![Mapping leafy spurge with field spectroscopy, Swan Valley, Idaho Jacob mapping leafy spurge in the field](https://www.boisestate.edu/wp-content/uploads/sites/320/files/2014/02/idfalls_asd_1733.jpg)
BCAL has been in forefront of research on mapping leafy spurge (Euphorbia esula L.) and other invasive species in Idaho using various remote sensing techniques.
BCAL graduate students Jessica Mitchell, Jacob Mundt, and Nagendra Singh have written Master of Science thesis on the topic. The results have been presented at several national conferences, as well as published in peer-reviewed journals.
- Mitchell, J and N Glenn. 2009. “Leafy Spurge (Euphorbia esula) Classification Performance Using Hyperspectral and Multispectral Sensors.” Rangeland Ecology & Management, 62 (1): 16-27.
- Mitchell, J and N Glenn. 2009. “Subpixel abundance estimates in mixture-tuned matched filtering classifications of leafy spurge (Euphorbia esula L.).” International Journal of Remote Sensing, 30 (23): 6099-6119.
- Glenn, N, J Mundt, K Weber, T Prather, L Lass, and J Pettingill. 2005. “Hyperspectral data processing for repeat detection of small infestations of leafy spurge.” Remote Sensing of Environment, 95 (3): 399-412.
- Mundt, J, N Glenn, K Weber, T Prather, L Lass, and J Pettingill. 2005. “Discrimination of hoary cress and determination of its detection limits via hyperspectral image processing and accuracy assessment techniques.” Remote Sensing of Environment, 96 (3): 509-517.
- Mundt, J, N Glenn, K Weber, and J Pettingill. 2006. “Determining target detection limits and accuracy delineation using an incremental technique.” Remote Sensing of Environment, 105 (1): 34-40.
- Lass, L, T Prather, N Glenn, K Weber, J Mundt, and J Pettingill. 2005. “A Review of Remote Sensing of Invasive Weeds and Example of the Early Detection of Spotted Knapweed (Centaurea maculosa) and Babysbreath (Gypsophila paniculata) with a Hyperspectral Sensor.” Weed Science , 53 (2): 242-251.
- Singh, N and N Glenn. 2009. “Multitemporal spectral analysis for cheatgrass (Bromus tectorum) classification.” International Journal of Remote Sensing, 30 (13): 3441-3462.