In recent years, the impact of aquatic invasive species on biodiversity has become a major global concern. In the
Sacramento-San Joaquin Delta region in the Central Valley of California, USA, dense infestations of the invasive
aquatic emergent weed, water hyacinth (<i>Eichhornia crassipes</i>) interfere with ecosystem functioning. This silent invader
constantly encroaches into waterways, eventually making them unusable by people and uninhabitable to aquatic fauna.
Quantifying and mapping invasive plant species in aquatic ecosystems is important for efficient management and
implementation of mitigation measures. This paper evaluates the ability of hyperspectral imagery, acquired using the
HyMap sensor, for mapping water hyacinth in the Sacramento-San Joaquin Delta region. Classification was performed
on sixty-four flightlines acquired over the study site using a decision tree which incorporated Spectral Angle Mapper
(SAM) algorithm, absorption feature parameters in the spectral region between 0.4 and 2.5μm, and spectral
endmembers. The total image dataset was 130GB. Spectral signatures of other emergent aquatic species like pennywort
(<i>Hydrocotyle ranunculoides</i>) and water primrose (<i>Ludwigia</i> <i>peploides</i>) showed close similarity with the water hyacinth
spectrum, however, the decision tree successfully discriminated water hyacinth from other emergent aquatic vegetation
species. The classification algorithm showed high accuracy (κ value = 0.8) in discriminating water hyacinth.