Spatial Synthesis
Volume II, Book 1:
Scientific, Planning, Humanitarian, and Teaching Applications, From DevInfo to Google Earth


Maternal mortality by country:  darker shades of red indicate higher rates (per 100,000 live births).  The shaded circles are sized according to mortality of children under 5 years of age.  The larger the radius, the higher the rate.  The background of the circles is shaded transparent to let the underlying country color show through.  There appears to be a strong direct association between the two indicators:  countries with a high maternal mortality rate also have a high childhood mortality rate.

Maternal mortality by country:  darker shades of red indicate higher rates (per 100,000 live births).  The shaded circles are sized according to sustained access to fresh water.  The larger the radius, the higher the value.  The background of the circles is shaded transparent to let the underlying country color show through.  There appears to be a strong inverse association between the two indicators:  countries with a low maternal mortality rate have a high value for sustained access to water.

Perhaps these observed associations are not surprising.  It seems plausible to think that countries that have high mortality for one fragile group might well have high mortality for others.  On the other hand, it also seems plausible that good access to fresh water may help to reduce mortality and vice-versa.  Maps of this sort, are useful for demonstrating natural associations to a target population that might be otherwise unaware of them.  They are often of even greater value, however, when one looks for the areas that do NOT conform to the expected situation.  In this case, the coastal countries of west Africa and Burundi appear to have high maternal mortality ratios, high childhood mortality rates, and fairly high values of sustained access to fresh water.  Taking a closer look at public health policy and a variety of other variables, normalizing as appropriate, that focus on these areas might be suggested.  The map serves not only as a visual display of data but also as a guide to where further research and data collection might be targeted:  maps and decisions interact and affect each other.
One of the great improvements in the current GIS package from ESRI is the presence of ArcCatalog which allows projection of the data.  It is easy to do and the online help is fine support.  The associated mapping package, ArcMap 9.x, permits extensive analysis of data, in a fairly straightforward fashion.  Each of ArcView 3.x and ArcMap 9.x has its merits and drawbacks.  Some users may be forced, through budgetary constraints, to remain with ArcView 3.x; others with extensive script libraries may choose to remain with ArcView 3.x.  Most, however, will probably choose to obtain the latest software. 

The example below singles out the country of Burundi for a closer look using ArcMap 9.x.  The map incorporates a number of concepts:  distance from a city; how cities share space; access to streams.  The images below suggest one use of the ArcToolBox in ArcMap 9.x.  Lines of the Thiessen polygons follow the intersections of the circular buffers surrounding the towns--that observation is a universal fact and is not coincidental (see, for example, the linked article with animated figures).   While these maps have some uses, it is quite clear that simultaneous visualization of the complex hydrological network coupled with the buffered city map is difficult, at best.

However, when the city buffers and the hydrology are taken to Google Earth, and the transparency is set at various levels, it becomes easy to visualize, simultaneously, the buffers, the hydrology, and the features, such as roads, introduced in the checkboxes in Google Earth.  The rivers follow the terrain and the buffers are centered on the cities; one can see buildings by diving into the buffers once they have been made transparent.  The animations below illustrate screen captures of such activity in Google Earth.  The reader is, however, encouraged to download the associated .kml files using these links and open the files in Google Earth:  hydrology; buffers.

The world of GIS usage in spatial analysis is a complex one.  There are many online resources available for the reader wishing to pursue various topics.  The point here is simply to indicate that this richness is part of the sequence in moving from DevInfo to Google Earth and that it can be tapped in a variety of ways depending on available software and expertise.

This sort of display offers yet another way to visualize different layers; it adds the component of time.  Thus, the timeline feature offers a powerful way to link temporal elements of spatial databases with the globe.

One way to solve this problem is to make the dominant color semi-transparent--in this case, the blue layer is made 50% transparent.  Thus, red shows through the blue and gives a purple cast to regions of double color.  Elsewhere, the higher value color dominates.  Note the Moiré effects in Southern Africa suggesting coplanar polygons representing similar values.   Naturally, both colors could be made of varying degrees of opaqueness.  More indicators could be added, as well.  The sequence of images below shows the merits of this scheme.  It works best when contrasting bright colors are chosen; the larger the number of colors/layers, the more one has to pay attention to color mixing strategy.


Software used in analysis:
  • DevInfo 5.0:
  • Adobe® PhotoShop and ImageReady
  • Adobe® DreamWeaver
  • ESRI:
    • ArcView® 3.2
    • ArcGIS® 9.2
      • ArcCatalog®
      • ArcMap®
  • Google Earth®

Author affiliations:
  • Arlinghaus, Sandra Lach.  Adjunct Professor of Mathematical Geography and Population-Environment Dynamics, School of Natural Resources and Environment, The University of Michigan.  Executive Committee Member (Secretary) Community Systems Foundation,,
  • Naud, Matthew.  Environmental Coordinator and Assistant Emergency Manager, Systems Planning Unit, City of Ann Arbor
  • Oswalt, Kris S.  President, Community Systems Foundation
  • Rayle, Roger.  Scio Residents for Safe Water
  • Lars Schumann.  Manager and Research Computer Specialist, University of Michigan 3D Laboratory at the Duderstadt Center; also of Cornell University, Ithaca NY
  • Arlinghaus, William C.  Professor of Mathematics and Computer Science, Lawrence Technological University, Southfield, MI
  • Arlinghaus, William E.  General Manager, Chapel Hill Memorial Gardens, Grand Rapids, MI
  • Batty, Michael. Bartlett Professor of Planning and Director of the Centre for Advanced Spatial Analysis (CASA) at University College London
  • Haug, Robert.  Ph.D. Candidate, Middle Eastern and North African Studies, The University of Michigan
  • Larimore, Ann Evans.  Professor Emerita, Residential College, The University of Michigan
  • Longstreth, Karl.  Head, Map Library, The University of Michigan
  • Nystuen, Gwen L.  Parks Advisory Commission; Environmental Commission; City of Ann Arbor
  • Nystuen, John D.  Professor Emeritus of Geography and Urban Planning, Taubman College of Architecture and Urban Planning, The University of Michigan.  Chief Executive Officer, Community Systems Foundation

Published by:
Institute of Mathematical Geography
August, 2008.
Copyright by Sandra Arlinghaus, all rights reserved.