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Mathematical Principles of Remote Sensing: Making Inferences from Noisy Data
 
 
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Mathematical Principles of Remote Sensing: Making Inferences from Noisy Data (Hardcover)

by Andrew S Milman (Author) "Few of us who live in cities ever see the stars in a dark night sky..." (more)
Key Phrases: unregularized solution, noiselike components, foreground gas, New York, Cambridge University Press, Mathematical Principles of Remote Sensing (more...)
4.0 out of 5 stars  (2 customer reviews)

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Product Description
Mathematical Principles of Remote Sensing is an informative reference, or working textbook, on the mathematics, and general physical and chemical processes behind remote sensor measurements. The issues and mathematical principles important to remote sensing and data analysis are covered extensively, including measurements and noise, physics of electromagnetic radiation, and radiation transfer. Specific mathematical methods include covariance and probability analysis, regression, linear algebra, Fourier transforms, convolution, and others. This book is an essential reference for remote sensing scientists and engineers concerned with applications in radiation transfer, image processing, atmospheric and noise correction, and modelling.

Product Details
  • Hardcover: 406 pages
  • Publisher: CRC (March 1, 2000)
  • Language: English
  • ISBN-10: 1575041359
  • ISBN-13: 978-1575041353
  • Product Dimensions: 10.2 x 7 x 1.2 inches
  • Shipping Weight: 2.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  (2 customer reviews)
  • Amazon.com Sales Rank: #1,897,716 in Books (See Bestsellers in Books)
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  • In-Print Editions: Kindle Edition (Kindle Book) |  All Editions


Inside This Book (learn more)
First Sentence:
Few of us who live in cities ever see the stars in a dark night sky. Read th