Classification Methods for Remotely Sensed Data

By Paul M. Mather, B. Tso. 2001

602 citations recorded by the source corpus.

How researchers see this paper

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A survey of image classification methods and techniques for improving classification performance (2007, unknown): “Although much previous research and some books are specifically concerned with image classification (Tso and Mather 2001 , Landgrebe 2003 ), a comprehensive up‐to‐date review of classification approaches and techniques is not available.”
Fuzzy clustering algorithms for unsupervised change detection in remote sensing images (2011, methodology): “To remove the effects of sensor errors and environmental factors, radiometric corrections are needed [7,66].”
High-resolution image texture as a predictor of bird species richness (2006, methodology): “The texture of an image contains important information about the spatial and structural arrangement of objects ( Tso & Mather, 2001 ).”
Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review (2020, methodology): “introduction of RF, however, it has drawn attentionwithin theRS community, as it produced classification accuracies comparable with those of SVM [67], [68].”
Vegetation classification method with biochemical composition estimated from remote sensing data (2011, methodology): “The classification accuracy and kappa statistic were then estimated (Congalton and Green 1999 , Tso and Mather 2001 ).”