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Proceedings Paper

Interfacing forest succession and radar backscatter models for forest ecosystem studies
Author(s): K. Jon Ranson; Guoqing Sun; John F. Weishampel; Robert G. Knox
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Paper Abstract

This paper discusses the approach and results of using a forest succession model and a microwave vegetation canopy scattering model to determine expected remote sensing signatures as the forest changes through time. We used the forest model to generate characteristics such as species, stem diameter and height for individual trees growing on a 0.01 ha patch over a 500 year period. The simulations were repeated fifteen times under random initialization conditions to provide a measure of variance. These data were used to parameterize a radar backscatter model and radar signatures were calculated for stands at 28 time intervals over the 500 year period. The results are discussed in terms of the radar backscatter response to changes in forest structure and the implications for radar remote sensing of forests. Our results show that a gap type forest growth model can be used to provide inputs for a radar backscatter model. The predicted backscatter can then be checked against actual SAR imagery as a test of both the forest and the radar backscatter models. Successful coupling of these models provides an effective tool for understanding backscatter measurements from forested areas, as well as, a capability to initialize and test forest ecosystem models.

Paper Details

Date Published: 31 January 1995
PDF: 12 pages
Proc. SPIE 2314, Multispectral and Microwave Sensing of Forestry, Hydrology, and Natural Resources, (31 January 1995); doi: 10.1117/12.200730
Show Author Affiliations
K. Jon Ranson, NASA Goddard Space Flight Ctr. (United States)
Guoqing Sun, Science Systems and Applications, Inc. (United States)
John F. Weishampel, NASA Goddard Space Flight Ctr. (United States)
Robert G. Knox, NASA Goddard Space Flight Ctr. (United States)


Published in SPIE Proceedings Vol. 2314:
Multispectral and Microwave Sensing of Forestry, Hydrology, and Natural Resources
Eric Mougin; K. Jon Ranson; James Alan Smith, Editor(s)

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