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Remotely-sensed Data for Natural Resource Models

Published online by Cambridge University Press:  24 August 2009

Jerry C. Ritchie  and
Edwin T. Engman
Jerry C. Ritchie
Affiliation:
Soil Scientist, USDA Agricultural Research Service, Hydrology Laboratory, Beltsville, Maryland 20705, USA
Edwin T. Engman
Affiliation:
Hydrologist, USDA Agricultural Research Service, Hydrology Laboratory, Beltsville, Maryland 20705, USA.
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Attempts to model ecosystems have increased in recent years through the application of systems theory and the improvement in computer capacity and speed. A major problem with these models is providing data for input or validation. A potential source of data is information collected by remote-sensing techniques. Remotely-sensed data can be used in natural resource simulation models to provide spatial and temporal measurements, data for model calibration or validation, and independent feedback to keep the model simulation on track with reality. Remote sensing can provide spatial and temporal measurements of many landscape parameters that could improve our ability to understand and model the spatial and temporal characteristics of landscapes.

The challenge for remote-sensing scientists, landscape ecologists, and natural resource modellers, is to determine the most effective way to interpret and use the data from remote sensors in natural resource management. Natural resource models that can fully utilize the spatial data which remote-sensing techniques can provide, will almost certainly improve our understanding of landscapes and our ability to simulate and manage them wisely.

Type
Main Papers
Information
Environmental Conservation , Volume 13 , Issue 3 , Autumn 1986 , pp. 203 - 210
Copyright
Copyright © Foundation for Environmental Conservation 1986

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