Capturing social sensing of farming activities for policymaking in fragile contexts

Social sensing data are lacking particularly in fragile and conflict-affected communities (FACAC). Stakeholder specific data are however needed to identify vulnerabilities and exposure to hazards. Climate vagaries, environmental degradation, high political pressure, shrinking economy predominantly dependent on agricultural production, and violent conflict characterize challenges of many developing countries. Based upon our experience in collecting geospatial datasets on farm management practices in the African Sahel, we address key questions: Which approach to comprehensive social data acquisition is suitable and promising particularly in FACAC? Can such an approach mitigate shortages in data availability arising from insufficient or failing government structures? To this end, we present challenges encountered, opportunities and key lessons. We aim to offer a guiding blueprint for researchers and practitioners to organize farm-level surveys in fragile and conflict-affected states. A survey was developed and used in Sudan by means of a smartphone app and in traditional paper form. The survey took place during the period spanning July 2022 to April 2024. Challenges such as sampling under non-updated census, lack of logistics, technology, financial limitation, distrust, low women representation, remoteness and vastness of localities, lacking infrastructure, and dialect often limit the access to different groups of farmers. Using international cooperation of Sudanese and German researchers, involving official staff and locals, and a balanced use of traditional as well as Information and Communication Technology (ICT) approaches facilitated a successful data collection campaign. The survey resulted in >1800 interviews with over 70 questions pertaining to three different farming systems, namely traditional and mechanized rainfed as well as irrigated systems. Our results and recommendations show that conducting social sensing at the farm level in challenging situations can be effectively achieved as a basis for research and policy intervention.