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Estimating Yellow Starthistle (Centaurea solstitialis) Leaf Area Index and Aboveground Biomass with the Use of Hyperspectral Data

Published online by Cambridge University Press:  20 January 2017

Shaokui Ge ,
Ming Xu ,
Gerald L. Anderson  and
Raymond I. Carruthers
Shaokui Ge*
Affiliation:
USDA—Agricultural Research Service, Exotic and Invasive Weeds Research Unit, 800 Buchanan St., Albany, CA 94710, and Earth and Planetary Sciences Department, University of California at Santa Cruz, 1156 High Street, Santa Cruz, CA 95064
Ming Xu
Affiliation:
Center for Remote Sensing and Spatial Analysis, Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, NJ 08901
Gerald L. Anderson
Affiliation:
USDA—Agricultural Research Service, Agriculture Research Systems Unit, 1500 N Central Ave. Sidney, MT 59270
Raymond I. Carruthers
Affiliation:
USDA—Agricultural Research Service, Exotic and Invasive Weeds Research Unit, 800 Buchanan St. Albany, CA 94710
*
Corresponding author's E-mail: shaokui@pw.usda.gov or gesk@nature.berkeley.edu
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Abstract

Hyperspectral remote-sensed data were obtained via a Compact Airborne Spectrographic Imager-II (CASI-II) and used to estimate leaf-area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (YST). In parallel, 34 ground-based field plots were used to measure aboveground biomass and LAI to develop and validate hyperspectral-based models for estimating these measures remotely. Derivatives of individual hyperspectral bands improved the correlations between imaged data and actual on-site measurements. Six derivative-based normalized difference vegetation indices (DNDVI) were developed; three of them were superior to the commonly used normalized difference vegetation index (NDVI) in estimating aboveground biomass of YST, but did not improve estimates of LAI. The locally integrated derivatives-based vegetation indices (LDVI) from adjacent bands within three different spectral regions (the blue, red, and green reflectance ranges) were used to enhance absorption characteristics. Three LDVIs outperformed NDVI in estimating LAI, but not biomass. Multiple regression models were developed to improve the estimation of LAI and aboveground biomass of YST, and explained 75% and 53% of the variance in biomass and LAI, respectively, based on validation assessments with actual ground measurements.

Keywords

Yellow starthistle, Centaurea solstitialis LInvasive specieshyperspectral remote sensingairborne hyperspectral datavegetation indexbiophysical estimation
Type
Special Topics
Information
Weed Science , Volume 55 , Issue 6 , December 2007 , pp. 671 - 678
Copyright
Copyright © Weed Science Society of America 

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