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Applications of Satellite-Based Remote Sensing Data in Public Health Decision Making

Special Issue Information

Dear Colleagues,

Data from satellite remote sensing is currently integrated with geographic information system (GIS) for spatial modelling of disease transmission, contributing significantly to informed public health decision making for control of diseases and/or to stop further transmissions. Remote sensing data provides global coverage of climatological parameters, such as rainfall, temperature, soil moisture, etc. as well as the ocean environment which is useful for understanding incidences and spread of diseases, as well as predictive modelling. The aim of this call for papers is to provide an update on remote sensing data and technological advances in public health decision making; to invoke new ways of thinking about how public health programs can be better accomplished, and to stimulate new ideas on how the data from satellite remote sensing can be further utilized. This Special Issue, “Applications of Satellite Remote Sensing Data in Public Health Decision Making”, calls for papers that demonstrate original research that can advance our knowledge in examining the remote sensing data for public health decision making.

Dr. Mohammad Ali
Prof. Michael Emch
Dr. Jianyong Wu
Dr. Veronica Escamilla
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Geographic Information System
Remote sensing technology
Spatial epidemiology
Disease transmission
Predictive modelling
Risk assessment
Landscape metrics and water quality
Ocean environment

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Submission deadline 31 May 2019
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Editors

Mohammad Ali
Guest Editor
Johns Hopkins Bloomberg School of Public Health, 615 N wolfe Street/E5543, Baltimore, MD 21205, USA
Interests: My main interest is the evaluation of vaccine effectiveness and to provide expertise in leadership, training, and motivation necessary to carry out multidisciplinary research projects. My research background includes geographic and statistical analyses of clinical trials, utilization of remote sensing technology, health, health interventions, population, human ecology, and multilevel analysis. Teaching and conducting training on applications of GIS in public health decision making, health interventions, spatial analysis, spatial epidemiology, and human ecology are my passion. Further, I am interested in designing, developing, implementing, and managing computer-based (geographic) information systems.
Michael Emch
Guest Editor
Website
Department of Geography, University of North Carolina at Chapel Hill, CB 3220, Chapel Hill, NC 27599, USA
Interests: My interests are in infectious disease ecology, spatial epidemiology, neighborhood determinants of health, and geographic information science applications of public health. I lead the Spatial Health Research Group which conducts research that explores spatio-temporal patterns of disease, primarily infectious diseases of the developing world. Disease patterns are studied using a holistic approach by investigating the role of natural, social, and built environments in disease occurrence in different places and populations. Diverse statistical and spatial analytical methods are informed by theory from the fields of health geography, epidemiology, ecology, and others. These theories and methods are used to examine diverse topics such as the role of population–environment drivers in pathogen evolution, how social connectivity contributes to disease incidence, and using environmental indicators to predict disease outbreaks.
Jianyong Wu
Guest Editor
Website
Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC 27599, USA
Interests: data science; global environmental health; infectious diseases; spatial epidemiology
Veronica Escamilla
Guest Editor
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel-Hill, 123 W Franklin St, Building C, Suite 330, Chapel Hill, NC 27516, USA
Interests: My research interests focus on human–environment interactions and their influence on health outcomes and access to health services. I take a spatial epidemiological approach which includes GPS survey design and implementation, geographic information systems, and multilevel models to examine a range of outcomes including infectious and vector-borne disease transmission and the effectiveness of public health interventions. I also have experience utilizing satellite imagery to design sampling frames for population health surveys. I have worked on multiple interdisciplinary projects in several countries, including Bangladesh, Malawi, Nigeria, and the United States.

Remote Sens. - ISSN 2072-4292

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