Environmental Management

, Volume 31, Issue 3, pp 0429–0441

Remotely Sensed Data for Ecosystem Analyses: Combining Hierarchy Theory and Scene Models

  • Stuart R. PHINN
  • DOUGLAS A. STOW
  • JANET FRANKLIN
  • LEAL A. K. MERTES
  • JOEL MICHAELSEN

DOI: 10.1007/s00267-002-2837-x

Cite this article as:
PHINN, S., STOW, D., FRANKLIN, J. et al. Environmental Management (2003) 31: 0429. doi:10.1007/s00267-002-2837-x

Abstract

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost–benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

KEY WORDS: Scene model; Hierarchy theory; Optimal scale; Landscape ecology; Remote sensing

Copyright information

© Springer-Verlag New York Inc. 2003

Authors and Affiliations

  • Stuart R. PHINN
    • 1
  • DOUGLAS A. STOW
    • 1
  • JANET FRANKLIN
    • 1
  • LEAL A. K. MERTES
    • 2
  • JOEL MICHAELSEN
    • 2
  1. 1.Department of Geography, San Diego State University, San Diego, California 92182-2493, USAUS
  2. 2.Department of Geography, University of California at Santa Barbara, Santa Barbara, California 93106, USAUS