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Estimating the Biomass of Waterhyacinth (Eichhornia crassipes) Using the Normalized Difference Vegetation Index Derived from Simulated Landsat 5 TM

Published online by Cambridge University Press:  20 January 2017

Wilfredo Robles ,
John D. Madsen  and
Ryan M. Wersal
Wilfredo Robles*
Affiliation:
Geosystems Research Institute, Box 9652, Mississippi State, MS 39762
John D. Madsen
Affiliation:
Geosystems Research Institute, Box 9652, Mississippi State, MS 39762
Ryan M. Wersal
Affiliation:
Geosystems Research Institute, Box 9652, Mississippi State, MS 39762
*
Corresponding author's E-mail: wilfredo.robles2@upr.edu
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Abstract

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Waterhyacinth is a free-floating aquatic weed that is considered a nuisance worldwide. Excessive growth of waterhyacinth limits recreational use of water bodies as well as interferes with many ecological processes. Accurate estimates of biomass are useful to assess the effectiveness of control methods to manage this aquatic weed. While large water bodies require significant labor inputs with respect to ground-truth surveys, available technology like remote sensing could be capable of providing temporal and spatial information from a target area at a much reduced cost. Studies were conducted at Lakes Columbus and Aberdeen (Mississippi) during the growing seasons of 2005 and 2006 over established populations of waterhyacinth. The objective was to estimate biomass based on nondestructive methods using the normalized difference vegetation index (NDVI) derived from Landsat 5 TM simulated data. Biomass was collected monthly using a 0.10m2 quadrat at 25 randomly-located locations at each site. Morphometric plant parameters were also collected to enhance the use of NDVI for biomass estimation. Reflectance measurements using a hyperspectral sensor were taken every month at each site during biomass collection. These spectral signatures were then transformed into a Landsat 5 TM simulated data set using MatLab® software. A positive linear relationship (r2 = 0.28) was found between measured biomass of waterhyacinth and NDVI values from the simulated dataset. While this relationship appears weak, the addition of morphological parameters such as leaf area index (LAI) and leaf length enhanced the relationship yielding an r2 = 0.66. Empirically, NDVI saturates at high LAI, which may limit its use to estimate the biomass in very dense vegetation. Further studies using NDVI calculated from narrower spectral bands than those contained in Landsat 5 TM are recommended.

Keywords

Waterhyacinth, Eichhornia crassipes (Mart.) Solms EICCRRemote sensingLandsat 5 TMnondestructive sampling methodshyperspectral reflectance
Type
Research Article
Information
Invasive Plant Science and Management , Volume 8 , Issue 2 , June 2015 , pp. 203 - 211
Copyright
Copyright © Weed Science Society of America 

Footnotes

Current address: Assistant Professor, Department of Crops and Agro-Environmental Science, University of Puerto Rico, Mayagüez, Box 9000, Mayagüez, PR 00681

Current address: USDA-ARS, EIWRU, Univ. of California-Davis, Dept. of Plant Sciences, Mail Stop 4, Davis, CA 95616

Current address: Lonza – Water Technology, Alpharetta Innovation and Technology Center, 1200 Bluegrass Lakes Pkwy, Alpharetta, GA 30004

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