Giles Foody

Professor of Geographical Information Science

University of Nottingham

United Kingdom

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Professor Giles Foody is a faculty member at the University of Nottingham, UK, specializing in Geographical Information Science. His research areas encompass dynamic surface water mapping, deep learning applications in environmental monitoring, and the relationship between spatial data and socio-economic factors. Recent articles highlight innovative methodologies for classifying water bodies and analyzing environmental challenges, particularly in the context of sustainability and climate change.

Articles (18)

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2025

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2023

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2022

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2022

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2022

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2022

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2022

Collaborators (10)

Catherine Waite

University of Cambridge

UNITED KINGDOM

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Zoe Trodd

University of Nottingham

UNITED KINGDOM

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Richard Field

UNITED KINGDOM

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Susan Ustin

Professor

University of California, Davis

UNITED STATES

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Sruthi Krishna Moorthy Parvathi

University of Oxford

UNITED KINGDOM

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Vítězslav Moudrý

CZECH REPUBLIC

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Doreen Boyd

University of Nottingham

UNITED KINGDOM

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Geertje van der Heijden

Associate Professor

University of Nottingham

UNITED KINGDOM

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Stefan Schnitzer

Professor

Marquette University

UNITED STATES

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Jessica Decker Sparks

Research Assistant Professor

Tufts University Friedman School of Nutrition Science and Policy

UNITED STATES

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Giles Foody

Research Interests

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Articles (18)

The future of decent work: Forecasting heat stress and the intersection of sustainable development challenges in India's brick kilns

Dynamic surface water fraction (DSWF): Global surface water fraction mapping at 10-meter spatial resolution with Sentinel-2 imagery in Google Earth Engine

Using an Area-Weighted Loss Function to Address Class Imbalance in Deep Learning-Based Mapping of Small Water Bodies in a Low-Latitude Region

Characterising the Thematic Content of Image Pixels with Topologically Structured Clustering

DeepWaterFraction: A globally applicable, self-training deep learning approach for percent surface water area estimation from Landsat mission imagery

Ground Truth in Classification Accuracy Assessment: Myth and Reality

Spatial–Temporal Analysis of Greenness and Its Relationship with Poverty in China

Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies

Spectral Characteristics of Beached <i>Sargassum</i> in Response to Drying and Decay over Time

Deep Feature and Domain Knowledge Fusion Network for Mapping Surface Water Bodies by Fusing Google Earth RGB and Sentinel-2 Images

Unmixing-Based Spatiotemporal Image Fusion Based on the Self-Trained Random Forest Regression and Residual Compensation

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

The Spectral Species Concept in Living Color

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

Towards an Automated Approach for Monitoring Tree Phenology Using Vehicle Dashcams in Urban Environments

Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project

Making (remote) sense of lianas

Superresolution Land Cover Mapping Using a Generative Adversarial Network

Collaborators (10)

Catherine Waite

Zoe Trodd

Richard Field

Susan Ustin

Sruthi Krishna Moorthy Parvathi

Vítězslav Moudrý

Doreen Boyd

Geertje van der Heijden

Stefan Schnitzer

Jessica Decker Sparks

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