Guidelines for creating framework data for GIS analysis in low‐ and middle‐income countries. (8th August 2016)

• Record Type: Journal Article
• Authors: Makanga, Prestige Tatenda; Schuurman, Nadine; Sacoor, Charfudin; Boene, Helena; von Dadelszen, Peter; Firoz, Tabassum
• Is Part Of: Canadian geographer. Volume 60:Number 3(2016)
• Page Start: 320
• Page End: 332
• Publication Date: 2016-08-08
• Subjects: framework data -- health GIS -- data capture -- global maternal health -- manual digitizing; données de référence -- SIG de la santé -- saisie de données -- santé maternelle mondiale -- numérisation manuelle; Geography -- Periodicals; 910
• DOI: 10.1111/cag.12295
• Languages: English
• ISSNs: 0008-3658

Abstract

Abstract : Health sciences research is increasingly incorporating geographic methods and spatial data. Accessing framework data is an essential pre‐requisite for conducting health‐related geographic information systems (GIS) research. However, in low‐ and middle‐income countries (LMICs) these data are not readily available—and there is a lack of coordinated data creation and sharing. This paper describes a simple set of strategies for creating high‐resolution framework data in LMICs, based on lessons from a maternal health GIS project—"Mapping Outcomes for Mothers"—conducted in southern Mozambique. Data gathering involved an extensive search through public online data warehouses and mapping agencies. Freely available satellite image services were used to create road centrelines, while GPS coordinates of households in the study area were used to create community boundaries. Our experience from this work shows that manual digitizing is becoming cheaper and faster, due to increased availability of free satellite image services and open mapping standards that allow for distributed data capture. Involving mapping agencies in data capture processes will likely promote the scaling up of framework data creation in LMICs. This will benefit health GIS research in these settings. Key Messages: While some framework data are available in LMICs, there is a lack of coordinated effort to create and share these data to support health GIS research in these settings. Manual digitizing can be used to generate framework data, and is increasingly becoming cheaper and faster due to widely available free satellite imagery and open mapping standards that allow distributed data capture. Efforts to create framework data should be done in collaboration with local mapping authorities that have the mandate for creating these data at scale.