Inclusive Green Infrastructures

Inclusive Green Infrastructures for Urban Wellbeing” is an interdisciplinary research project funded by the British Academy Urban Infrastructures of Well-being Programme. Our research explores the interactions between urbanisation and green infrastructures and implications for wellbeing in Wuhan, China and Ghaziabad, India. The project combines development of a web-app for land-use change analysis alongside fieldwork with peri-urban farmers and residents in the two cities.

The web-app provides a novel approach to combining deep learning techniques with visual image analysis to map land-use change across multiple scales using satellite imagery. The deep learning integration is enabled via a data labeling interface (to generate training data) and a label correction interface (to evaluate and correct the results of the AI classifier). Presentation of land-use maps is facilitated through an interactive mapping interface and a modeling system enables spatiotemporal analysis on multiple map layers which can be viewed as overlays on the map or saved as new map layers.

Our hope is that the web-app can be used by others to support research and stakeholder engagement on urban sustainability policy and landscape management. It also has the potential to enable integration of citizen science methods and crowd sourced data analysis with new and evolving deep learning techniques for image analysis in many fields including and beyond land-use classification.

It is currently being used and further developed as part of a £12.5m pilot programme, ‘Nature-based Solutions for Climate Change at the Landscape Scale’. This is a Defra - BEIS project supported by the Treasury’s Shared Outcomes Fund and led by Natural England, Environment Agency, RBG Kew and the Forestry Commission.

Our project website presents details of the research, a description of the web-app and a summary of project outputs.

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Akash Vashishtha

Environmental lawyer

Baoshan Li

Zhongnan University of Economics and Law

Researcher

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Dr Jonathan Dolley

SPRU, University of Sussex

Research Fellow

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Dr Krishna Chaudhary

Jawaharlal Nehru University, New Delhi

Researcher, Centre of Social Medicine and Community Health

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Dr Kumud Teresa

Jawaharlal Nehru University, New Delhi

Researcher

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Dr Novi Quadrianto

Predictive Analytics Lab

School of Engineering and Informatics, University of Sussex

PI, Reader in Machine Learning

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Dr Rajashree Saharia

Jawaharlal Nehru University, New Delhi

Researcher, Centre of Social Medicine and Community Health

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Dr Sayan Das

Jawaharlal Nehru University, New Delhi

PhD Research Scholar, Centre of Social Medicine and Community Health

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Georgios Voulgaris

Predictive Analytics Lab

School of Engineering and Informatics, University of Sussex

Research Student

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James Robinson

Predictive Analytics Lab

School of Engineering and Informatics, University of Sussex

Research Fellow & Web Developer

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Prof Fiona Marshall

SPRU, University of Sussex

PI, Professor of Environment and Development

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Prof Jeremy Reffin

Predictive Analytics Lab

School of Engineering and Informatics, University of Sussex

PI, Research Professor

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Prof Ramila Bisht

Jawaharlal Nehru University, New Delhi

Professor, Centre of Social Medicine and Community Health

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Prof Ritu Priya

Jawaharlal Nehru University, New Delhi

Professor, Centre of Social Medicine and Community Health

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Prof Sanwei He

Zhongnan University of Economics and Law

Associate Professor

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Prof Shijun Ding

Zhongnan University of Economics and Law

Dean of School of Business Administration

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Shubham Mishra

Urban planner and PhD candidate

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Sushil Ragav

Environmental activist

Wenmin Ye

Zhongnan University of Economics and Law

Researcher

Yuyang Liu

Zhongnan University of Economics and Law

Researcher

Story Maps

Ghaziabad Story Map 2
Ghaziabad Story Map 2
Ghaziabad Story Map 1
Ghaziabad Story Map 1
Wuhan Story Map
Wuhan Story Map

Web-app

The idea behind the web-app
The idea behind the web-app

This research is funded by the British Academy’s Urban Infrastructures of Well-Being 2019 Programme, supported under the UK Government’s Global Challenges Research Fund