Remote Sensing of Forest Environments

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.- 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.- 19. Tree and canopy height estimation with scanning lidar.- 20. Remote sensing of forest environments, Conclusions. Challenges and opportunities.