The American Journal of Tropical Medicine and Hygiene, 81(6), 2009, pp. 944-949
Ingrid Peterson, Luisa N. Borrell, Wafaa El-Sadr, and Awash Teklehaimanot
“ Urban malaria is a growing problem in Africa. Small-scale spatialstudies are useful in identifying foci of malaria transmissionin urban communities. A population-based cohort study comprising8,088 individuals was conducted in Adama, Ethiopia. During asingle malaria season, the Kulldorff scan statistic identifiedone temporally stable spatial malaria cluster within 350 m ofa major Anopheles breeding site. Factors associated with malariaincidence were residential proximity to vector breeding site,poor house condition (incidence rate ratio [IRR] = 2.0, 95%confidence interval [CI] = 1.4, 2.9), and a high level of vegetation(IRR = 1.8, 95% CI = 1.0, 3.3). Maximum (IRR = 1.4, 95% CI =1.1, 1.9) and minimum daily temperatures (°C; IRR = 1.3,95% CI = 1.2, 1.5) were positively associated with malaria incidenceafter a 1-month delay. Rainfall was positively associated withmalaria incidence after a 10-day delay. Findings support theuse of small scale mapping and targeted vector control in urbanmalaria control programs in Africa.”
In this short video from August 2007, GIS pioneer Roger Tomlinson visits DMTI Spatial in Canada. He discusses principles of GIS and how they have changed the world. DMTI Spatial CTO John Fisher discusses the pervasiveness of GIS in today’s business world.
Last April, when the spread of H1N1 (swine) flu began, students in Texas watched with a vested interest. The Texas Education Agency made recommendations to reschedule or cancel area and state-level competitions in an effort to limit student travel and minimize contact. With events approaching, like prom, spring concerts, and even graduation ceremonies, students waited as local school districts made careful decisions. Some districts halted student travel and others canceled school classes for a period of weeks.
Lubbock Independent School District GIS teacher Penny Carpenter knew GIS tools would be used to monitor and inform the public of the flu’s pandemic potential, and she saw a unique opportunity for her students. Philosophically, Carpenter motivates students with relevant real-world topics, and the reality of H1N1 flu had certainly captured her students’ attention. They found maps of countries and states with confirmed flu cases but none of Texas counties. Because the outbreak originated in Mexico, students looked to the border towns for reported infections, and that is when geographic inquiry began: Where were the counties in Texas with confirmed H1N1 flu cases?
International Journal of Geographical Information Science, Volume 23, Issue 11 November 2009 , pages 1389 – 1412
Giorgos Mountrakis; Kari Gunson.
“Moose-vehicle collisions (MVCs) pose a serious safety and environmental concern in many regions of Europe and North America. For example, in the state of Vermont, one-third of all reported MVCs resulted in motorist injury or fatality while collisions have increased from two in 1982 to 164 in 2002. Our work used a MVC dataset from 1983 to 1999 in the Northeastern Highlands of Vermont (four major roads) to perform space, time and spatiotemporal analyses and guide future mitigation strategies. An adapted kernel density estimator was implemented for exploratory analyses to detect high density collision hotspots on roads. The kernel in space showed seven major density peaks which varied in magnitude and spread between roads. The kernel estimator in time for all roads showed an exponentially increasing trend with annual periodicity and a seasonal cyclic component, where the majority of collisions occurred from May to October. Spatiotemporal kernel estimation exhibited discontinuous density hotspots in time and space suggesting changing animal movement patterns across roads. We used an adapted Ripley’s K-function to test the hypothesis that MVCs clustering occurred at multiple scales in space, in time and in space-time combined. Statistically significant spatial clustering was evident on all roads at spatial scales from 2 to 10 km. A more consistent clustering in time occurred on all roads at a scale distance of 5 years. Similar to the kernel estimation, annual periodicity was also evident. Positive space-time clustering was present at small spatial (5 km) and temporal scales (2 years) indicating that where MVCs occur is also influenced by when they occur. In retrospect, using multiple road lengths, and the combined kernel estimation and Ripley’s K-function in time and space, provided a powerful methodology to study varying spatiotemporal patterns of wildlife collisions along roads. This can greatly assist transportation planners in identifying optimal mitigation strategies along specific roads, such as deciding on location and spatial length for permanent and expensive measures (e.g. crossing structures and associated fencing) versus less permanent and inexpensive structures (e.g. wildlife signage and reduced speed limits).”
Hydrocarbon exploration is an expensive, high-risk operation that involves searching for hydrocarbon deposits (like oil and gas) beneath the earth’s surface. Though visible surface features can provide evidence of hydrocarbon generation, most exploration methods depend on highly sophisticated technology to detect and determine the presence of these deposits deep within the earth.
In early 2000, there was a significant natural gas discovery in southern New York that led to a boom in hydrocarbon exploration. Shortly after this discovery, MIR Télédétection Inc.—a natural resources consulting firm located in Québec, Canada,—began providing expertise to help target hydrocarbon reservoirs.
Among the many services MIR provides are customized earth sciences applications that support hydrocarbon exploration in North America through the capture, integration, and analysis of geologic, remotely sensed, and geoscientific data. Its research plays an integral role in successfully turning leads (structures that may contain or trap hydrocarbons) into prospects (leads that have been fully evaluated and are ready to drill).