The Integration of Geospatial and Statistical Information

By: Valrie Grant, Managing Director, GeoTechVision

Over the past two weeks, this column has focused on United Nations Global Geospatial Information Management (UN-GGIM).

The priorities and work programme of UN-GGIM are driven by UN Member States and much of the focus coming out of the fifth session of the Committee of Experts surrounds the Sustainable Development Goals that will be ratified by the UN General Assembly next month – September 2015. The UN-GGIM has been engaged in helping all to recognize that in order to measure and monitor these important goals and their targets, geospatial information is critical. One of the discussion topics and resolutions resulting from the Experts Meeting is that of integrating geospatial, statistical and other information to create a multidimensional data and information model.

What does this really speak to and why is it relevant?

Valerie Grant
Valerie Grant

There is a need for an overarching statistical-geospatial data integration framework in each country. When both statistical information and geospatial information are integrated within a geospatial-statistical framework, the resulting multidimensional information model can significantly improve the quality of official statistics and population census and the measuring and monitoring of the sustainable development goals.

This means that both the national statistical offices and the national geospatial data management authorities must lead the charge in integrating statistical and geospatial information. For this coordination to work, standards must be established and agreed on by both disciplines to ensure that integration is achieved in an effective and consistent manner. At the very onset, it must be recognized that while data collection, processing, analysis and operations are important, even more critical will be the access to that data by end users – the various stakeholders who need to make use of this critical information resource. Hence, both the statistical and the geospatial communities must determine the kinds of information products that will have real value to their various stakeholders.

Presently, many of the statistical offices in the region only use GIS for the purposes of Census mapping and for updating census maps. There is however, an increased recognition that geography is key to virtually all national statistics, providing a structure for collecting, processing, storing, aggregating and disseminating the data. As such, national statistics offices must contemplate transforming their statistical infrastructure and use this opportunity to embed geography – a spatial data framework, into their information systems and processes.

GIS is a useful tool in many different areas of statistics – population census, social and demographic statistics (health, education, labour), economic statistics (business surveys, trade, tourism, agriculture, etc.) and environment statistics. GIS can be used in all the phases of producing statistical information.

The value of geospatial data in statistics cannot be overstated – data is often analysed in the context of when and where. We are all aware of the power of place – everything and everyone is somewhere – and statisticians are uniquely aware of how boundary delineation can affect sampling and therefore their results. There are also many benefits of linking socio-economic data to a location. Linking people, business, the environment and the economy to a particular place results in a better grasp of the social and economic issues of that particular locale.

Today, there is also an increased demand for location-enabled socioeconomic data by various stakeholders. Geospatial data can significantly improve the quality (accuracy, relevance, accessibility) of official statistics. The simple fact is that the utility of statistical information increases when a spatial component is embedded, which then facilitate the building of complex multidimensional location based information resource.

The geographic dimension enriches statistical data to generate better information that is essential to economic planning and decision making. It is therefore critical that the regional governments take the lead in ensuring the development of their spatial data infrastructure as a priority.

An opportunity to integrate GIS with statistics in the region is the 2020 round of census. A quality census starts with locating all dwellings in a country, thus enabling every household to be visited thus providing a complete coverage.

Census statistics provide counts of people or households for geographical areas broken down by socio-demographic characteristics such as age, gender or employment.

Digitised boundary datasets represents the underlying geography of the census. By linking census area statistics with the corresponding locational information for a specific census year, the census attributes can be visualised on a map and provides the basis for exploring the characteristics of the census datasets which usually provides additional demographic, socio-economic and cultural insights.

The use and application of geospatial technologies is therefore beneficial at all stages of the population census process. Employing GIS will improve the efficiency in preparatory, enumeration, processing and dissemination phases of the census.

The governments of the region must therefore use the upcoming 2020 census as an opportunity to enhance the geospatial capabilities of their national statistical organizations and by so doing, develop a geospatial-statistical information infrastructure. An opportunity now presents itself for Guyana to be among the many nations that fully utilizes Geospatial Technologies in the upcoming census.

This will help the country to capitalize on many benefits including efficiency for data collection and effectiveness of data analysis, which will lead to cost savings and greater credibility and increased accuracy and better decisions.

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