Mapping Downy Brome (Bromus tectorum) Using Multidate AVIRIS Data

Abstract

Invasive plants impose threats to both natural and managed ecosystems. Downy brome is among the most aggressive invasive weeds that has infested the shrub-steppe ecoregion of eastern Washington. Hyperspectral remote sensing has potential for early detection and for monitoring the spread of downy brome—information that is essential for developing effective management strategies. Two airborne hyperspectral Advanced Visible Infrared Imaging Spectrometer (AVIRIS) images (electromagnetic spectrum ranging from 400 to 2,500 nm) were acquired at a nominal 4-m ground resolution over a study area in south-central Washington on July 27, 2000 and May 5, 2003. We used a mixture-tuned matched filtering (MTMF) algorithm to classify downy brome and predict its percent cover in each dataset plus a merged multiseasonal dataset using the transformed bands from a minimum noise fraction (MNF) output. The correlation coefficient was 0.79, calculated for the multidate MTMF predicted downy brome abundance, compared to 0.41 and 0.51 derived from the July 2000 and May 2003 data, respectively. Although this study used high spatial resolution (∼3 to 4 m) hyperspectral imagery, this result shows that data acquired in different seasons is more effective for detection of downy brome invasion, compared to single-date datasets. These results support expanded use of multitemporal data for weed mapping to capitalize on spectral differences between seasons for weeds, in this case downy brome, and the surrounding environment.

Benefits of hyperspectral remote sensing for tracking plant invasions

“…(1) Multitemporal spectral stack; (2) July 2000 spectral data; and (3) May 2003 data. The overall accuracy coefficients for the three downy brome occurrence maps were 0.81 for multitemporal data set, and 0.70 and 0.72 for 2000 and 2003 data sets (reproduced from Noujdina & Ustin, 2008). This figure is available in colour online.…”

Earth system science related imaging spectroscopy—An assessment

“…In both managed and unmanaged ecosystems the spectroscopy focus is on detection and identification of plant succession, phenology, plant health, plant functional types (Schmidtlein & Sassin, 2004), and on monitoring invasive species (Asner et al, 2008c;Hestir et al, in press;Noujdina & Ustin, 2008;Underwood et al, 2003). Biochemical applications will concentrate on the (simultaneous) retrieval of moisture content (Cheng et al, 2006(Cheng et al, , 2008Li et al, 2007), carbon (C) (Grace et al, 2007), nitrogen (N) Smith et al, 2002), and potentially phosphorus (P) (Mutanga & Kumar, 2007), and connecting soil, leaf, and plant functioning with atmospheric fluxes using quantitative approaches.…”

Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas

“…The newest hyperspectral instruments, have more than 100 spectral channels of relative narrow bandwidths (5-10 nm) and have been successfully used to identify invasive species (Adam and Mutanga, 2009;Andrew and Ustin, 2008;DiPietro et al, 2002;Hamada et al, 2007;Noujdina and Ustin, 2008;Taylor et al, 2012;Underwood et al, 2003Underwood et al, , 2007Vaiphasa et al, 2007;Yang et al, 2012). Although hyperspectral data improves species discrimination by capitalizing on the biochemical and structural vegetation properties, it has to deal with a high dimensional complexity (Cochrane, 2000;Marcus et al, 2003;Underwood et al, 2003).…”