Applied Statistics in Remote Sensing
Applied Statistics in Remote Sensing
Course Description
This course will give students an introduction to the basic elements of probability and statistics. The course will focus on statistical methods in remote sensing and their applications in running statistical analysis. This can be performed through both manual means and software, followed by the interpretation of the analysis results, which lead to decision making in practical cases and examples. By the end of this course, it is accepted that the student will:
Know the concepts and principles of basic statistics;
Understand the need for data collection and summarize data sets into meaningful information;
Execute appropriate statistical procedures and write sound interpretations for use in practical decision-making;
Able to deal with remote sensing applications (problems & projects) statistically.
Be familiar with “R Graphical statistics” software to visualize andinterpret data..
Lectures and Materials
References & Textbooks
The most useful textbooks are:
Ross, S. M. (2014). Introduction to probability and statistics for engineers and scientists Academic Press. https://www.sciencedirect.com/science/book/9780123704832
Stein, A., van der Meer, F. D., Gorte, B. (2006). Spatial statistics for remote sensing (Vol. 1): Springer Science Business Media. https://books.google.iq/books?id= cBnvBwAAQBAJ&dq=statistical+Methods+in+Remote+Sensing&source=gbs_navlinks_s
McCoy, R. M. (2005). Field methods in remote sensing: Guilford Press. https://books.google.iq/books?id=jxalSbaxb6QC&source=gbs_navlinks_s
Bivand, R., Pebesma, E. J., & Gómez-Rubio, V. (2008). Applied spatial data analysis with R. New York: Springer. http://www.asdar-book.org/
O. Schabenberger & C. A Gotway (2005). Statistical Methods for Spatial Data Analysis. Chapman & Hall. https://books.google.iq/books/about/Statistical_Methods_ for_Spatial_Data_Ana.html?id=iVJuVLArmZcC&redir_esc=y