Use of earth observation data for applications in public health |
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| Authors: | Qihao Weng Bing Xu Xuefei Hu Hua Liu |
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| Institution: | 1. Department of Earth &2. Environmental Systems, Center for Urban and Environmental Change, Indiana State University, Terre Haute, IN, USAqweng@indstate.edu;4. School of Environment, Tsinghua University, Beijing, China;5. State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China;6. Department of Geography, University of Utah, Salt Lake, UT, USA;7. Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA;8. Department of Political Science and Geography, Old Dominion University, Norfolk, VA, USA |
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| Abstract: | The Earth Observation (EO) data with their advantages in spectral, spatial and temporal resolutions have demonstrated their great value in providing information about many of the components that comprise environmental systems and ecosystems for decades that are crucial to the understating of public health issues. This literature review shows that in conjunction with in situ data collection, EO data have been used to observe, monitor, measure and model many environmental variables that are associated with disease vectors. Furthermore, satellite derived aerosol optical depth has been increasingly employed to estimate ground-level PM2.5 concentrations, which have been found to associate with various health outcomes such as cardiovascular and respiratory diseases. It is suggested that Landsat-like imagery data may provide important data sources to analyse and understand contagious and infectious diseases at the local and regional scales, which are tied to urbanisation and associated impacts on the environment. There is also a great need of data products from coarse resolution imagery, such as those from moderate resolution imaging spectrometer, multiangle imaging spectroradiometer and geostationary operational environmental satellite , to model and characterise infectious diseases at the continental and global scales. The infectious diseases at greater geographical scales have become unprecedentedly significant as global climate change and the process of globalisation intensify. The relationship between infectious diseases and environmental characteristic have been explored by using statistical, geostatistical and physical models, with recent emphasis on the use of machine-learning techniques such as artificial neural networks. Lastly, we suggest that the planned HyspIRI mission is crucial for observing, measuring and modelling environmental variables impacting various diseases as it will improve both spectral resolution and revisit time, thus contributing to better prediction of occurrence of infectious diseases, target intervention and tracking of epidemic events. |
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| Keywords: | earth observation satellite remote sensing spatial resolution spectral resolution temporal resolution infectious diseases aerosol optical depth PM2 5 climate change globalisation urban environmental characteristics HyspIRI |
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