Experiences in Designing a Mobile GIS Mapping Tool for Rural Farmers in Ghana

Proceedings of the 4th Annual Symposium on Computing for Development

Sunandan Chakraborty, Tiffany Tong, Jay Chen, Afshan Aman, Talal Mufti, Yaw Nyarko, Lakshminarayanan Subramanian

The task of balancing problems associated with population growth and food production has often been impaired by a lack of accurate information on food supply availability in any given region or time. Such data has conventionally been gathered by legions of field workers who must travel to individual farms and collect information by hand. Predictably, data collection has been slow, error-prone, and difficult to maintain. There is therefore a need to develop tools and techniques that can quickly and accurately generate relevant and up-to-date information on food production. In this paper, we describe our experience in designing and implementing an Android mobile application (or “app”) that is capable of building GPS-based food production maps of a region. This hand-held app collects data as the user walks along the boundary of a farm. It records the user’s movement by tracking the GPS coordinates and subsequently constructs the boundary of the farm. The user has various options to enter key information about the farm, such as the crop that is currently being cultivated in the bounded region. The user can enter additional metadata through audio recording and photo capturing features of the app. We field-tested our app in the Hohoe Municipality of the Volta region in Eastern Ghana with local farmers and agricultural extension agents. Based on observations and user feedback from these repeated trials, a revised version of the app was deployed in Hohoe, in April 2013. Here, 11 farmers were recruited as data collectors, including local leaders of community Farming Based Organizations (FBOs) and Ministry of Food and Agriculture (MOFA) Agricultural Extension Agents (AEAs). After using the app for 10 days, 201 farm boundaries and numerous other observations about the farms were collected from the municipality and uploaded to a remote server for further analysis. From this aggregated information, we were able to collect a snapshot on the current agricultural practices and productivity of the region.