Introduction

The Use of Remote Sensing in Public HealthMarguerite Walsh – 109468692 – 11th March 2015

• There still are many hurdles to overcome when using RS, including “cost, inadequate spatial, spectral, or temporal resolution, availability of adequate data and long turnaround times for products” and these may have restricted the use of RS in public health applications up until now (Lleo et al,

2008). Many believe “it has not proved to be the wonder tool that scientists expected” (Lleo et al, 2008).

• With great environmental change expected in the near future many more dangers will encroach upon Ireland, but with an increase in knowledge and awareness of remote sensing as well as new satellites and sensors, these can be predicted and mitigated against.

• Environment Canada, 2013. HomeColourful Research - Remote Sensing for Algal Blooms. Available online at: https://www.ec.gc.ca/eau-water/default.asp?lang=En&n=2E9EDFA9-1 Last accessed 03 March 2015.

• Gilbert,M., Xiangming,X., Chaitaweesub,P., Kalpravidh,W., Premashthira,S., Boles,S., & Slingenbergh,J., 2007. Avian influenza, domestic ducks and rice agriculture in Thailand. Agriculture, Ecosystems and Environment, Vol.119, P.409–415.

• Hartfield,K.A., Landau,K.I., & van Leeuwen,W.J.D., 2011. Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat, Remote Sensing, Vol.3, P.2364-2383.

• Haynes,J.A., n.d. NASA Public Health Applications of Remote Sensing Data. Available online at:

https://www.earthobservations.org/documents/cop/he_henv/20100727_France/17_

NASA_HAYNES.pdf Last accessed 03 March 2015.

• Johnson,D., Lulla,V., Stanforth,A., & Webber,J., 2011. Remote Sensing of Heat-Related Health Risks: The Trend Toward Coupling Socioeconomic and Remotely Sensed Data, Geography Compass, Vol.5, Issue.10, P.767–780.

• Kelly,M., Blanchard,S.D., Kersten,E., & Koy,K., 2011. Terrestrial Remotely Sensed Imagery in Support of Public Health: New Avenues of Research Using Object-Based Image Analysis, Remote Sensing, Vol.3, P.2321-2345.

• Lleo,M.M., Lafaye,M., & Guell,A., 2008. Application of space technologies to the surveillance and modelling of waterborne diseases. Current Opinion in Biotechnology, Vol.19, P.307–312.

• Maxwell,S.K., 2011. Downscaling Pesticide Use Data to the Crop Field Level in California Using Landsat Satellite Imagery: Paraquat Case Study, Remote Sensing, Vol.3, P.1805-1816.

• Neteler,M., Hamish Bowman,M.H., Landa,M., & Markus Metz,M., 2012. GRASS GIS: A multi-purpose open source GIS, Environmental Modelling & Software, Vol.31, P.124-130.

• Palaniyandi Masimalai,P., 2014. Remote Sensing and Geographic Information Systems (GIS) as the Applied Public Health & Environmental Epidemiology, International Journal of Medical Science and Public Health, Vol.3, Issue.12, P.1430-1438.

• Patz,J.A., Campbell-Lendrum,D., Holloway,T., & Foley,J.A., 2005. Impact of regional climate change on human health. Nature, Vol.438, P.310-317.

• Stumpf,R.P., &Tomlinson,M.C., 2005. Remote Sensing of Harmful Algal Blooms, Remote Sensing of Coastal Aquatic Environments, P.277–296.

• Tran,A., Goutard,F., Chamaille,L., Baghdadi,N., and Seen,D., 2010. Remote sensing and avian influenza: A review of image processing methods for extracting key variables affecting avian influenza virus survival in water from Earth Observation satellites, International Journal of Applied Earth Observation and Geoinformation, Vol.12, P.1–8.

• Often remote sensing (RS) and geographical information systems (GIS) are grouped together under the term “GIS”. However RS on its own deserves recognition for disease surveillance, spatial modelling and monitoring (Palaniyandi Masimalai,P., 2014) .

• Ms. Heather Hegarty from the Health Service Executive has already demonstrated a couple of uses of GIS including mapping diseases such as tuberculosis (TB) and the use of mapping in emergency preparedness.

• We shall now look at some of the uses of remote sensing in public health.• Some, of these uses are shown in Figure 1 below. Many, but not all, are then discussed in further detail in this poster.

Conclusion

RS & Vector or Water-borne Diseases

• In 2011 a study by Hartfield et al, used LiDAR (Light Detection and Ranging), multispectral imagery and NDVI (Normalized Difference Vegetation Index) to improve land cover classification for the city of Tuscan, Arizona, USA.

• This was then used to map mosquito habitats. In this urban area the use of NDVI helped greatly to separate the vegetated areas from the non vegetated areas, while LiDAR provided information on elevation and height to produce a 3D model of the city.

• Including additional information on temperature and precipitation produced a “spatially explicit and highly accurate prediction of mosquito population”.

• This study also helped to map seasonal changes to mosquito life cycles.

Fig 1 shows many of the areas of public health monitoring and prediction where remote sensing and earth observation can be used. Many of these areas are interrelated, such as waterborne diseases and vector-borne diseases. (Image: Author’s own, compiled from all the sources listed in the references section)

Fig 3 shows one of the resulting maps from Hartfield’s study. The red areas represent the areas of vegetation – namely gardens, parks and golf courses. The level of detail is clearly quite high.

• One of the main uses of RS in Public Health is the creation of land use or land cover maps. This is a common technique used to monitor Malaria and other vector and water -borne diseases which are often related to environmental conditions.

• A number of projects and organisations have focused on mapping Malaria in Africa where it is most common. Examples of these projects and organisations include: Mapping Malaria Risk in Africa (MARA), Malaria Modelling and Surveillance (MMS) and Epidemiological Applications of Spatial Technologies

• However with shifts in climate due to climate change, the conditions where mosquitoes can survive will be expanding and this expansion will need to be monitored in different environments and habitats.

References

RS & Toxin Exposure• In both developed and developing countries toxins are a constant threat to the public’s health.

• Pesticides, poisons and Harmful Algae Blooms( HAB) all cause toxicity which can be damaging to the publics health.

Fig 2 Lake Erie, Northern America, where algae blooms are a common problem. This is a true colour composite image where the algae blooms can clearly be seen as they appear green compared to the surrounding blue water (Environment Canada, 2013).

• HABs can be monitored by looking at different types of data - Sea Surface Temperature (SST), suspended particulate material, ocean sea colour, all of which can be got from satellites (Stumpf, &Tomlinson, 2005, Lleo et al, 2008)

• According to the CORINE dataset, 64% of Ireland’s landcover is used for agriculture

• This means that much of Ireland is susceptible to pesticide exposure, which “has been associated with increased risk of many adverse health effects” (Maxwell, 2011).

• A study by S.K.Maxwell in 2011, into pesticide levels in California, used Landsat imagery and a spectral signature library of all the crops to identify areas where large amounts of pesticides had been applied.

• In Ireland aerial photography would be more suitable as our fields are smaller in size, and a higher spatial resolution would be better.

RS & Influenza• Despite Ireland being an island: swine flu, avian flu and severe acute respiratory syndrome (SARS) influenza have all reached us at one stage or another.

• While trade can be blamed for some of these viruses reaching us, environmental factors also play a huge role.

• Similar to mapping locations of mosquitoes proximity to wetland areas and seasonal influences are two of the most important factors.

• Both optical and radar remote sensing may be used to detect and characterize water bodies (Tran et al, 2010).

• Tran et al, 2010, used RS to identify water bodies and also areas of flood water, and also look at variables such as pH, temperature and salinity. All “key variables influencing the AI virus survival in water” (Tran et al, 2010).

• Another study be Gilbert et al in 2007 used RS to identify areas of rice in Thailand and the number of crops per year. These areas form the habitat of grazing ducks and so are likely areas for avian flu to originate.

Fig 4 shows the number of rice crops per year (Gilbert et al, 2007)