Remote Sensing of Forest Environments Concepts and Case Studies

Remote Sensing of Forest Environments: Concepts and Case Studies is an edited volume intended to provide readers with a state-of-the-art synopsis of the current methods and applied applications employed in remote sensing the world's forests. The contributing authors have sought to illustrate an...

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Bibliographic Details
Other Authors: Wulder, Michael A. (Editor), Franklin, Steven E. (Editor)
Format: eBook
Language:English
Published: New York, NY Springer US 2003, 2003
Edition:1st ed. 2003
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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300 |a XV, 519 p  |b online resource 
505 0 |a 19. Tree and canopy height estimation with scanning lidar -- 20. Remote sensing of forest environments, Conclusions. Challenges and opportunities 
505 0 |a Section 1: Data collection and pre-processing -- 1. Remote sensing of forest environments, Introduction. The transition from theory to information -- 2. Selection of remotely sensed data -- 3. The roles of aerial photographs in forestry remote sensing image analysis -- 4. Indirect measurement of forest canopy structure from in situ optical sensors -- 5. Accuracy assessment of maps of forest condition: Statistical design and methodological considerations -- Section 2: Common methods for data processing and information generation -- 6. Geometric correction of remotely sensed images -- 7. Radiometric image processing -- 8. Per-pixel analysis of forest structure: Vegetation indices, spectral mixture analysis and canopy reflectance modeling -- 9. Extracting individual tree information: A survey of techniques for high spatial resolution imagery -- 10. Rationale and conceptual framework for classification approaches to assess forest resources and properties --  
505 0 |a 11. Remote sensing of forests over time: Change types, methods, and opportunities -- Section 3: Case studies illustrating methods and applications for remote sensing of forests -- 12. National scale forest information extraction from coarse resolution satellite data, Part 1. Data processing and mapping land cover types -- 13. National scale forest information extraction from coarse resolution satellite data, Part 2. Forest biophysical parameters and carbon -- 14. Regional forest land cover characterisation using medium spatial resolution satellite data -- 15. Modeling forest productivity using data acquired through remote sensing -- 16. Experiences in field data collection: In support of land use and land cover change classification in boreal and tropical environments -- 17. Estimation of foliar chemistry of western hemlock using hyperspectral data -- 18. Using georeferenced large-scale aerial videography as a surrogate for ground validation data --  
653 |a Geographical Information System 
653 |a Computer vision 
653 |a Forestry 
653 |a Computer Vision 
653 |a Signal, Speech and Image Processing 
653 |a Geographic information systems 
653 |a Signal processing 
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520 |a Remote Sensing of Forest Environments: Concepts and Case Studies is an edited volume intended to provide readers with a state-of-the-art synopsis of the current methods and applied applications employed in remote sensing the world's forests. The contributing authors have sought to illustrate and deepen our understanding of remote sensing of forests, providing new insights and indicating opportunities that are created when forests and forest practices are considered in concert with the evolving paradigm of remote sensing science. Following background and methods sections, this book introduces a series of case studies that exemplify the ways in which remotely sensed data are operationally used, as an element of the decision-making process, and in the scientific study of forests. Remote Sensing of Forest Environments: Concepts and Case Studies is designed to meet the needs of a professional audience composed of both practitioners and researchers. This book is also suitable as a secondary text for graduate-level students in Forestry, Environmental Science, Geography, Engineering, and Computer Science