Gee Ho's dissertation focuses on the application of satellite and aerial image remote sensing for observing the Earth's surface, land monitoring, and managing geographic information systems. The work discusses the acquisition of information through imaging sensors and spectroradiometers in the form of multispectral image stacks. An innovative 2-D Multivariate Vector AR (ARV) time series model is developed to analyze the temporal relationships between pixels and efficiently compute the parameters of the ARV system matrix as well as the error covariance matrix. Additionally, the powerful Support Vector Machine (SVM) is employed for pixel classification. This dissertation provides valuable insights into the processing and analysis of remote sensing images and is particularly suited for capturing the rich contextual information in single and multiple images.