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Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification

Remote sensing of environment, 2020-03, Vol.239, p.111630, Article 111630

Foody, Giles M.

2020

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Feature Selection for Classification of Hyperspectral Data by SVM

IEEE transactions on geoscience and remote sensing, 2010-05, Vol.48 (5), p.2297-2307

2010

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IEEE_Xplore

Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient

PloS one, 2023-10, Vol.18 (10), p.e0291908-e0291908

2023

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Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data

Remote sensing (Basel, Switzerland), 2022-11, Vol.14 (21), p.5380

Foody, Giles M.

2022

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Classification accuracy comparison: Hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority

Remote sensing of environment, 2009-08, Vol.113 (8), p.1658-1663

Foody, Giles M.

2009

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Status of land cover classification accuracy assessment

Remote sensing of environment, 2002-04, Vol.80 (1), p.185-201

Foody, Giles M.

2002

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Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8

ISPRS journal of photogrammetry and remote sensing, 2018-08, Vol.142, p.380-388

2018

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Earth Observation and Machine Learning to Meet Sustainable Development Goal 8.7: Mapping Sites Associated with Slavery from Space

Remote sensing (Basel, Switzerland), 2019-02, Vol.11 (3), p.266

2019

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Active restoration accelerates the carbon recovery of human-modified tropical forests

Science (American Association for the Advancement of Science), 2020-08, Vol.369 (6505), p.838-841

2020

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Key issues in rigorous accuracy assessment of land cover products

Remote sensing of environment, 2019-09, Vol.231, p.111199, Article 111199

2019

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Assessing the accuracy of land cover change with imperfect ground reference data

Remote sensing of environment, 2010-10, Vol.114 (10), p.2271-2285

Foody, Giles M.

2010

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Impacts of ignorance on the accuracy of image classification and thematic mapping

Remote sensing of environment, 2021-06, Vol.259, p.112367, Article 112367

Foody, Giles M.

2021

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Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM+ Thermal Infrared Images

Remote sensing (Basel, Switzerland), 2017-11, Vol.9 (11), p.1175

2017

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The Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data

ISPRS international journal of geo-information, 2016-11, Vol.5 (11), p.199-199

2016

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Remote sensing in landscape ecology

Landscape ecology, 2023-11, Vol.38 (11), p.2711-2716

Foody, Giles M.

2023

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Making (remote) sense of lianas

The Journal of ecology, 2022-03, Vol.110 (3), p.498-513

2022

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Impervious Surface Change Mapping with an Uncertainty-Based Spatial-Temporal Consistency Model: A Case Study in Wuhan City Using Landsat Time-Series Datasets from 1987 to 2016

Remote sensing (Basel, Switzerland), 2017-11, Vol.9 (11), p.1148

2017

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The impact of imperfect ground reference data on the accuracy of land cover change estimation

International journal of remote sensing, 2009-01, Vol.30 (12), p.3275-3281

Foody, Giles M.

2009

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The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies

Transactions in GIS, 2017-02, Vol.21 (1), p.74-90

2017

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Supervised methods of image segmentation accuracy assessment in land cover mapping

Remote sensing of environment, 2018-02, Vol.205, p.338-351

2018

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Harshness in image classification accuracy assessment

International journal of remote sensing, 2008-06, Vol.29 (11), p.3137-3158

Foody, Giles M.

2008

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Impacts of Sample Design for Validation Data on the Accuracy of Feedforward Neural Network Classification

Applied sciences, 2017-08, Vol.7 (9), p.888

Foody, Giles

2017

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Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation

Remote sensing in ecology and conservation, 2021-06, Vol.7 (2), p.292-305

2021

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Good practices for estimating area and assessing accuracy of land change

Remote sensing of environment, 2014-05, Vol.148, p.42-57

2014

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Sample size determination for image classification accuracy assessment and comparison

International journal of remote sensing, 2009-01, Vol.30 (20), p.5273-5291

Foody, Giles M.

2009

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Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification

Feature Selection for Classification of Hyperspectral Data by SVM

Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient

Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data

Classification accuracy comparison: Hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority

Status of land cover classification accuracy assessment

Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8

Earth Observation and Machine Learning to Meet Sustainable Development Goal 8.7: Mapping Sites Associated with Slavery from Space

Active restoration accelerates the carbon recovery of human-modified tropical forests

Key issues in rigorous accuracy assessment of land cover products

Assessing the accuracy of land cover change with imperfect ground reference data

Impacts of ignorance on the accuracy of image classification and thematic mapping

Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM+ Thermal Infrared Images

The Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data

Remote sensing in landscape ecology

Making (remote) sense of lianas

Impervious Surface Change Mapping with an Uncertainty-Based Spatial-Temporal Consistency Model: A Case Study in Wuhan City Using Landsat Time-Series Datasets from 1987 to 2016

The impact of imperfect ground reference data on the accuracy of land cover change estimation

The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies

Supervised methods of image segmentation accuracy assessment in land cover mapping

Harshness in image classification accuracy assessment

Impacts of Sample Design for Validation Data on the Accuracy of Feedforward Neural Network Classification

Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation

Good practices for estimating area and assessing accuracy of land change

Sample size determination for image classification accuracy assessment and comparison

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