Descrizione del progetto
Esaminata la governance fondiaria in Africa meridionale
Il progetto InSiTe-LandGov, finanziato dall’UE, combinerà megadati con approcci qualitativi per generare nuovi set di dati e metodi a libero accesso sulla governance delle risorse naturali, che saranno testati utilizzando i dati esistenti provenienti da oltre 5 000 terreni di ricerca distribuiti nella zona boschiva più grande della savana, che si estende in 12 paesi dell’Africa meridionale. Tale bioma fondamentale svolge un ruolo importante nel mitigare gli impatti dei cambiamenti climatici, preservare la biodiversità e ridurre la povertà. InSiTe-LandGov classificherà i metodi attuali di osservazione della governance delle risorse e genererà un nuovo set di dati a libero accesso per l’intero bioma delle zone boschive dell’Africa meridionale, utilizzando l’apprendimento automatico, i dati satellitari e i terreni di ricerca. Infine, InSiTe-LandGov esaminerà il modo in cui gli aspetti della governance delle risorse influenzano il degrado ambientale e la povertà nella regione.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinatore
10691 Stockholm
Svezia