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.
Nomenclature: Waterhyacinth, Eichhornia crassipes (Mart.) Solms EICCR.
Management Implications: Typically, the biomass of waterhyacinth is estimated using quadrats with a specific unit area placed over the plant mat. However, it is labor and time intensive to collect and process samples. Moreover, this method is destructive because it removes plant material from the system which affects long term studies of plant growth. The normalized difference vegetation index (NDVI) is a well-known vegetation index that can be used to monitor aquatic plants. However, limitations due canopy complexity during the growing season often limit its use. Based on the results, NDVI alone is not sufficient to estimate the biomass of waterhyacinth. The poor predictive performance of band 4, as well as canopy complexity related to waterhyacinth phenology during the growing season and vegetation cover/water background ratio likely affected the performance of NDVI. According to this study, measuring morphometric parameters such as leaf area index may enhance the performance of NDVI derived from Landsat 5 TM or other multispectral sensors with same spectral resolution. Therefore, the sole use of NDVI from Landsat 5 TM is not recommended to estimate the biomass of waterhyacinth. It is suggested that large-scale waterhyacinth management would consider NDVI derived from other multispectral sensors (e.g. Landsat 8 OLI). Current results could be useful to test new multispectral or hyperspectral sensors for aquatic vegetation management.