Gholz

The Use of Remote Sensing in the Modeling of Forest Productivity

Herausgeber: Gholz, Henry L; Shimoda, H.; Gholz, H L; Nakane, Kaneyuki; Shimoda, Haruhisa

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Springer Nature Singapore / Springer Netherland
• Seitenzahl: 340
• Erscheinungstermin: 1. Januar 1997
• Englisch
• Abmessung: 241mm x 160mm x 24mm
• Gewicht: 676g
• ISBN-13: 9780792342786
• ISBN-10: 079234278X
• Artikelnr.: 21082990

Inhaltsangabe

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.