Project description
Land governance in southern Africa examined
The EU-funded InSiTe-LandGov project will combine Big Data with qualitative approaches to generate new open access datasets and methods on natural resource governance. These will be tested using existing data from more than 5 000 research plots spread across the world's largest savannah woodland, covering 12 southern African countries. This key biome plays a major role in mitigating the impacts of climate change, maintaining biodiversity and alleviating poverty. InSiTe-LandGov will classify current methods for observing resource governance and generate a new open access dataset for the entire southern African woodland biome, using machine learning, satellite data and research plots. Lastly, InSiTe-LandGov will examine how aspects of resource governance affect environmental degradation and poverty across the region.
Objective
InSiTe-LandGov combines big data with qualitative approaches to generate new open access datasets and methods on natural resource governance—a critical data gap in sustainability science. It will test these using existing data from a unique network of >5000 research plots across the world’s biggest savannah woodland, spanning 12 countries in southern Africa. This biome is key to European and global climate change, biodiversity and poverty alleviation goals: it supports the livelihoods of 150 million people, stores as much carbon as the Congo Basin, and is home to iconic megafauna, yet it suffers some of the highest rates of deforestation and poverty on Earth. Improved understandings of resource governance will be crucial to meeting these challenges, but empirical methods for assessing governance remain opaque, costly and spread across several disciplines. First, I will produce a typology of current methods for observing resource governance that bridges the divide between positivist and constructivist approaches. I will do this through a systematic review and workshops with experts from Europe, North America and southern Africa. Second, I will generate a new open access dataset on governance for the entire southern African woodland biome. I will use machine learning, open access ‘big’ satellite and census data, the >5000 research plots, and a field visit to Mozambique and Zimbabwe. Finally, I will produce a world-first analysis on how aspects of resource governance affect environmental degradation and poverty across the region. I will use a novel approach combining qualitative and big data methods. In this fellowship I aim to build on my existing skills to define myself as a global expert in interdisciplinary governance research, and to secure a long term job at a European university. I will draw on the expertise of supervisors at three world-class hubs of sustainability research: McGill University, University of Edinburgh and the Stockholm Resilience Centre.
Fields of science
- social sciencessociologygovernance
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesearth and related environmental sciencesenvironmental sciencessustainability sciences
- social sciencessociologydemographycensus
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
10691 Stockholm
Sweden