Mapping App Enables Global Dialog around Aid Projects

AidData and Esri Submit Prototype to World Bank’s “Apps for Development” Competition

Public voting closes today, February 28, 2011, for World Bank’s “Apps for Development” competition, which includes an innovative mapping tool created by AidData with support from Esri. AidData’s Development Loop application presents a visual story of assistance, need, and impact driving the complex flow of development funds around the globe. To vote or access a demo and prototype of Development Loop, visit the Apps for Development website.

AidData—a joint initiative of Brigham Young University, the College of William and Mary, and nonprofit organization Development Gateway—captures and interprets development data to support aid activities. Development Loop integrates project data from the World Bank and African Development Bank with success stories, development indicators, and relevant local information on an interactive map. Future enhancements, such as social media integration and free mobile offerings, will facilitate place-based feedback loops among donors, development professionals, and aid recipients.

Through the app challenge, AidData hopes to encourage donor organizations to collaborate in building a comprehensive picture of development efforts and a dynamic platform on which to plan, analyze, and evaluate projects.

“Development Loop goes far beyond depicting where and how funds are being spent,” says Stephen Davenport, senior director for business development at Development Gateway. “It can open the lines of communication and track funding as it moves from one organization to another to the intended beneficiary. It makes projects more empowering and efficient and establishes a platform for sustainable workflows that can be incorporated into existing reporting processes.”

The Development Loop prototype is built on Esri’s ArcGIS API for Microsoft Silverlight/WPF and ArcGIS Server technology. World Bank and African Development Bank activity data was geocoded through the Mapping for Results project, a partnership between AidData and the World Bank.

Organizations interested in integrating project information into Development Loop may contact AidData at info@aiddata.org or Salim Sawaya of Esri at ssawaya@esri.com. To learn more about Esri, visit esri.com. For information on AidData, visit aiddata.org.

[Source: Esri press release]

A Brief History of Spatial Analysis

March 3, 2011, Department of Statistics, University of Illinois

Anil Bera

“Spatial econometrics which is essentially concerned with statistical techniques to take account of economic interactions among agents located on space is relatively a new field of research. However, spatial analysis in general, has a long history. In the statistics literature, R.A. Fisher was probably the first to recognize the implications of spatial dependence. While discussing the shapes of blocks and plots in agricultural experiments, he commented, After choosing the area we usually have no guidance beyond the widely verified fact that patches in close proximity are commonly more alike, as judged by the yield of crops, than those which are further apart, see Fisher (1937, pp.73-74). Even after so many years, the basic tenet of spatial dependence has not changed much from Fishers characterization. In the current statistics and econometrics literature, spatial dependence is also loosely defined as the coincidence of value similarity with location similarity. Every beginning, however, has its own beginning. I will start at the very beginning, and discuss the disconnected developments in spatial analysis during the last century. Then I will move to spatial econometrics, and mention some key developments. Finally, I will try to cover some of my joint work with students/colleagues on specification tests for spatial models.”

Using MODIS Satellite Imagery to Predict Hantavirus Risk

Global Ecology and Biogeography, Article first published online: 17 FEB 2011

Lina Cao, Thomas J. Cova, Philip E. Dennison, and Denise Dearing

“Aims: Sin Nombre virus (SNV), a strain of hantavirus, causes hantavirus pulmonary syndrome (HPS) in humans, a deadly disease with high mortality rate (> 50%). The primary virus host is the deer mouse, and greater abundance of deer mice has been shown to increase the human risk of HPS. Our aim is to identify and compare vegetation indices and associated time lags for predicting hantavirus risk using remotely sensed imagery.

“Location: Utah, USA.

“Methods: A 5-year time-series of moderate-resolution imaging spectroradiometer (MODIS) satellite imagery and corresponding field data was utilized to compare various vegetation indices that measure productivity with the goal of indirectly estimating mouse abundance and SNV prevalence. Relationships between the vegetation indices and deer mouse density, SNV prevalence and the number of infected deer mice at various time lags were examined to assess which indices and associated time lags might be valuable in predicting SNV outbreaks.

“Results: The results reveal varying levels of positive correlation between the vegetation indices and deer mouse density as well as the number of infected deer mice. Among the vegetation indices, the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) produced the highest correlations with deer mouse density and the number of infected deer mice using a time lag of 1.0 to 1.3 years for May and June imagery.

“Main conclusions: This study demonstrates the potential for using MODIS time-series satellite imagery in estimating deer mouse abundance and predicting hantavirus risk. The 1-year time lag provides a great opportunity to apply satellite imagery to predict upcoming SNV outbreaks, allowing preventive strategies to be adopted. Analysis of different predictive indices and lags could also be valuable in identifying the time windows for data collection for practical uses in monitoring rodent abundance and subsequent disease risk to humans.”

Representing Places and Change: From the Dynastic to the Diurnal

GIScience Colloquium, University of Zurich-Irchel, May 3, 2011

Paul Longley

“This presentation will take stock of ongoing work at University College London that seeks to profile the dynamics of local area change at temporal scales ranging from the dynastic to the diurnal. We begin with the genetic structure of Great Britain, and evidence that the historic origins of family names remain important in understanding spatial structure. Our regional classification suggests that population mix is today an amalgam of contagious and hierarchical diffusion – with the former incremental over time, and the latter precipitated by episodic events. Next, we reflect on 80 years’ research into the kaleidoscope of change in urban areas, which has culminated in use of geodemographic indicators of social similarity and built form to link disparate geographic locations. Such indicators have more recently been used to characterise the consumption of public as well as private goods, although this begs interesting questions about the geographic scale at which they might best be deployed to characterise neighbourhood expectations and community attitudes. We then consider the impacts of recent technologies that at the same time facilitate change in the way that individuals interact with their (virtual) communities while providing new ways of measuring, monitoring and hence generalising about such interactions. In conclusion we draw these different strands together in order to propose geodemographics that accommodate the unique virtual and conventional demographic characteristics that characterise different locations. We argue that the change dynamics of such indicators say much about social mobility and social interaction in Britain, and internationally.”