Leafy Spurge (Euphorbia esula) Classification Performance Using Hyperspectral and Multispectral Sensors
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CitationMitchell, J. J., & Glenn, N. F. (2009). Leafy spurge (Euphorbia esula) classification performance using hyperspectral and multispectral sensors. Rangeland Ecology & Management, 62(1), 16-27.
PublisherSociety for Range Management
JournalRangeland Ecology & Management
AbstractTwo demonstration sites in southeast Idaho were used to extend the scope of remote sensing of leafy spurge research toward investigating coarser scale detection limits. Hyperspectral images were obtained to produce baseline leafy spurge maps, from which spatially and/or spectrally degraded images were subsequently derived for comparative purposes with Landsat 5 Thematic Mapper (TM). The baseline presence/absence maps had an overall accuracy of 67% at the Spencer study site and 85% at the Medicine Lodge study site. Unexpectedly high-accuracy results were produced from the images that were spectrally degraded to the bandwidths of Landsat 5 TM, which suggests that high spectral resolution is not critical to leafy spurge detection. However, a classification using a Landsat 5 TM image indicates that the sensor is inadequate for regional distribution monitoring. The differences in results between the actual and degraded images suggest that a sensor with comparable resolutions but improved instrumentation (e.g., signal to noise) may offer an alternative to hyperspectral data for mapping leafy spurge at regional scales.