Fundamentals of Remote Sensing and Geospatial Analysis
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | Lec: 19 | 245 MB
Genre: eLearning | Language: English

Become proficient in satellite remote sensing, spatial analysis principles, methods, applications, sensors, and GIS!

MASTER THE FUNDAMENTAL PRINCIPLES OF REMOTE SENSING AND GEOSPATIAL ANALYSIS!

Do you find that other remote sensing courses are too short and vague, and do not prepare you for real world problems? Are you looking for a course that goes IN-DEPTH and teaches you all the fundamentals of remote sensing?

My course provides a solid foundation to carry out practical, real life remote sensing spatial data analysis and gives you the techniques and knowledge to tackle a variety of geological and environmental problems.

This course provides an introduction to remote sensing - the acquisition of information about the earth from a distance, typically via airborne and spaceborne sensors. The abundance of earth observation data allows us to address many pressing environmental, geographical, and geological issues. This course will prepare the students for the basics of using remote sensing data.

Students will have a solid understanding of the physical principles of remote sensing, including electromagnetic (EM) radiation concepts, and will also explore in detail the interaction of EM radiation with the atmosphere, water, vegetation, minerals, and other land types from a remote sensing perspective. We will go over various industries where remote sensing can be used including agriculture, geology, mining, hydrology, forestry, environmental, and many more!

The students will also learn about current satellite sensor platforms for remote sensing analysis including passive senors, synthetic aperture radar, and LiDAR. In addition to learning the basic concepts, terminology, and theories in remote sensing science and application, they will also learn the accurate steps for pre-processing images including radiometric and atmospheric correction techniques.

Lastly, we will look at how to interpret spectral characteristics from different materials and how to create their own basic equation for using remote sensing images on their own projects in the future.



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