Learners enrolled: Remote sensing RS is the technology that helps to gather information about objects and phenomena from a distance. The advancement in sensors and data processing algorithms have led to multiple applications of RS in various domains. To perform quantitative RS, one must understand the basic nature of RS sensors, the interaction between electromagnetic radiation and earth surface features and the assumptions and limitations of the algorithms applied.
This course will enable the participants to learn about the necessary physical concepts involved in different phases of RS which will help in better appreciation of algorithms and existing datasets.
The concepts will further be strengthened through explanation of selected applications. Course layout Week 1: Introduction, electromagnetic radiation, basic laws. Week 3: RS in visible and IR domain: Radiance to reflectance, atmospheric and topographic correction.
NOTE Includes bibliographical references p. Richards, J. NOTE Includes bibliographical references and index. LAB 0. Installation instructions. LAB 1. Electromagnetic radiation, polarization. Rees 2.
GPS and the Ionosphere Fourier transform introduction. LAB 2. Thermal radiation. Spectra and Fourier transforms Diffraction. LAB 3. Data Types. Propagation, dispersion, and scattering.
Rees 3. Image processing - 1. LAB 4. Google Earth. Image Processing - 2 Optics, stereo. Rees 5. Image classification Machine learning. LAB 5. Image Processing. Review and go over HW The remainder of the book covers five possible types of remote sensing of the earth from space where the main limitations are: the transparency of the atmosphere and ionosphere to electromagnetic waves; the space—time sampling that is possible from an orbiting sensor; and the types of sensors—passive or active.
Chapter 5 covers passive optical sensors with a focus on the underlying concepts of resolution, focal length, field of view and stereo imaging. This chapter provides the essential geometry without getting bogged down on all the engineering of these complex cameras in space.
Chapter 6 on electro-optical systems introduces the concepts of viewing the Earth in multiple wavelength bands. The main windows are in the visible and thermal infrared. Multi- and hyper-spectral sensors add a third dimension to imaging the Earth that can be used to investigate properties such as vegetation on land or chorophyll in the ocean.
This chapter also includes a nice discussion of the physical principles behind diurnal and seasonal changes in land, ocean and ice temperature. Nice but non-essential colour figures are also imbedded in this chapter but more important they are available on the Cambridge University Press web site for use in preparing lectures.
Chapter 7 discusses passive microwave systems, which have low spatial resolution because of the longer wavelength radiation, but are highly sensitive to temperature and emissivity, so they are excellent for decadal monitoring of sea ice cover and ocean surface temperature. Chapter 8 covers laser and radar altimeters—nicely explaining the strengths and weaknesses of each system in terms of surface type i.
Chapter 9 is a brief overview of the physical principles of active microwave systems such as scatterometers for measuring ocean winds, synthetic aperture radars for all-weather, day—night, high-resolution imaging of land, ocean and ice and radar interferometry for mapping topography and surface deformation.
Chapter 10 covers platforms used for remote sensing and is primarily focused on satellite orbits. This chapter assumes that the reader is familiar with the laws of Newton and Kepler, and then provides just the essential orbital dynamics and kinematics to understand concepts such as geosynchronous orbits, sun synchronous orbits and the need for highly precise orbits for active remote sensing instruments.
One of the highlights of the book is Chapter 11 on data processing. This chapter covers the basics of image processing e.
All of this material can be presented in two class lectures and a Matlab exercise so that students can understand the concepts behind more sophisticated remote sensing software packages. In summary, this is an excellent book for an introductory course in Satellite Remote Sensing appropriate for students with strong backgrounds in the physical sciences or engineering.
The mostly mathematical homework exercises at the end of each chapter are well designed to help the student understand physical principles. The book does not cover any particular applications in detail and I commonly have the graduate students in the class write a remote sensing term paper related to their research topic.
I highly recommend this book to any advanced student or researcher who wants to learn the basics of satellite remote sensing as a foundation to more advanced remote sensing books on particular methods. Oxford University Press is a department of the University of Oxford.
It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.
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