Optimal classification methods for mapping agricultural tillage practices

By S. South, J. Qi, D. Lusch. 2004

123 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/efe491fdfdf58af3fb2d4726ece0a5d6e5eeebcf

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. José Manuel Peñá-Barragán
2. Johan Six
3. Richard E. Plant
4. Moffatt K. Ngugi
5. Marco Körner
6. Marc Rußwurm
7. Xiaoxiao Li
8. Guofan Shao

In Environmental Engineering

1. Johan Six

Citations in the corpus

• A survey of image classification methods and techniques for improving classification performance (2007, unknown): “…is often conducted to find the best classification result for a specific study (Zhuang et al. 1995, Atkinson et al. 1997, Cortijo and de la Blanca 1997, Flygare 1997 Improving classification performance Erbek et al. 2004, Lu et al. 2004, Olthof et al. 2004, Pal and Mather 2004, South et al. 2004).”
• Object-based crop identification using multiple vegetation indices, textural features and crop phenology (2011, background): “Agricultural land use information is, therefore, updated routinely in many cropland regions in USA and Europe through farmer communications or ground visits of administrative inspectors to selected fields (Peña-Barragán et al., 2008; South et al., 2004).”
• Remote Sensing and Cropping Practices: A Review (2018, methodology): “[128] tested five supervised classification methods to map no-till and conventional tillage using a single Landsat 7 ETM scene.”