This course provides both theoretical knowledge and practical skills in Geospatial Data Analysis and Visualization on Google Cloud. In this course, you will be given hands on practical exercises to master analyzing big geospatial data on the cloud. You will learn to access, process and analyze satellite data including Landsat, MODIS, and Sentinel and others using an open source platform. You will also learn to classify satellite images using machine learning algorithms. You will also have access to the lab exercise scripts as part of this course.
In this lecture, we will explore the various data types including satellite images, geophysical, climate and demographic data sets on the Google Earth data library.
Dr. Alemayehu Midekisa (PhD) is a research scientist at the University of California San Francisco. He has a Master of Science degree in GIS and Remote Sensing and a PhD in Geospatial Science & Engineering. Dr. Midekisa is also the recipient of the prestigious NASA Earth and Space Science Fellowship and various other awards. He has over 10 years of experience applying geospatial science and technologies in various applications including public health, agriculture, and natural resources.
His research work in the application of geographic information science has been published in various scientific journals. He has presented his research findings in various scientific meetings including the American Geophysical Union, Association of American Geographers, American Tropical and Hygiene and Medicine, and NASA Science Team Meetings. He teaches online courses in various themes including geospatial science and technology. He is also the founder of Nile Geospatial.