The Use of Remote Sensing in the Modeling of Forest Productivity

  • Haruhisa Shimoda
  • Henry L. Gholz
  • Kaneyuki Nakane

Part of the Forestry Sciences book series (FOSC, volume 50)

Table of contents

  1. Front Matter
    Pages i-vii
  2. Stand-Level Analyses

  3. Landscape/Regional-Level Analyses

  4. Global-Level Analyses

    1. Front Matter
      Pages 239-239
    2. Samuel N. Goward, Dennis G. Dye
      Pages 241-272
    3. J. J. Landsberg, S. D. Prince, P. G. Jarvis, R. E. McMurtrie, R. Luxmoore, B. E. Medlyn
      Pages 273-298
  5. Back Matter
    Pages 299-326

About this book


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.


Landsat Plantation biochemistry biodiversity biomass chemistry ecosystem forest growth remote sensing simulation vegetation

Editors and affiliations

  • Haruhisa Shimoda
    • 1
  • Henry L. Gholz
    • 2
  • Kaneyuki Nakane
    • 3
  1. 1.Tokai UniversityTokyoJapan
  2. 2.University of FloridaGainesvilleUSA
  3. 3.Hiroshima UniversityHiroshimaJapan

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1997
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-6290-9
  • Online ISBN 978-94-011-5446-8
  • Series Print ISSN 0924-5480
  • Series Online ISSN 1875-1334
  • Buy this book on publisher's site
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