Predictive map of Ixodes ricinus high-incidence habitats and a tick-borne encephalitis risk assessment using satellite data (original) (raw)

Abstract

The main objective of this project was to predict Ixodes ricinus abundant habitats reliably as a means of tick-borne encephalitis (TBE) risk assessment for the prevention of this disease. The vegetation types were used as the indicators of an ecosystem suitable for tick occurrence, for TBE virus circulation and, accordingly, for the existence of natural foci of this infection. Remote sensing methods were used to determine the indicative plant cover. Satellite data covering an experimental area of 70 × 70 km in Central Bohemia, the Czech Republic, was acquired by the Landsat 5 TM scanner. Nine forest classes were recognized in the experimental area by successive supervised and unsupervised classifications and identified in a field-checking botanical survey. An epidemiological TBE map based on human cases contracted in the territory under study was exploited for the evaluation of risk in particular forest classes. Predictive maps are expressed both in digital and in printed forms at a scale of 1 : 300 000 for an overall risk evaluation and at a scale of 1 : 25 000 for a detailed local orientation.

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Authors and Affiliations

1. School of Public Health, Postgraduate Medical School, Prague, Czech Republic
   Milan Daniel
2. Laboratory of Remote Sensing, Czech Technical University, Prague, Czech Republic
   Jan Kolár & Karel Pavelka
3. Regional Centre of Hygiene, Prague, Czech Republic
   Petr Zeman
4. Institute of Botany, Academy of Sciences of the Czech Republic, Czech Republic
   Jirí Sádlo

Authors

1. Milan Daniel
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2. Jan Kolár
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3. Petr Zeman
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4. Karel Pavelka
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5. Jirí Sádlo
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Daniel, M., Kolár, J., Zeman, P. et al. Predictive map of Ixodes ricinus high-incidence habitats and a tick-borne encephalitis risk assessment using satellite data.Exp Appl Acarol 22, 417–433 (1998). https://doi.org/10.1023/A:1006030827216

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• Issue Date: July 1998
• DOI: https://doi.org/10.1023/A:1006030827216