The Use of Remote Sensing in the Modeling of Forest Productivity

ISBN-13: 9789401062909 / Angielski / Miękka / 2012 / 327 str.

H.L. Gholz;Kaneyuki Nakane;H. Shimoda

Opis

Forests comprise the greatest storage of carbon on land, provide fuel for millions, are the habitat for most terrestrial biodiversity, and are critical to the economies of many countries. Yet changes in the extent and dynamics of forests are inherently difficult to detect and quantify. Remote sensing technologies may facilitate the measurement of some key forest properties which, when combined with other information contained in various computer models, may allow for the quantification of critical forest functions. This book explores how remote sensing and computer modeling can be combined to estimate changes in the carbon storage, or productivity, of forests - from the level of the leaf to the level of the globe. Land managers, researchers, policy makers and students will all find stimulating discussions among an international set of experts at the cutting edge of the interface between science, technology and management.

Recenzje

`The approaches discussed in the book are not limited to forests only they can easily be utilized in evaluation of other types of ecosystems. This is why the book will certainly be highly valuable for a wide range of scientists and land managers.'
Biologia Plantarum, 40:4 (1997/8)

Spis treści

Preface. Section One: Stand-Level Analyses. 1. Assessing Leaf Area and Canopy Biochemistry of Florida Pine Plantations Using Remote Sensing; H.L. Gholz, et al. 2. Modeling Radiative Transfer Through Forest Canopies: Implications for Canopy Photosynthesis and Remote Sensing; T. Nilson, J. Ross. 3. Estimating Forest Canopy Characteristics as Inputs for Models of Forest Carbon Exchange by High Spectral Resolution Remote Sensing; M.E. Martin, J.D. Aber. Section Two: Landscape/Regional-Level Analyses. 4. Detecting Structural and Growth Changes in Woodlands and Forests: The Challenge for Remote Sensing and the Role of Geometric-Optical Modeling; D.L.B. Jupp, J. Walker. 5. Integrating Remotely Sensed Spatial Heterogeneity with a Three-Dimensional Forest Succession Model; J.F. Weishampel, et al. 6. Combining Remote Sensing and Forest Ecosystem Modeling: An Example Using the Regional HydroEcological Simulation System (RHESSys); J.C. Coughlan, J.L. Dungan. 7. Forest Vegetation Classification and Biomass Estimation Based on Landsat TM Data in a Mountainous Region of West Japan; N.J. Lee, K. Nakane. 8. Forest Structure and Productivity Along the Oregon Transect; D.L. Peterson. 9. Use of Remote Sensing to Model Land Use Effects on Carbon Flux in Forests of the Pacific Northwest, USA; D.O. Wallin, et al. Section Three: Global-Level Analyses. 10. Global Biospheric Monitoring with Remote Sensing; S.N. Goward, D.G. Dye. 11. Energy Conversion and Use in Forests: An Analysis of Forest Production in Terms of Radiation Utilisation Efficiency (epsilon); J.J. Landsberg, et al. Color Plates. Index.