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
Potential use of hyperspectral data to classify forest tree species
TL;DR: In this article, a hyperspectral image of a forest stand in north-eastern Poland taken using an AISA (Airborne Imaging Spectrometer for Application) Eagle camera was transformed to extract the most valuable spectral differences and was classified into seven tree types (birch, European beech, oak, hornbeam, European larch, Scots pine, and Norway spruce) using nine classification algorithms.
Journal ArticleDOI
Height variation hypothesis: A new approach for estimating forest species diversity with CHM LiDAR data
Michele Torresani,Duccio Rocchini,Duccio Rocchini,Ruth Sonnenschein,Marc Zebisch,Heidi C. Hauffe,Michael Heym,Hans Pretzsch,Giustino Tonon +8 more
TL;DR: The HVH is a valuable tool for assessing tree species diversity in forest ecosystems, and could also be useful for overall biodiversity estimates, underlined that the abundance-based diversity measures are more highly correlated with HH than with species richness.
Journal ArticleDOI
Organismic Remote Sensing for Tropical Forest Ecology and Conservation1,2
TL;DR: In this paper, the authors focus on high-resolution remote-sensing developments to measure and monitor tropical forest canopies at the "organismic scale", which is the resolution that resolves individual canopy and species throughout the forest landscape.
An object-based approach to quantity and quality assessment of heathland habitats in the framework of natura 2000 using hyperspectral airborne ahs images
Birgen Haest,G. Thoonen,J. Vanden Borre,Toon Spanhove,Stephanie Delalieux,L. Bertels,Lammert Kooistra,Caspar A. Mücher,Paul Scheunders +8 more
TL;DR: In this paper, a multi-step mapping framework was developed and applied on a protected semi-natural heathland area in the north of Belgium, which consecutively consists of a 4-level hierarchical land cover classification of hyperspectral airborne AHS image data, and a kernel-based structural re-classification algorithm in combination with habitat patch object composition definitions.
Journal ArticleDOI
Evaluation of Hyperspectral Multitemporal Information to Improve Tree Species Identification in the Highly Diverse Atlantic Forest
Gabriela Takahashi Miyoshi,Nilton Nobuhiro Imai,Antonio Maria Garcia Tommaselli,Marcus Vinicius Antunes de Moraes,Eija Honkavaara +4 more
TL;DR: Results show that UAV-based, hyperspectral, multitemporal remote sensing imagery is a promising tool for tree species identification in tropical forests.
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.