Cargando…
Predicting Species Cover of Marine Macrophyte and Invertebrate Species Combining Hyperspectral Remote Sensing, Machine Learning and Regression Techniques
In order to understand biotic patterns and their changes in nature there is an obvious need for high-quality seamless measurements of such patterns. If remote sensing methods have been applied with reasonable success in terrestrial environment, their use in aquatic ecosystems still remained challeng...
Autores principales: | Kotta, Jonne, Kutser, Tiit, Teeveer, Karolin, Vahtmäe, Ele, Pärnoja, Merli |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3670917/ https://www.ncbi.nlm.nih.gov/pubmed/23755113 http://dx.doi.org/10.1371/journal.pone.0063946 |
Ejemplares similares
-
Relating Remotely Sensed Optical Variability to Marine Benthic Biodiversity
por: Herkül, Kristjan, et al.
Publicado: (2013) -
Predicting the cover and richness of intertidal macroalgae in remote areas: a case study in the Antarctic Peninsula
por: Kotta, Jonne, et al.
Publicado: (2018) -
Establishing Functional Relationships between Abiotic Environment, Macrophyte Coverage, Resource Gradients and the Distribution of Mytilus trossulus in a Brackish Non-Tidal Environment
por: Kotta, Jonne, et al.
Publicado: (2015) -
Predicting lake dissolved organic carbon at a global scale
por: Toming, Kaire, et al.
Publicado: (2020) -
Novel crab predator causes marine ecosystem regime shift
por: Kotta, J., et al.
Publicado: (2018)