Evaluation of UAV imagery for mapping Silybum marianum weed patches

By A. A. Tamouridou, T. Alexandridis, X. Pantazi, A. Lagopodi, J. Kashefi, D. Moshou. 2017

57 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/255837e2dfe60b8fcb3dac341b7da039cba75ef8

How researchers see this paper

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

In Ecology

1. Yanbo Huang
2. Haikuan Feng
3. Guijun Yang
4. Zhenhai Li

In Environmental Engineering

1. Haikuan Feng
2. Guijun Yang
3. Zhenhai Li

Citations in the corpus

• Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives (2017, methodology): “…et al., 2016), tiller densities (Du and Noguchi, 2017), and emergence (Sankaran et al., 2015a), can be rapidly obtained using the image analysis methods or the spectral and texture information in the images acquired by a UAV deployed imaging sensors (Tamouridou et al., 2017; Yu et al., 2017).”
• Early season weed mapping in rice crops using multi-spectral UAV data (2018, methodology): “UAV imagery were successfully used for mapping weed infestation over maize and sunflower crops (Peña et al. 2013; Pérez-Ortiz et al. 2015; López-Granados et al. 2016; Pérez-Ortiz et al. 2016; Castaldi et al. 2017), as well as grasslands (Tamouridou et al. 2017).”