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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Book ChapterDOI
Machine Learning Algorithms for Optical Remote Sensing Data Classification and Analysis
G. P. Obi Reddy,K. C. Arun Kumar +1 more
TL;DR: In this article, the authors provide a critical review on important advanced ML algorithms in remote sensing data classification, and analysis; secondly, examine the performance of widely used important supervised ML algorithms namely Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Tree (CART) in satellite image classification.
Proceedings Article
Connecting infrared spectra with plant traits to identify species : abstract + powerpoint
TL;DR: In this paper, the authors measured the infrared spectra (1.4-16.0 mm) on individual, fresh leaves of 19 species (from herbaceous to woody species), as well as 14 leaf traits for each leaf.
Proceedings Article
Urban Tree Species Classification Using Aerial Imagery
TL;DR: This study first offers a pipeline for generating labelled dataset of urban trees using Google Map’s aerial images and then investigates how state of the art deep Convolutional Neural Network models such as VGG and ResNet handle the classification problem of urban tree aerial images under different parameters.
Journal Article
Multi-level adaptive support vector machine classification for tropical tree species
TL;DR: Result of SVM also has proven its better capability than Maximum Likelihood Classification (MLC) in tropical tree species classification.
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.