Satellite Remote Sensing of Natural Resources offers an introduction to digital remote sensing. This comprehensive text emphasizes the basics, with simple concepts presented in clear, easy-to-understand language. For those who are interested in practical remote sensing but do not have an extensive background in math and statistics, this primer is invaluable. The main topics covered include satellite images, image processing systems, spectral regions, radiometric and geometric corrections, supervised and unsupervised classification, and accuracy assessment. Each chapter concludes with a section of sample problems and list of additional readings.
FREE Two-Day Shipping for Students. Learn more |
Book Description
Special Offers and Product Promotions
- Buy $50 in qualifying physical textbooks, get $5 in Amazon MP3 Credit. Here's how (restrictions apply)
Product Details
Would you like to update product info or give feedback on images?
|
More About the Author
Discover books, learn about writers, read author blogs, and more.
Customer Reviews
|
There are no customer reviews yet.
|
|||
|
Video reviews
|
Inside This Book
(learn more)
First Sentence:
A digital satellite image consists of a grid of numbers (Figure 1.1). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
ground control pixels, new class centers, histogram adjustment technique, coniferous forest leaf area index, ground control locations, spectral class mean, rectification models, video intensities, spectral distance, panoramic distortion, pushbroom scanning, resemblance matrix, candidate pixel, classification accuracy assessment, classified image, video intensity, parallelepiped classifier, rectified image, spectral classes, map interpolation, digital classification, line dropout, spectral relationships, skip factor, print shade Key Phrases - Capitalized Phrases (CAPs): (learn more)
Remote Sensing of Environment, International Journal of Remote Sensing, Additional Readings, Geocarto International, United States, Universal Transverse Mercator, Canadian Journal of Remote Sensing, Pixel Digital Value, Geological Survey, Mean Band, General Readings, Grouping Based, Red Band, Geologic Survey, Green Band, Journal of Forestry, Remote Sensing of the Environment, Scientific American New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
A digital satellite image consists of a grid of numbers (Figure 1.1). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
ground control pixels, new class centers, histogram adjustment technique, coniferous forest leaf area index, ground control locations, spectral class mean, rectification models, video intensities, spectral distance, panoramic distortion, pushbroom scanning, resemblance matrix, candidate pixel, classification accuracy assessment, classified image, video intensity, parallelepiped classifier, rectified image, spectral classes, map interpolation, digital classification, line dropout, spectral relationships, skip factor, print shade Key Phrases - Capitalized Phrases (CAPs): (learn more)
Remote Sensing of Environment, International Journal of Remote Sensing, Additional Readings, Geocarto International, United States, Universal Transverse Mercator, Canadian Journal of Remote Sensing, Pixel Digital Value, Geological Survey, Mean Band, General Readings, Grouping Based, Red Band, Geologic Survey, Green Band, Journal of Forestry, Remote Sensing of the Environment, Scientific American New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 10
books:
See all 10 books this book cites
4
books
cite this book:
- Remote Sensing: Symposium Proceedings by G. K. C. Pardoe on 4 pages
- Remote Sensing: Technique for Environmental Analysis by John E. Estes on page 12, and page 13
- Remote Sensing (Treatise of Petroleum Geology Reprint, No. 19) by Edward A. Beaumont on page 65
- Aerial Mapping: Methods and Applications, Second Edition (Mapping Science) by Dennis Morgan in Front Matter
- Remote Sensing of Forest Resources: Theory and application (Remote Sensing Applications) by J.A. Howard on page 64
See all 10 books this book cites
- Introduction to Environmental Physics: Planet Earth, Life and Climate by Peter Hughes on page 195, and Back Matter
-
Forest Ecosystems, Second Edition: Analysis at Multiple Scales
by Richard H. Waring B.S. 1957 Forestry University of Minnesota St. Paul MN
M.S. 1959 Forestry (Botany) University of Minnesota
Ph.D. 1963 Botany (Soils) University of California Berkeley in Back Matter - Assessing the Accuracy of Remotely Sensed Data: Principles and Practices (Mapping Science) by Russell G. Congalton in Front Matter
- Wetland and Environmental Applications of GIS by John G. Lyon in Front Matter
Books on Related Topics
(learn more)
|
Tag this product(What's this?)Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items. |
Sell a Digital Version of This Book in the Kindle Store
If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store.
Learn more
Customer Discussions
|
This product's forum
Active discussions in related forums
Search Customer Discussions
|
Related forums
|
Listmania!
So You'd Like to...
Look for Similar Items by Category
- Books > Business & Investing > Popular Economics
- Books > New & Used Textbooks > Science & Mathematics > Earth Sciences
- Books > New & Used Textbooks > Science & Mathematics > Environmental Studies
- Books > Professional & Technical > Engineering
- Books > Science & Math > Earth Sciences > Cartography
- Books > Science & Math > Earth Sciences > Environmental Science
- Books > Science & Math > Earth Sciences > Geography
- Books > Science & Math > Earth Sciences > Geology
- Books > Science & Math > Environment
- Books > Science & Math > Nature & Ecology > Conservation
