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Proceedings Paper

Multitemporal spectroradiometry-guided object-oriented classification of salt marsh vegetation
Author(s): Daniel L. Civco; Martha S. Gilmore; Emily H. Wilson; Nels Barrett; Sandy Prisloe; James D. Hurd; Cary Chadwick
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Paper Abstract

This study addresses the use of multitemporal field spectral data, satellite imagery, and LiDAR top of canopy data to classify and map common salt marsh plant communities. Visible to near-infrared (VNIR) reflectance spectra were measured in the field to assess the phenological variability of the dominant species - Spartina patens, Phragmites australis and Typha spp. The field spectra and single date LiDAR canopy height data were used to define an objectoriented classification methodology for the plant communities in multitemporal QuickBird imagery. The classification was validated using an extensive field inventory of marsh species. Overall classification accuracies were 97% for Phragmites, 63% for Typha spp. and 80% for S. patens meadows. Using a fuzzy assessment analysis, these accuracies were 97%, 76%, and 92%, respectively, for the three major species.

Paper Details

Date Published: 10 October 2008
PDF: 12 pages
Proc. SPIE 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, 71100A (10 October 2008); doi: 10.1117/12.800016
Show Author Affiliations
Daniel L. Civco, Univ. of Connecticut (United States)
Martha S. Gilmore, Wesleyan Univ. (United States)
Emily H. Wilson, Univ. of Connecticut (United States)
Nels Barrett, U.S. Dept. of Agriculture (United States)
Sandy Prisloe, Univ. of Connecticut (United States)
James D. Hurd, Univ. of Connecticut (United States)
Cary Chadwick, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 7110:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII
Ulrich Michel; Daniel L. Civco; Manfred Ehlers; Hermann J. Kaufmann, Editor(s)

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