Giles Foody
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Status of land cover classification accuracy assessment
GM Foody
Remote sensing of environment 80 (1), 185-201, 2002
Good practices for estimating area and assessing accuracy of land change
P Olofsson, GM Foody, M Herold, SV Stehman, CE Woodcock, MA Wulder
Remote sensing of Environment 148, 42-57, 2014
A relative evaluation of multiclass image classification by support vector machines
GM Foody, A Mathur
IEEE Transactions on geoscience and remote sensing 42 (6), 1335-1343, 2004
Thematic map comparison
GM Foody
Photogrammetric Engineering & Remote Sensing 70 (5), 627-633, 2004
Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation
P Olofsson, GM Foody, SV Stehman, CE Woodcock
Remote sensing of environment 129, 122-131, 2013
Feature selection for classification of hyperspectral data by SVM
M Pal, GM Foody
IEEE Transactions on Geoscience and Remote Sensing 48 (5), 2297-2307, 2010
Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions
GM Foody, DS Boyd, MEJ Cutler
Remote sensing of environment 85 (4), 463-474, 2003
Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification
GM Foody, A Mathur
Remote Sensing of Environment 93 (1-2), 107-117, 2004
Approaches for the production and evaluation of fuzzy land cover classifications from remotely-sensed data
GM Foody
International Journal of Remote Sensing 17 (7), 1317-1340, 1996
Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification
GM Foody, NA Campbell, NM Trodd, TF Wood
Photogrammetric engineering and remote sensing 58 (9), 1335-1341, 1992
The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM
GM Foody, A Mathur
Remote sensing of environment 103 (2), 179-189, 2006
Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions
GM Foody, DP Cox
International Journal of Remote Sensing 15 (3), 619-631, 1994
Measuring and modelling biodiversity from space
TW Gillespie, GM Foody, D Rocchini, AP Giorgi, S Saatchi
Progress in physical geography 32 (2), 203-221, 2008
On the compensation for chance agreement in image classification accuracy assessment
GM Foody
Photogrammetric Engineering and Remote Sensing 58, 1459-1460, 1992
Multiclass and binary SVM classification: Implications for training and classification users
A Mathur, GM Foody
IEEE Geoscience and remote sensing letters 5 (2), 241-245, 2008
Global land cover validation: Recommendations for evaluation and accuracy assessment of global land cover maps
AH Strahler, L Boschetti, GM Foody, MA Friedl, MC Hansen, M Herold, ...
European Communities, Luxembourg 51 (4), 1-60, 2006
Harshness in image classification accuracy assessment
GM Foody
International Journal of Remote Sensing 29 (11), 3137-3158, 2008
Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification
GM Foody
Remote sensing of environment 239, 111630, 2020
Mapping the biomass of Bornean tropical rain forest from remotely sensed data
GM Foody, ME Cutler, J McMorrow, D Pelz, H Tangki, DS Boyd, ...
Global Ecology and Biogeography 10 (4), 379-387, 2001
Key issues in rigorous accuracy assessment of land cover products
SV Stehman, GM Foody
Remote Sensing of Environment 231, 111199, 2019
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