Journal ArticleDOI
Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales
TLDR
In this paper, the authors investigated the utility of high spectral and spatial resolution imagery for the automated species-level classification of individual tree crowns (ITCs) in a tropical rain forest (TRF).About:
This article is published in Remote Sensing of Environment.The article was published on 2005-06-30. It has received 714 citations till now. The article focuses on the topics: Multispectral pattern recognition & Hyperspectral imaging.read more
Citations
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Journal ArticleDOI
The role of remote sensing in process-scaling studies of managed forest ecosystems
TL;DR: In this paper, the authors review the application of remote sensing for upscaling forest attributes from the plot scale to regional domains, with particular emphasis on how remote sensing products can support parameterization and validation of ecosystem process models.
Journal ArticleDOI
Observing Changing Ecological Diversity in the Anthropocene
TL;DR: Current satellite remote-sensing data can only produce relatively simple classifications, but new techniques will produce data with dramatically higher biological information content, and the amount of information about species' relationships to climate declines as their distributions move farther from steady state.
Journal ArticleDOI
A Convolutional Neural Network Classifier Identifies Tree Species in Mixed-Conifer Forest from Hyperspectral Imagery
Geoffrey A. Fricker,Jonathan Ventura,Jeffrey A. Wolf,Malcolm P. North,Frank W. Davis,Janet Franklin +5 more
TL;DR: By training a CNN classifier using field data and hyperspectral imagery, this study was able to accurately identify tree species and predict their distribution, as well as the distribution of tree mortality, across the landscape.
Journal ArticleDOI
Classification of Australian Native Forest Species Using Hyperspectral Remote Sensing and Machine-Learning Classification Algorithms
Xiao Shang,Laurie A. Chisholm +1 more
TL;DR: It is demonstrated that hyperspectral remote sensing and machine-learning classification has substantial potential for the classification of Australian native forest species.
Journal ArticleDOI
From Google Maps to a fine-grained catalog of street trees
TL;DR: This is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees.
References
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Book
Using multivariate statistics
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Journal ArticleDOI
Pattern Classification and Scene Analysis.
Book
Pattern classification and scene analysis
Richard O. Duda,Peter E. Hart +1 more
TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.
Journal ArticleDOI
A new method for non-parametric multivariate analysis of variance
TL;DR: In this article, a non-parametric method for multivariate analysis of variance, based on sums of squared distances, is proposed. But it is not suitable for most ecological multivariate data sets.
Journal ArticleDOI
Extinction risk from climate change
Chris D. Thomas,Alison Cameron,Rhys E. Green,Rhys E. Green,Michel Bakkenes,Linda J. Beaumont,Yvonne C. Collingham,Barend F.N. Erasmus,Marinez Ferreira de Siqueira,Alan Grainger,Lee Hannah,Lesley Hughes,Brian Huntley,Albert S. van Jaarsveld,Guy F. Midgley,Lera Miles,Lera Miles,Miguel A. Ortega-Huerta,A. Townsend Peterson,Oliver L. Phillips,Stephen E. Williams +20 more
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.