Geographic Vulnerability Analysis Exercise

Vulnerability of Population to Flood Risk in Malawi
Vulnerability of Population to Flood Risk in Malawi

My experience reading national climate change adaptation plans from developing countries is that their vulnerability analysis and synthesis could be improved with geographic analysis! In response, Eliza Drury and I reviewed and developed guidelines for Geographic Vulnerability Analysis in Developing Countries. I took Eliza’s geographic vulnerability analysis work on Malawi in ArcGIS and translated it into an exercise in open-source QGIS: GIS software any developing country planner or NGO can afford! The exercise is designed for anyone who has already taken an introductory course in any GIS software. I gave the exercise to my seminar in Geographies of Climate Change Adaptation and Development in Spring 2016 and edited it based on student feedback. Several students then successfully applied GVA in their own research projects.

Geographic Vulnerability Analysis in Developing Countries

Eliza Drury worked with me over the summer of 2015 in the Climate and Development Lab at Brown University to analyze geographic analysis in national adaptation programmes of action and apply geographic vulnerability analysis to the test case of Malawi’s climate change adaptation plans. We wanted to test whether adaptation plans really prioritized the places where climate change vulnerability is greatest, as defined in the adaptation planning process itself. We found that very few countries used geographic vulnerability analysis, but that the method helped improve the quality of proposed adaptation projects (see diagrams below).

National adaptation planning without geographic vulnerability analysis does not recognize interactions of vulnerability between sectors or develop projects cutting across sectors.
National adaptation planning without geographic vulnerability analysis does not recognize interactions of vulnerability between sectors or develop projects cutting across sectors.
National adaptation planning with geographic vulnerability analysis. Improvements are signaled with red font color. GVA helps identify interactions of vulnerability between sectors and plan cross-sectoral adaptation projects targeting the most vulnerable locations.
National adaptation planning with geographic vulnerability analysis. Improvements are signaled with red font color. GVA helps identify interactions of vulnerability between sectors and plan cross-sectoral adaptation projects targeting the most vulnerable locations.

We reviewed methods and guidelines for national adaptation planning provided by developing countries by the UNFCCC and Least Developed Countries Expert Group (LEG), and found that geographic analysis was recommended, but guidance was out of date. In response to this, Eliza took on senior work in environmental studies with myself and Dr. Timmons Roberts to update guidance for developing countries to use geographic vulnerability analysis using Malawi as an example case. She presented this work at the climate change research conference in Bangladesh and fulfilled an invitation to write a summary of the work for the Dhaka Tribune.

As final products, we are publishing a Technical Guide to Geographic Vulnerability Analysis (with Eliza as lead author) and an applied Geographic Vulnerability Analysis Exercise.

Thematic Mapping for Medical Residents

I’ve been facing an interesting challenge: is it possible for residents in medicine, with very limited time, to create reasonably high quality cartographic representations of health indicators?  I think so!  I need two things:

  1. A more or less fool-proof spatial database of health indicators with data at the sub-county level.  I’m working in Rhode Island here, and we only have five counties!
  2. An interactive thematic mapping tool that makes it easy for intelligent medical residents, inexperienced in cartography or GIS, to create quality maps.

For #1, I found the Centers for Disease Control and Prevention Social Vulnerability Atlas, which allows you to download the social vulnerability index and all of its component indicators by census tract for any state.

For #2, I found the online thematic mapping tool, indiemapper, recently made free to the public by its developers at axismaps.

Here are the results of my experiment, followed by some thoughts and specific steps taken to create this map.

CDCSVIRI

Benefits of indiemapper
  • No installation required: just run it in your web browser!
  • Save your work as an .imp file, inclusive of all your data, symbology and the page layout.
  • Default symbology is easy on the eyes, and choropleth maps use Cynthia Brewer’s ColorBrewer. You can choose equal interval, optimal breaks, or quantile classifications and the tool displays a small colorized histogram.
  • Supports multivariate choropleth maps, dot density maps, proportional symbols, and cartograms.
  • Supports several different projections and automatically customizes projection parameters for the extent of your data.
  • Exports maps as a flat jpg or png images or as layered vector svg images which can be edited in Adobe Illustrator or similar open source software like Inkscape.
  • Straightforward cartographic advice and explanation of cartography jargon in Learn More menus.
Limitations of indiemapper

(disclosure: this is based on knowledge accumulated through 4 hours or so of experimentation)

  • All uploads should use the WGS 1984 geographic coordinate system (epsg code: 4326)
  • I could only successfully upload single-part features, and this could be quite problematic for thematic mapping. On one hand, you can use GIS to convert multi-part shapefiles to single-part shapefiles and then upload them. On the other hand, this can seriously distort your data distributions for optimal breaks or quantile classifications by duplicating the data values for every part of a feature.
  • You cannot rename layers or attributes, and this includes legends.
  • You cannot select subsets of layers or exclude any data values from classification.
  • You cannot upload image/raster graphics.
  • Text is always aligned to the left.
  • There is no scale ratio or scale bar. To be fair, the app seems to have been designed primarily for global thematic maps, for which scale is not constant.
  • No support for legend customization, and thus no way to edit “RPL_Themes” on the map above. Each legend includes just one data layer, and legends are only available for layers symbolized with classes or gradients.
  • Unlike Google’s My Maps, I have not reached a limit on the number of attributes (maximum of 50 with My Maps) and files uploaded with the correct attribute data types, (My Maps requires you to duplicate any numerical field!)
Making this Social Vulnerability Map
  1. Create the water and service area layers in QGIS: Prior to making this map, I had downloaded 2010 Census Data for Rhode Island at the census block level from RIGIS.  Using QGIS, I saved the data layer in the WGS 1984 geographic coordinate system and separated water from land. I dissolved the census blocks into towns, and selected Pawtucket and Central Falls, the two towns in the Memorial Hospital service area based on the Dartmouth Health Atlas.
  2. Create the social vulnerability layer in QGIS: I downloaded the Rhode Island social vulnerability atlas data by census tracts from the CDC SVI Atlas, and downloaded a guide to the index and component attributes. In QGIS, I saved the layer in the WGS 1984 geographic coordinate system and then converted from multi-part to single part. I realized that two census tracts had no population and values of -999 for social vulnerability percentiles, which really distorts indiemapper’s classifications. Therefore I selected all the features with RPL_THEMES >= 0. In simpler terms, I selected just the census tracts with legitimate data and saved them to a separate file.
  3. Upload data to indiemapper: I launched indiemapper and uploaded my three data layers (hospital service area, water, and social vulnerability) with their shp and dbf files.
  4. Organize and symbolize data layers: I placed the layers in the following order: hospital service area on top, followed by water and social vulnerability.   Social vulnerability is symbolized as a choropleth data layer with the RPL_THEMES attribute.
  5. Page layout, map projection and extent: The portrait page layout is best for Rhode Island, and I zoomed the map extent to the social vulnerability layer. From the available map projections, the Transverse Mercator projection is best for Rhode Island, as the RI state plane system uses it.  Indiemapper’s suggested parameters for the projection’s central meridian is good, matching the RI state plane projection.
  6. Final touches: I made the graticule layer invisible, and added a north arrow, legend for RPL_THEMES, and annotations for the title, credits, and map notes.
Do it Yourself:

The Social Vulnerability Atlas is composed of four themes based on fifteen attributes, plus two ancillary attributes for health insurance and daytime population. Therefore, I’ve only shown one out of 22 possible maps here!

You can download all the data for this project in the form of shapefiles in a zip file here: www.josephholler.com/files/SVI_indiemapper_files.zip. Be sure to extract/copy the contents out of the zip file once it downloads. The zip file also includes the CDC’s documentation, or else download that here.

If you’re inclined to do even less of the work yourself, download my indeimapper map file for the project here: www.josephholler.com/files/CDCSVI.imp. Launch the indiemapper app, load my CDCSVI.imp map file with the “Browse for IMP” button on the start-up screen, and start customizing your own thematic maps!