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
Remote sensing methods for power line corridor surveys
Leena Matikainen,Matti Lehtomäki,Eero Ahokas,Juha Hyyppä,Mika Karjalainen,Anttoni Jaakkola,Antero Kukko,Tero Heinonen +7 more
TL;DR: The review shows that most previous studies have concentrated on the mapping and analysis of network components, and more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way.
Journal ArticleDOI
Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests
TL;DR: In this paper, the authors present concepts that combine chemical and spectral remote sensing perspectives to facilitate canopy diversity mapping, using examples from their ongoing work in the Hawaiian Islands, demonstrating how a new “airborne sp...
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Carnegie Airborne Observatory: in-flight fusion of hyperspectral imaging and waveform light detection and ranging for three-dimensional studies of ecosystems
Gregory P. Asner,David E. Knapp,Ty Kennedy-Bowdoin,Matthew O. Jones,Roberta E. Martin,Joseph W. Boardman,Christopher B. Field +6 more
TL;DR: The Carnegie Airborne Observatory (CAO) provides in-flight fusion of high-fidelity visible/near-infrared imaging spectrometer data with scanning, waveform light detection and ranging (wLiDAR) data, along with an integrated navigation and data processing approach, that results in geo-orthorectified products for vegetation structure, biochemistry and physiology as well as the underlying topography.
Journal ArticleDOI
Tree Species Classification in Boreal Forests With Hyperspectral Data
TL;DR: Evaluating the potential of two high spectral and spatial resolution hyperspectral sensors, operating at different wavelengths, for tree species classification of boreal forests showed that the HySpex VNIR 1600 sensor is effective in borealTree species classification with kappa accuracies over 0.8.
Journal ArticleDOI
An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities
Christine Lee,Morgan L. Cable,Simon J. Hook,Robert O. Green,Susan L. Ustin,Daniel Mandl,Elizabeth M. Middleton +6 more
TL;DR: The NASA Hyperspectral InfraRed Imager (HyspIRI) as mentioned in this paper is comprised of a visible to short-wavelength infrared (VSWIR) imaging spectrometer and a thermal infrared (TIR) multispectral imager, together with an Intelligent Payload Module (IPM) for onboard processing and rapid downlink of selected data.
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.