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Participatory action-research for improved land governance in Senegal. Using geo-information tools to assessing agribusiness dynamics as means to empower local communities

Valette E., Bourgoin J., Guillouet S.. 2016. Washington : AAG, 1 p.. AAG Annual Meeting, 2016-03-28/2016-04-02, San Francisco (Etats-Unis).

A number of scholars have underlined the potential risks caused by the global land acquisition phenomenon (Robertson and Pinstrup -Andersen, 2010; Von Braun and Meinzen-Dick, 2009) . Amongst other hindrances, large -scale land acquisitions are usually depicted as poorly negotiated with local farmers and that unfair or nontransparent trade arrangements tend to foster reasonable suspicions and conflicts with and within local communities. Unofficial (e.g. NGO assessments) and official data sources at the country level can show discrepancies, and none may actually reflect reality on the ground. This acknowledgement leads to an urgent need of relevant and ac countable data on the forms and dynamics of agribusiness and their interactions with family farming in developing countries (Cotula, 2012). Local communities would strongly benefit from geospatial information on land acquisitions: mapping being "an intrinsically political act" (Peluso, 1995), the access to - and the control of - this information would inherently increase their negotiation capacity, enhance the transparency in land deals and strengthen the accountability of land investors. In Senegal, we designed a participatory action-research project in partnership with the National Observatory of Land Governance. This platform is an initiative of the civil society, and aims at gathering counter-information on land deals and landscape dynamics at the national level. The methodology we developed consisted in strengthening a network of farmers throughout the country that could contribute the upscale spatial data. Secondly, we designed a participatory mapping methodology, combining both participatory mapping and web -mapping, that is accessible to all stakeholders, yet robust to produce relevant data.

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