Skip to main content

Research Repository

Advanced Search

Outputs (89)

Assessing the accuracy of land cover change with imperfect ground reference data (2010)
Journal Article
Foody, G. M. (2010). Assessing the accuracy of land cover change with imperfect ground reference data. Remote Sensing of Environment, 114(10), https://doi.org/10.1016/j.rse.2010.05.003

The ground data used as a reference in the validation of land cover change products are often not an ideal gold standard but degraded by error. The effects of ground reference data error on the accuracy of land cover change detection and the accuracy... Read More about Assessing the accuracy of land cover change with imperfect ground reference data.

Feature selection for classification of hyperspectral data by SVM (2010)
Journal Article
Pal, M., & Foody, G. M. (2010). Feature selection for classification of hyperspectral data by SVM. IEEE Transactions on Geoscience and Remote Sensing, 48(5), https://doi.org/10.1109/TGRS.2009.2039484

SVM are attractive for the classification of remotely sensed data with some claims that the method is insensitive to the dimensionality of the data and so not requiring a dimensionality reduction analysis in pre-processing. Here, a series of classifi... Read More about Feature selection for classification of hyperspectral data by SVM.

Harshness in image classification accuracy assessment (2008)
Journal Article
Foody, G. M. (2008). Harshness in image classification accuracy assessment. International Journal of Remote Sensing, 29(11), https://doi.org/10.1080/01431160701442120

Thematic mapping via a classification analysis is one of the most common applications of remote sensing. The accuracy of image classifications is, however, often viewed negatively. Here, it is suggested that the approach to the evaluation of image cl... Read More about Harshness in image classification accuracy assessment.

RVM-based multi-class classification of remotely sensed data (2008)
Journal Article
Foody, G. M. (2008). RVM-based multi-class classification of remotely sensed data. International Journal of Remote Sensing, 29(6), https://doi.org/10.1080/01431160701822115

The relevance vector machine (RVM), a Bayesian extension of the support vector machine (SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is introduced and used to derive a multi-class classification of land cov... Read More about RVM-based multi-class classification of remotely sensed data.

Crop classification by a support vector machine with intelligently selected training data for an operational application (2008)
Journal Article
Mathur, A., & Foody, G. M. (2008). Crop classification by a support vector machine with intelligently selected training data for an operational application. International Journal of Remote Sensing, 29(8), https://doi.org/10.1080/01431160701395203

The accuracy of supervised classification is dependent to a large extent on the training data used. The aim is often to capture a large training set to fully describe the classes spectrally, commonly with the requirements of a conventional statistica... Read More about Crop classification by a support vector machine with intelligently selected training data for an operational application.

One-class classification for monitoring a specific land cover class: SVDD classification of fenland (2007)
Journal Article
Sanchez-Hernandez, C., Boyd, D. S., & Foody, G. M. (2007). One-class classification for monitoring a specific land cover class: SVDD classification of fenland. IEEE Transactions on Geoscience and Remote Sensing, 45(4), https://doi.org/10.1109/TGRS.2006.890414

Remote sensing is a major source of land cover information. Commonly, interest focuses on a single land cover class. Although a conventional multi-class classifier may be used to provide a map depicting the class of interest the analysis is not focus... Read More about One-class classification for monitoring a specific land cover class: SVDD classification of fenland.

Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority
Journal Article
Foody, G. M. Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority. Remote Sensing of Environment, 113(8), https://doi.org/10.1016/j.rse.2009.03.014

The comparison of classification accuracy statements has generally been based upon tests of difference or inequality when other scenarios and approaches may be more appropriate. Procedures for evaluating two scenarios with interest focused on the sim... Read More about Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority.

A relative evaluation of multi-class image classification by support vector machines
Journal Article
Foody, G. M., & Mathur, A. A relative evaluation of multi-class image classification by support vector machines. IEEE Transactions on Geoscience and Remote Sensing, 42(6), https://doi.org/10.1109/TGRS.2004.827257

Support vector machines (SVM) have considerable potential as classifiers of remotely sensed data. A constraint on their application in remote sensing has been their binary nature, requiring multi-class classifications to be based upon a large number... Read More about A relative evaluation of multi-class image classification by support vector machines.