The use of high-resolution remote sensing for plague surveillance in Kazakhstan

被引:40
|
作者
Addink, E. A. [1 ]
De Jong, S. M. [1 ]
Davis, S. A. [2 ,3 ]
Dubyanskiy, V. [4 ]
Burdelov, L. A. [4 ]
Leirs, H. [5 ,6 ]
机构
[1] Univ Utrecht, Dept Phys Geog, NL-3508 TC Utrecht, Netherlands
[2] Yale Univ, Sch Med Epidemiol & Publ Hlth, New Haven, CT 06520 USA
[3] Univ Utrecht, Dept Vet Med, NL-3508 TD Utrecht, Netherlands
[4] M Aikimbayevs Kazakh Sci Ctr Quarantine & Zoonot, Anti Plague Inst, Alma Ata 050074, Kazakhstan
[5] Univ Antwerp, Dept Biol, B-2020 Antwerp, Belgium
[6] Univ Aarhus, Dept Integrated Pest Management, Danish Pest Infestat Lab, DK-2800 Lyngby, Denmark
关键词
Bubonic plague; Object-based image analysis; Quickbird; LAND-COVER; CLASSIFICATION; MOUNDS; SCALE;
D O I
10.1016/j.rse.2009.11.015
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 of plague in gerbils started in 1947, reducing the number of human cases and mortalities drastically. However, the monitoring is labour-intensive and hence expensive and is now under threat due to financial constraints. 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 30 m 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 field campaigns in September 2007 and May and September 2008 and acquired corresponding QuickBird images of the first two periods. User's and producer's accuracy values of the classification reached 60 and 86%, respectively, providing proof of concept that automatic mapping of burrow systems using high-resolution 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. (C) 2009 Elsevier Inc. All rights reserved.
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页码:674 / 681
页数:8
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