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Monday, 13 January 2014 06:00

Demographic Explorer for Climate Adaptation (DECA)–An Automated Spatial Analysis Tool

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We are happy to announce that with the collaboration with Wolfram Solutions (https://www.wolfram.com/), the Demographic Explorer for Climate Adaptation (DECA) – An Automated Spatial Analysis Tool is now available on POPClimate: http://popclimate.net/deca.

We have featured the two DECAs, DECA Semarang, Indonesia and DECA Malawi, on POPClimate. You can access and conduct analysis through DECA online, download DECA to a local disk, or share the tool elsewhere. We encourage you to share any comments or interesting findings from your interaction with the DECA on DECA Gallery (http://popclimate.net/deca/deca-gallery).

Background

Geospatial analysis using Geographic Informations Systems (GIS), combined with the techniques of remote sensing, have been widely applied to monitor the Earth’s surface features and climate change related environment characteristics, as well as explore their social-economic implications by linking these characteristics with population, social and economic data. Despite the powerful map-based spatial analysis of GIS available today, it is not easy for non-geographers to manipulate and understand. Most existing online tools provide limited population data, data integration ability, and are designed with a focus on visualization instead of spatial analysis. This creates an obstacle to applying evidence-based analysis to policy-making processes. Through our previous work assisting countries with planning for and adapting to climate change, we felt an urgent need to make analysis easier to design, implement, and understand, and thus encourage participation by social scientists, disaster risk reduction practitioners, multi-level government, planner, climate-related organizations and the general public.

Based on the above observations, we developed the Demographic Explorer for Climate Adaptation (DECA) – an automatic spatial analysis tool, via a technical partnership with Wolfram Solutions, and based on the concepts, methods and case studies in “The Demography of Adaptation to Climate Change”(http://www.unfpa.org/public/home/publications/pid/13218). The objective of the development of the tool is to support the analysis of incorporating population dynamics into climate change adaptation and national development strategies.

The online DECA tool is the first, innovative tool for automated integration and analysis of multiple kinds of spatial data. It aims to fill in knowledge gaps in social, environmental, and science-policy by involving stakeholders into the spatial analysis and decision-making process.

Firstly, the DECA tool will provide a much simpler and straightforward approach to incorporating various data, particularly census data and other social survey data, into planning for climate change adaptation though spatial analytics. Unlike existing spatial analysis software, DECA assembles all the data into the tool, lists breakdown variables into detailed categories (e.g. hazard levels, land use type, housing materials, age groups, education levels, infrastructure types), so that the user can combine any categories based on specific groups of people or targeted geographic areas. All these analysis can be conducted automatically, so can be learned by the user with the minimal previous analysis experience. Through the tool, the data analysis capacity of countries, especially the least-developed countries, could potentially be enhanced.

Secondly, DECA will be a helpful tool to support climate-change adaptation programmes that are carried out by local and national governments with the support of other UN agencies and NGOs. For example, the National Adaptation Plans (NAPs) supported by the UN Framework Convention on Climate Change (UNFCCC) could benefit from this online tool. United Nations Development Programme (UNDP)’s Third National Communication to the UNFCCC, which aims to strengthen the climate-change mitigation, adaptation, and environmental sustainability measures in targeted vulnerable provinces, sectors and communities, might also find this online tool is valuable for their project. It is also our hope that DECA tool could assist the Task Force on Climate Change Related Statistics in analysis or research related to climate change.

Thirdly, DECA will increase the public awareness of climate change. DECA is an online tool and free to access by the public (assuming that data providers agree). It will enhance communication among scientist, decision-makers, stakeholders and general public in the issues of population and climate change, and enhance the linkage of analysis with policy formulation. The general public will benefit from the tool, as they can see the level of climate-change risk, the socioeconomic status of the neighborhood where they are located, and thus strengthen their individual awareness of the need for adaptation.

Features of the DECA tool

We have developed the tool by generating two DECAs: Malawi country and Semarang district, Indonesia. Both countries have recently completed national censuses in formats that allow for mapping at local level – a characteristic of many of the censuses conducted in 2010. The study selected variables and indices to identify local vulnerability and adaptive capacity at ‘small area’ level, including population size, population density, age, gender, education, occupation, female-headed households, migration and mobility, household conditions, and access to resources and services.

Data applied in the Malawi DECA tool include Malawi census data from 2008, flood risk data generated by hydrological analysis combing open-source elevation, precipitation, and water system data. The DECA tool built for Semarang, Indonesia profile brings together the 2010 census data received from the National Statistical Office, administrative spatial data, infrastructure and land-use data from Geospatial Information Agency, and climate hazard maps from the National Agency for Disaster Management. The main features incorporated in the DECA tool reflected in the two country profiles include:

(1) Integration of multiple types of geo-referenced data. The tool provides the user the ability to specify particular combinations of data layers via a selection function or toggle, as well as different vulnerability indicators generated for instance from census data, such that the combinations of layers and indicators are generated and visualized. For example, Figure 1 below is the Malawi DECA interface. Average precipitation from December to April (rain season) in Malawi is selected as Property 1, and the adjusted Secure Tenure Index (STI), which is a gives a quantitative estimate of slums, is selected as Property 2. The STI is used to track progress towards Millennium Development Goal 7.10. In the “Selection of village by property”, we select the villages (here in Malawi, is Traditional Authority areas) with low STI and high precipitation. The selection criteria are highlighted by bold black circles at the lower-left corner of the legend in the left panel. The DECA tool then finds the targeted villages that fit the criteria, and illustrates the characteristics and locations of these villages through the associated maps, tables and figures. The analysis results have two sections: for “all villages” and for the “selected villages”.

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Figure 1. Analysis of villages with low Secure Tenure Index in high precipitation area using the Malawi DECA as an example.

Figure 2 provides another example of data integrations using the Indonesia DECA. It shows the villages that exposed in the high flood zones and with high dependency ratio in the Semarang district. The spatial distribution of education buildings is also integrated in the data analysis. It demonstrates how indicators of population data can be combined with infrastructure data, and climate-related hazard data through the DECA tool.

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Figure 2. Analysis of villages with high dependency ratio in the high flood risk areas using the Indonesia DECA as an example.

(2) Customized inputs for automated analysis. The DECA tool allows the user to conduct automated analysis based on specific needs. The user can combine the variables based on existing variables in the database (e.g. combine age groups, school attendance at different education levels, housing material types, or land use types), select inputs by gender, by total “count” or “proportion”, select particular types of infrastructure by checking each individual category, select the cross-legend of the low-high levels of two properties (e.g. high flood risk and high population density), select particular areas by typing village names, or by directly clicking the map. Figure 3, the Indonesia DECA data input panel, illustrates how a user can customize data input, determine the variables, and conduct a specific analysis.

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Figure 3. Customized input selections and combination of variables by different approaches.

(3) Analysis results adjusted in real time to reflect analysis choices made by the user. Based on customized inputs, the tool automatically generates analytical maps and accompanying tables and figures on analysis results to facilitate the examination of population and related data on climate vulnerability. For example, the user can change the selection of the hazard risk level and the age group, and the analysis results at the right panel of the interface will be adjusted correspondently in order to evaluate the vulnerability and adaptable capacity of the individuals and households in the selected zones (Figure 4). In the next step of the DECA development, the user will be able to “lock” the selected villages while switching to other properties to investigate more characteristics of the selected villages, e.g. other population characteristics, housing conditions, service accessibility through the tables and figures. Similarly, the further improvement of the tool will also allow selection within the results, i.e. clicking the villages with certain features directly in the histograms will correspondently highlights these villages in the map, and the analysis will be changed simultaneously.

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Figure 4. Real-time analysis results visualization.

Results of the analysis have the potential to contribute to Malawi and Indonesia’s National Adaptation Programmes of Action. Malawi in particular lacks strong data on either historical climate hazards or existing hazard exposure areas, so the tool will provide a valuable approach in analyzing environmental hazard and the population aspects of climate vulnerability.

Future work

These two DECAs in Malawi and Indonesia present a prototype of the online automated analysis tool. It demonstrates significant potential for our future work, which will involve improvement and replication to include more countries. Specifically, major work starting from the year 2014 will concentrate on:

(1) Expand the spatial analysis. The second stage in the development of DECA aims to enhance the geographic analysis related to climate change, such as calculating the distance from villages to roads (adaptation capacity), from villages to rivers (flooding vulnerability), from villages to hospitals (adaption capacity), buffer zones of hospitals and schools (service area), as well as the distance among villages (isolation). Statistical analysis and modeling tools will explore the interactions between population dynamics and climate change.

(2) Include temporal analysis. The current stage of the tool uses one-year data; the future work might include data from different years, providing both spatial and temporal analysis, and long-term monitoring of changes in the environment and human vulnerability.

(3) Scale up to more countries. One advantage of the DECA tool is that it is easily replicable. We started with the countries of Indonesia and Malawi, and will replicate the project by building data from other countries into the DECA. In 2014, we will be working on the Maldives and potentially Zambia DECA, and aim to provide services to more countries and regions by building country-specific DECA tools and carrying out training for governments who are developing and implementing adaptation initiatives.

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