Field spectroscopy for weed detection in wheat and chickpea fields

By U. Shapira, Ittai Herrmann, Arnon Karnieli, David J. Bonfil. 2013

69 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/38fe73a92c01ac39900b157debc01bf227ae03dc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. U. Shapira
2. Arnon Karnieli
3. Ittai Herrmann
4. David J. Bonfil

In Ecology

1. Arnon Karnieli
2. Ittai Herrmann
3. David J. Bonfil
4. U. Shapira
5. S. Kinast

In Plant Science

1. Arnon Karnieli
2. Ittai Herrmann
3. David J. Bonfil

Citations in the corpus

• Ground-level hyperspectral imagery for detecting weeds in wheat fields (2013, background): “The red-edge region is the slope connecting the low red and high NIR reflectance values in the spectrum of vegetation and is an important indicator for spectral separation of different plant species (Herrmann et al. 2011; Shapira et al. 2013).”
• Estimating green LAI in four crops: Potential of determining optimal spectral bands for a universal algorithm (2014, unknown): “, 2011) or weed identification (Shapira et al., 2013).”
• Weed detection by UAV: simulation of the impact of spectral mixing in multispectral images (2017, background): “For example, mapping weed patches would allow precision spraying, in which weed-free areas would not be sprayed, saving herbicide and thus limiting input costs and losses in the environment (Gerhards et al. 2002; Martı́n et al. 2016; Nordmeyer 2006; Stafford and Miller 1993).”