Understanding Forest Disturbance and Spatial Pattern: Remote Sensing and GIS Approaches

by Michael A. Wulder (Editor), Steven E. Franklin (Editor)

Overview

Remote sensing and GIS are increasingly used as tools for monitoring and managing forests. Remotely sensed and GIS data are now the data sources of choice for capturing, documenting, and understanding forest disturbance and landscape pattern. Sitting astride the fields of ecology, forestry, and remote sensing/GIS, Understanding Forest Disturbanc

Product Details

ISBN-13:	9781040198797
Publisher:	CRC Press
Publication date:	07/27/2006
Sold by:	Barnes & Noble
Format:	eBook
Pages:	246
File size:	6 MB

About the Author

Michael A. Wulder, Steven E. Franklin

Table of Contents

Introduction: Structure, Function, and Change of Forest Landscapes. Identifying and Describing Forest Disturbance and Spatial Pattern: Data Selection Issues and Methodological Implications. Remotely Sensed Data in the Mapping of Forest Harvest Patterns. Remotely Sensed Data in the Mapping of Insect Defoliation. Using Remote Sensing to Map and Monitor Fire Damage in Forest Ecosystems. Integrating GIS and Remotely Sensed Data for Mapping Forest Disturbance and Change. New Directions in Landscape Pattern Analysis and Linkages with Remote Sensing. Characterizing Stand-Replacing Harvest and Fire Disturbance Patches in a Forested Landscape: A Case Study from Cooney Ridge. Conclusion: Understanding Forest Disturbance and Spatial Pattern, Information Needs, and New Approaches. Index.

Editorial Reviews

". . . this book seriously integrates the use of remote sensing and GIS techniques to help forestry researchers, resource management professionals, and conservation biologists meet the challenges of capturing and characterizing forest disturbance and their spatial patterns . . . well-researched and makes a significant contribution to the forestry, remote sensing and landscape ecology bodies of literature."

– Kin M. Ma, Geography and Planning Department, Grand Valley State University, in Photogrammetric Engineering & Remote Sensing, November 2008

From the Publisher