Identifying plant species using mid-wave infrared (2.5–6 μm) and thermal infrared (8–14 μm) emissivity spectra

By Saleem Ullah, Martin Schlerf, Andrew K. Skidmore, C. Hecker. 2012

151 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Food Science

View Paper: https://www.semanticscholar.org/paper/1b82353c4400d1328d80bed15b3cf59dc7b07625

How researchers see this paper

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

In Ecological Modeling

1. A. Gutierrez
2. Abel Ramoelo
3. Harini Nagendra
4. Carlo Ricotta
5. Kate S. He
6. Duccio Rocchini
7. Thomas A. Groen
8. Markus Neteler

In Ecology

1. Markus Metz
2. A. Gutierrez
3. Abel Ramoelo
4. Harini Nagendra
5. Carlo Ricotta
6. Kate S. He
7. Duccio Rocchini
8. Thomas A. Groen

In Food Science

1. Kate S. He

Citations in the corpus

• Potential of remote sensing to predict species invasions (2015, background): “…to discriminate plant species come from laboratory studies on the characteristic emissivity spectra of plant species in the mid- and thermal infrared, and from foreseen advances in air-borne and space-borne hyperspectral thermal sensors (Ribeiro da Luz and Crowley, 2010; Ullah et al., 2012).”
• Retrieval of leaf water content spanning the visible to thermal infrared spectra (2014, methodology): “This strong correlation led to the successful estimation of leaf water 71 content from MIR spectra using various spectral transformation techniques (Ullah et al. 2012c; 72 Ullah et al. 2013).”