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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Proceedings ArticleDOI
(Semi-) Supervised Mixtures of Factor Analyzers and Deep Mixtures of Factor Analyzers Dimensionality Reduction Algorithms For Hyperspectral Images Classification
TL;DR: The proposed dimensionality reduction methods for classification using real HSI give better results than more conventional methods like probabilistic principal component analysis, factor analysis, mixtures of factor analyzers and deep mixture of factor Analyzers.
Proceedings ArticleDOI
Assessment of CNN-Based Methods for Single Tree Detection on High-Resolution RGB Images in Urban Areas
Pedro Alberto Pereira ZamboniThgeThe,Jose Marcato,Gabriela Takahashi Miyoshi,Jonathan de Andrade Silva,Jose Martins,Wesley Nunes Gonçalves +5 more
TL;DR: Zhang et al. as discussed by the authors proposed to evaluate deep learning-based methods combined with high-resolution RGB images to detect single-trees in the urban environment, and three state-of-the-art methods are tested: Faster-RCNN, RetinaNet, and ATSS.
Proceedings ArticleDOI
Mapping tropical rainforest canopies using multi-temporal spaceborne imaging spectroscopy
TL;DR: In this paper, an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection strategy in MESM A was proposed for floristic mapping of tree species in Hawaiian rainforests.
Journal ArticleDOI
Mapping individual silver fir trees using hyperspectral and LiDAR data in a Central European mixed forest
Yifang Shi,Tiejun Wang,Andrew K. Skidmore,Andrew K. Skidmore,Stefanie Holzwarth,Uta Heiden,Marco Heurich,Marco Heurich +7 more
TL;DR: In this article, a set of relevant spectral and structural features from the hyperspectral and LiDAR data were extracted and used to build machine learning classification models to map individual trees in a spruce-dominated natural forest in the Bavarian Forest National Park.
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.