Habitat suitability modelling of an invasive plant with advanced remote sensing data
By M. E. Andrew, Susan L. Ustin. 2009
120 citations recorded by the source corpus.
Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/1b12429e7fa03078d80076a041b79819ed0d32fb
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
- Markus Neteler
- Duccio Rocchini
- Sebastian Schmidtlein
- Kate S. He
- A. Gutierrez
- Gregory P. Asner
- Nathalie Pettorelli
- Harini Nagendra
In Ecology
- Markus Neteler
- Markus Metz
- Duccio Rocchini
- Kate S. He
- Harini Nagendra
- Sebastian Schmidtlein
- Cho‐ying Huang
- A. Gutierrez
In Nature and Landscape Conservation
- Duccio Rocchini
- Kate S. He
- Gregory P. Asner
- Nathalie Pettorelli
- Harini Nagendra
- Carlo Ricotta
- Markus Neteler
- Sebastian Schmidtlein
Citations in the corpus
- Will remote sensing shape the next generation of species distribution models? (2015, background): “…sensors onboard satellites, planes and unmanned aerial vehicles are revolutionizing the way we can detect and monitor both plant and animal species in terrestrial and aquatic ecosystems as well as allowing the emergence of novel predictor variables appropriate for species distribution modeling.”
- Applications of Remote Sensing to Alien Invasive Plant Studies (2009, background): “Recently, efforts have been undertaken to fully integrate spectral and LiDAR instrument systems and analytical techniques in order to improve the analysis of vegetation functional and structural properties [72,73].”
- Benefits of hyperspectral remote sensing for tracking plant invasions (2011, methodology): “One example of hyperspectral data used for invasion risk assessment is carried out by Andrew and Ustin (2009).”
- Potential of remote sensing to predict species invasions (2015, methodology): “Remote sensing data have been used as ancillary spatial variables to improve species distribution models both spatially and temporally (e.g. Andrew and Ustin, 2009; Bradley and Fleishman, 2008; Gillespie et al., 2008; Saatchi et al., 2008).”