Remote Sensing of Natural Resources
eBook - PDF

Remote Sensing of Natural Resources

  1. 580 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Remote Sensing of Natural Resources

About this book

Highlighting new technologies, Remote Sensing of Natural Resources explores advanced remote sensing systems and algorithms for image processing, enhancement, feature extraction, data fusion, image classification, image-based modeling, image-based sampling design, map accuracy assessment and quality control. It also discusses their applications for

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Yes, you can access Remote Sensing of Natural Resources by Guangxing Wang, Qihao Weng in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Civil Engineering. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2013
Print ISBN
9780367867454
eBook ISBN
9781466556935
Edition
1
Topic
Biological Sciences
Subtopic
Civil Engineering
Index
Biological Sciences

Table of contents

  1. Front Cover
  2. Contents
  3. Acknowledgments
  4. Editors
  5. Contributors
  6. Introduction to Remote Sensing of Natural Resources
  7. Chapter 1 - Introduction to Remote Sensing Systems, Data, and Applications
  8. Chapter 2 - Remote Sensing Applications for Sampling Design of Natural Resources
  9. Chapter 3 - Accuracy Assessment for Classification and Modeling
  10. Chapter 4 - Accuracy Assessment for Soft Classification Maps
  11. Chapter 5 - Spatial Uncertainty Analysis When Mapping Natural Resources Using Remotely Sensed Data
  12. Chapter 6 - Land Use/Land Cover Classification in the Brazilian Amazon with Different Sensor Data and Classification Algorithms
  13. Chapter 7 - Vegetation Change Detection in the Brazilian Amazon with Multitemporal Landsat Images
  14. Chapter 8 - Extraction of Impervious Surfaces from Hyperspectral Imagery: Linear versus Nonlinear Methods
  15. Chapter 9 - Road Extraction: A Review of LiDAR-Focused Studies
  16. Chapter 10 - Application of Remote Sensing in Ecosystem and Landscape Modeling
  17. Chapter 11 - Plant Invasion and Imaging Spectroscopy
  18. Chapter 12 - Assessing Military Trainingā€“Induced Landscape Fragmentation and Dynamics of Fort Riley Installation Using Spatial Metrics and Remotely Sensed Data
  19. Chapter 13 - Automated Individual Tree-Crown Delineation and Treetop Detection with Very-High-Resolution Aerial Imagery
  20. Chapter 14 - Tree Species Classification
  21. Chapter 15 - Estimation of Forest Stock and Yield Using LiDAR Data
  22. Chapter 16 - National Forest Resource Inventory and Monitoring System
  23. Chapter 17 - Remote Sensing Applications on Crop Monitoring and Prediction
  24. Chapter 18 - Remote Sensing Applications to Precision Farming
  25. Chapter 19 - Mapping and Uncertainty Analysis of Crop Residue Cover Using Sequential Gaussian Cosimulation with QuickBird Images
  26. Chapter 20 - Remote Sensing of Leaf Area Index of Vegetation Covers
  27. Chapter 21 - LiDAR Remote Sensing of Vegetation Biomass
  28. Chapter 22 - Carbon Cycle Modeling for Terrestrial Ecosystems
  29. Chapter 23 - Remote Sensing Applications to Modeling Biomass and Carbon of Oceanic Ecosystems
  30. Chapter 24 - Wetland Classification
  31. Chapter 25 - Remote Sensing Applications to Monitoring Wetland Dynamics: A Case Study on Qinghai Lake Ramsar Site, China
  32. Chapter 26 - Hyperspectral Sensing on Acid Sulfate Soils via Mapping Iron-Bearing and Aluminum-Bearing Minerals on the Swan Coastal Plain, Western Australia
  33. Back Cover