Sussex Sustainability Research Programme

Understanding trade-offs between SDG's in urbanising contexts

We developed a web-app and a method to visualise urban development, food security and poverty trade-offs and synergies, and to support stakeholder engagement.

SDGs

SDG 1SDG 2SDG 3SDG 6SDG 11SDG 15

The team

Principal Investigator (PI) and Co PI details

Principal Investigator

Co-Investigators

Project team
Partners
  • Professor Shijun Ding, ZhongNan University of Economics and Law, Wuhan, China
  • Professor Ritu Priya, Jawarhalal Nehru University (environment, health and participatory research), India
  • Prof Madhoolika Agrawal, Banaras Hindu University (pollution impacts on food systems); Ravi Agrawal Toxicslink NGO (policy engagement);
  • Priyanie Amerasinghe, International Water Management Institute (Ecosystem service mapping).

Where we worked

Wuhan, China and Varanasi, India.

Project title

Understanding trade-offs between SDGs in urbanising contexts: Novel methods of mapping rural-urban interactions in food systems to analyse risks and opportunities for environmental and human health.

Overview

Rapid urbanisation creates trade-offs between development, food security and poverty alleviation goals which are often ignored or invisible. Revealing and communicating the nature and scale of these trade-offs to policymakers is a key step towards achieving SDGs around urban sustainability and resilience. Our project applies deep learning techniques to map peri-urban agriculture in Wuhan, China and Varanasi, India and explores ways of integrating multiple types of data through a web-based mapping and visualisation tool to support research and stakeholder engagement on urban sustainability policy.

Full project description

Scientists working on social and ecological aspects of food systems and computer scientists have been working closely together to develop a web-app. Dr Novi Quadrianto worked with Bradley Butcher and Abetharan Antony to develop the deep learning aspects and implement the modelling/visualization aspects of the work.

Dr Jonathan Dolley was responsible for generating training data for the deep learning methods and providing insights from fieldwork to help specify the goals of the deep learning analysis.

As Principal Investigator (PI), Professor Fiona Marshall had oversight of the whole process of collaboration across the team and provided guidance on the desired functions of the web-app and its potential use in transdisciplinary research and stakeholder engagement.

Dr Jeremy Reffin was involved in facilitating our interdisciplinary collaboration and advising on implementation strategy while Professor Andy Philippides provided expert guidance on the modelling aspects of the project. Other members of the team (Professor Ann Light, Professor Jorn Scharlemann, Professor Gordon McGranahan and Dr Emily Lydgate) provided advice and input on development of the prototype web-app and strategy for attracting funding for a larger project incorporating further development of this project.

Following completion of the prototype, short fieldwork and seminars were held in China and India to explore methods for using the web-app in policy dialogue and transdisciplinary research and get feedback on its further development. A regional policy workshop was organised for higher-level discussions. Outputs from the project included a methodology paper for journal publication and a research protocol for use of the web-app within transdisciplinary research and policy dialogue contexts.

Finally, we aim to develop a funding proposal for a larger consortium on urban sustainability research which incorporates the web-tool within a larger transdisciplinary research program.

Timeline and funding

The project started in April 2017 and continued until September 2018. Total project funding was £99,369.

Methods 

Migrant peri-urban farmers in fields (Wuhan)Fig 1:Migrant peri-urban farmers in fields (Wuhan) 

 

Village housing being demolished for redevelopment (Wuhan)Fig 2: Village housing being demolished for redevelopment (Wuhan)

We created a web-app that allows non-experts to analyse land-use change using built-in deep learning techniques and freely available satellite imagery and create simple models to visualise the diverse impacts of that land-use change. This approach enabled us to detect changes in agricultural land-use that are not picked up through conventional land-use classification techniques and even, in the case of intensive vegetable cultivation, to identify the presence of migrant tenant farmers. We tested and demonstrated the web-app with a case study of peri-urban land-use change in Wuhan, China and have begun further testing through another case study of Ghaziabad, India.

Findings 

 

In the Wuhan case, we used the web-app to analyse land-use change in a peri-urban district drawing on qualitative data from a previous project. Our analysis revealed a transformation in peri-urban agriculture in tandem with urban expansion. This agricultural transformation involved the conversion of grain and cotton fields into intensive vegetable cultivation, a large proportion of which was by migrant farmers. It showed that a hidden impact of urban expansion was the displacement of these migrant farmers who lost livelihoods and homes. This highlighted the extent of migrant involvement in the type of peri-urban agriculture most critical to urban food security. It also revealed the double-edged sword of urbanisation creating new opportunities for migrants to establish agricultural livelihoods while constantly facing the negative impacts of periodic displacement.

Finally, the analysis highlighted the increasing risk to food safety posed by recent urbanisation patterns which increasingly placed intensive vegetable cultivation in close proximity to potentially polluting industry. This reveals the hidden trade-offs with food safety (SDG 2) and inequality (SDG 10) which are closely connected to the changing role of informal migrant farmers in peri-urban agriculture and the impacts of urbanisation on their livelihoods.

Web-app demo graphicFig 3: Web-app demo graphic

Conclusion

We have created a prototype web-app that can be used by non-experts to visually show the hidden characteristics and impacts of peri-urban transformations and inform new approaches to city-region planning. It has the potential to support research into peri-urban dynamics and the inclusion of diverse stakeholder perspectives in agenda setting. It will be particularly helpful in enhancing our ongoing programme of action research concerned with sustainability transformations in peri-urban India, China and elsewhere.

Related work

An event was held at the Indian Council of Agricultural Research in Delhi in March 2018 which included discussion of the project. It was organised bythe International Council for Local Environmental Initiatives (ICLEI) - local local governments for sustainability - in collaboration with Ecosystem Services and Poverty Alleviation (ESPA) and members of the Sussex Sustainability Research Programme (SSRP) team.

'What does the future hold for Delhi’s urban farmers' in Medium.com.

'Why peri-urban ecosystem services matter for urban policy', ESPA Policy Briefing.

'Tackling poverty and food security: lessons from India’s peri-urban frontier', IIED Briefing.

'India’s peri-urban frontier: rural-urban transformations and food security', IIED report.