The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-3/W1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3/W1-2020, 145–150, 2020
https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-145-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-3/W1-2020, 145–150, 2020
https://doi.org/10.5194/isprs-archives-XLIV-3-W1-2020-145-2020

  18 Nov 2020

18 Nov 2020

CLOUD-BASED INTEGRATION AND STANDARDIZATION OF ADDRESS DATA FOR DISASTER MANAGEMENT – A SOUTH AFRICAN CASE STUDY

G. Tredrea, S. Coetzee, and V. Rautenbach G. Tredrea et al.
  • Department of Geography, Geoinformatics and Meteorology, University or Pretoria, South Africa

Keywords: data integration, address data, standardisation, cloud computing, cross jurisdiction semantics

Abstract. Addresses are essential for disaster risk management and response because they are used to locate people affected by a disaster or at risk of being affected. South Africa is vulnerable to disasters, however, despite a legislative framework for supporting disaster risk management that meets international standards, implementation falls short due to underfunding, poor interdepartmental coordination and lack of political support. The importance of cross jurisdictional address data was highlighted by the COVID-19 pandemic of 2020 when the geocoding of positive cases was hindered due to the lack of such address data in South Africa. In this paper, we present first results about a cloud-based tool for integrating address data from multiple municipalities into a single address dataset that conforms to the South African National Standard, SANS 1883-2:2017, Geographic information – Addresses: Part 2: Address data exchange. We reviewed and evaluated three cloud platforms for the prototype implementation. The integrated dataset is maintained in the cloud and therefore readily accessible by relevant organizations. At the same time, processing in the cloud can handle changing volumes of data with elasticity, i.e. computing power can be increased or decreased at short notice, as necessary during a disaster response. Furthermore, processing can be automated, thereby mitigating the risk of reduced manpower due to a disaster. Overall, a properly maintained cloud-based tool can result in more efficient use of resources presenting a viable and interesting alternative for underfunded disaster risk management centres in South Africa and other parts of the world.