Retrieval of leaf water content spanning the visible to thermal infrared spectra

By Saleem Ullah, Andrew K. Skidmore, Abel Ramoelo, Thomas A. Groen, M. Naeem, Asad Ali. 2014

116 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/8b57744e0e712a55a5f02b60406985c1dbbbb89f

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In Analytical Chemistry

1. Yangyang Fan
2. Lei Zhou
3. Osama Elsherbiny
4. Zhengjun Qiu

Citations in the corpus

• Comparison of various modelling approaches for water deficit stress monitoring in rice crop through hyperspectral remote sensing (2019, background): “The RWC serves as a key leaf parameter to determine leaf water content (Ullah et al., 2014; Das et al., 2017).”
• Fusion of Feature Selection Methods and Regression Algorithms for Predicting the Canopy Water Content of Rice Based on Hyperspectral Data (2021, methodology): “, chlorophyll [80], nitrogen [37], relative water content [22], and leaf equivalent water thickness [81].”