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
Identification of the Best Hyperspectral Indices in Estimating Plant Species Richness in Sandy Grasslands
TL;DR: The spectral variability within the 420–480 nm and 760–900 nm ranges, the first derivative value at the sensitive bands, and the normalized difference at narrow spectral ranges correlated well with plant species richness.
Journal ArticleDOI
Assessing the utility of uav-borne hyperspectral image and photogrammetry derived 3d data for wetland species distribution quick mapping
TL;DR: In this paper, the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area of Hong Kong was compared.
Journal ArticleDOI
Discrimination of dominant forest types for Matschie's tree kangaroo conservation in Papua New Guinea using high-resolution remote sensing data
TL;DR: In this article, the capabilities of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de la Terre (SPOT)-4 multispectral image data at discriminating dominant forest types at a remote research location in Papua New Guinea (PNG).
Journal ArticleDOI
Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data
TL;DR: A hybrid ensemble method that is comprised of a sequential and a parallel architecture for the classification of tree genus using LiDAR data and an automatic feature reduction method using results drawn from Random Forests to improve classification accuracy is presented.
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.