Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling
Submitted: 17 July 2015
Accepted: 23 October 2015
Published: 30 November 2015
Accepted: 23 October 2015
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Department of Remote Sensing, Institute for Geography and Geology, University of
Würzburg, Würzburg; Institute for Environment and Human Security, United Nations University, Bonn, Germany.
Department of Remote Sensing, Institute for Geography and Geology, University of
Würzburg, Würzburg, Germany.
Department of Remote Sensing, Institute for Geography and Geology, University of
Würzburg, Würzburg, Germany.
Department of Remote Sensing, Institute for Geography and Geology, University of
Würzburg, Würzburg; German Remote Sensing Data Centre, German Aerospace Centre, Oberpfaffenhofen, Germany.
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel; University of Basel, Basel, Switzerland.
Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan; Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Abidjan, Côte d'Ivoire.
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel; University of Basel, Basel, Switzerland.
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel; University of Basel, Basel, Switzerland.
Supporting Agencies
German Aerospace Center for providing RapidEye data from the RapidEye science archiveHow to Cite
Walz, Y., Wegmann, M., Leutner, B., Dech, S., Vounatsou, P., N’Goran, E. K., Raso, G., & Utzinger, J. (2015). Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling. Geospatial Health, 10(2). https://doi.org/10.4081/gh.2015.398
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