Using very high spatial resolution remote sensing to monitor and combat outbreaks of bubonic plague in (original) (raw)

Bubonic plague, caused by the bacteria Yersinia pestis, persists as a public health problem in many parts of the world, including central Kazakhstan. Bubonic plague occurs most often in humans through a flea bite, when a questing flea fails to find a rodent host. For many of the plague foci in Kazakhstan the great gerbil is the major host of plague, a social rodent well-adapted to desert environments. Intensive monitoring and prevention started in 1947, reducing the number of cases and mortalities enormously. However, the monitoring is labourintensive and hence expensive and is now under threat due to financial restraints. Previous research showed that the occupancy rate of the burrow-systems of the great gerbil is a strong indicator for the probability of a plague outbreak. The burrow-systems are around 30m in diameter with a bare surface. This paper aims to demonstrate the automatic classification of burrow-systems in satellite images using object-oriented analysis. We performed a field campaign in September 2007 and acquired a QuickBird image in the same period. Overall accuracy of the classification reached 95%, providing proof of concept that automatic mapping of burrow-systems using highresolution satellite images is possible. Such maps, by better defining great gerbil foci, locating new or expanding foci and measuring the density of great gerbil burrow-systems could play a major role in a renewed monitoring system by better directing surveillance and control efforts. Furthermore, if similar analyses can separate occupied burrow-systems from empty ones, then very-high-resolution images stand to play a crucial role in plague surveillance throughout central Asia.

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