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TECHNICAL REFERENCE DOCUMENT

UNDERSTANDING THE EFFECT OF ENVIRONMENTAL FACTORS ON 

HUMAN HEALTH AND WELL-BEING

1. Introduction

What if we could reduce the incidence, or eliminate the most virulent cases, of deadly diseases like 

malaria, cholera, and West Nile encephalitis? Malaria and cholera killed more than 2.7 million 

people last year, primarily in the developing world; West Nile virus has now been detected in all 

but one of the lower 48 states. 

Since mosquitoes are the principal vectors for both malaria and West Nile virus, environmental 

factors often set the stage for optimal conditions for their spread and are important in determining 

their transmission, intensity and duration. By using in situ and remotely sensed data to monitor 

weather patterns, such as temperature and rainfall, and their effects on soil moisture and humidity, 

warnings may someday be available for high-risk areas up to a month in advance. Health officials 

could use these “red flag” warnings to plan their prevention efforts, perhaps averting a potentially 

deadly outbreak. 

 

The effective combination of in situ and remotely sensed data, indicators, and models could also 

be used in computer simulations to estimate the risk of cholera. Ocean temperature and circulation 

affect the proliferation and movement of phytoplankton blooms that harbor cholera bacteria. 

Satellite data can identify large-scale spatial and temporal bloom development while in situ buoys 

and stream gauges can provide local verification.

What if? This quest has proven valuable in the past. People born at the beginning of the 21st 

century, on average, can expect to live significantly longer and healthier lives than those born just 

over a century ago. Much of that increase was gained by environmental changes including 

improved sanitation, purified water, more effective control of disease vectors and reservoirs, 

cleaner air, and safer use of chemicals in homes, gardens, factories, and offices. 

Continued improvements in quality of life and longevity will require a better understanding of the 

causes, development and progression of common diseases and disorders—and how they relate to 

environmental factors. For example, what are the environmental factors behind the burgeoning 

increases in vector-borne diseases (e.g., malaria, West Nile virus) and chronic diseases with 

possible links to environmental exposures (e.g., breast cancer, Parkinson’s disease and asthma)? 

What are humans being exposed to? How can we improve prediction of outbreaks of acute 

diseases such as malaria and cholera?
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Most health problems in an individual arise from the interplay of a complex array of factors 

including genetic susceptibilities, stress, nutrition, age, stage of development, and environmental 

exposures. With the sequencing of the human genome, rapid progress in understanding human 

genetic susceptibilities is expected. One of the most difficult of these factors to monitor and 

assess are environmental exposures.

There are a variety of concerns or societal imperatives, which take a different form from the 

obvious or traditional concerns. These societal imperatives include a growing world population, 

projected to roughly double in the next few decades that will increasingly demand access to 

crucial resources like clean water and plentiful food. The concentration of populations is shifting 

from rural areas to urban centers, many in low-lying coastal regions or seismically active zones. 

In the U.S., more than half of the population lives within 50 miles of our coasts, and these areas 

are particularly vulnerable to storm surges and flooding. We rely upon coastal regions for healthy 

fisheries, and reliable transport and navigation. Increased dependence on infrastructure networks 

(roads, power grids, oil and gas pipelines) increases our potential vulnerability to natural disasters, 

and requires improved understanding of the complex workings of Earth systems in order to protect 

society and manage our resources in a more efficient and effective way. 

A well-designed, coordinated integrated United States Earth Observation System (IEOS) would 

contribute significantly to providing data and products on many environmental factors that 

influence stress (extreme weather events, noise), nutrition (price and availability of food), and 

most importantly exposures (air and water pollution, pathogens) that directly affect human health 

and well-being. The potential benefits would be enormous (see Table 1).

• Improved visibility and reduced haze for tourism

• Improved understanding of global transport of 

pollutants for policy making

• Warnings for sensitive populations to change 

activity patterns

• Early warnings for harmful exposures

• Early warnings for increases in disease vectors

• Improved mitigation/ prevention programs.

• Reduced releases of air and water pollutants

• Reduced use of pesticides and chemicals

• Reduced lung-related and water-born diseases 

& premature death

• Reduced hospital admissions & use of 

medicines

• Reduced absences from work and school; 

lower sick pay costs

• Improved resiliency of crops; increased yields

• Prevention of environmentally related diseases 

• Reduced exposure to toxic substances in air 

and water

Table 1. Potential Benefits of Increased Data on Environmental Factors Affecting Human 

Health and Well-Being

2. User Requirements

Over the past fifty years, the public has expressed a significant interest in understanding the 

relationships between health and environmental parameters. This has fostered an increasing 

demand that the best science be available to inform their own decisions and those of service 
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providers and policy-makers. In addition, high priority requirements have been articulated by 

national and international groups including the National Academy of Sciences, Institute of 

Medicine, Intergovernmental Panel on Climate Change, U.S. National Assessment, Arctic 

Monitoring and Assessment Program, UN Environmental Program, World Health Organization, 

the World Meteorological Organization, and others. 

The optimal approach is to combine ground or in situ and remote observation data, information, 

indicators, models, research, and other decision support systems to focus on an issue. These 

materials can be distributed widely using communications information systems and web portals, 

and effectively provide the information and tools for the public and decision-makers to make 

decisions about their daily lives that can influence health and well-being.

Data and data products relevant to human health and well-being include, but are not limited to the 

following areas:

• Air quality and pollution transport

• Water quantity and quality, especially for human use 

• Hot spots of pollution in wetland and coastal areas

• Fate of pathogens in marine and other low oxygen environments, such as, aquifers, 

mountain tops and caves

• Fate and transport of chemicals in the terrestrial, aquatic, and marine environments

• Impact of environmental changes and agriculture on biodiversity

• Special regions valued for recreational, religious, or aesthetic purposes

• Search for natural substances with medicinal/commercial value

• Environmental conditions that influence disease transmission from animals to humans

• Environmental conditions that affect the spread and control of emerging or reemerging diseases

• Disease vector and reservoir habitats and variations in range

• Safe and adequate supply of food

• Urban environment and growth

• Noise/odor levels

• Radioactivity

• Transportation patterns and travel statistics

• Sensitive resource and environmental data for transportation planning

• Land use, urban form, population data, including GIS, for transportation planning

• Human activities and location for exposure assessment and resource management

• Weather and climate

• Invasive species, particularly those affecting humans
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3. Existing Capabilities and Commonalities

Vision

An information system of environmental and health factors that are important to human health and 

well-being would integrate satellite measurements with ground-based measurements, human 

activity data, and models to describe and track pollution sources, concentrations, and human 

activities that influence exposure and impact human health. Other components of the global Earth 

observation system of systems will develop data to reduce disasters, protect and wisely use natural 

resources, understand and predict climate variation, support sustainable agriculture, forecast 

weather, and sustain areas valued for recreational, religious or aesthetic purposes. Since these 

components will also provide data for improving human health and well-being, there will be many 

observational systems to build upon. Such a system will augment existing and planned activities 

by collecting additional data and using data analysis tools (models, bioinformatics and state-ofthe-art information technology) to integrate the data into meaningful sets of public health 

indicators both for short-term predictions, future forecasts, or retrospective evaluation. 

Such a system will draw upon indicators of health and disease as well as some environmental 

public health indicators that exist today, but there are gaps and thus challenges ahead to develop a 

more comprehensive set of indicators. Observations will be selected to address these gaps 

including the tracking of pollutant sources, pollutant and pathogen concentrations and transport, 

and human locations and activities. Data analysis tools will be used to integrate the data and 

provide indicators of possible adverse health impacts on specified populations. Pilot projects will 

use an integrated suite of existing and new indicators to identify short and long-term changes in 

stressors-of-concern and changes in the human, land cover, environmental and social factors that 

effect human health and well-being. The value of IEOS will be judged on how well it succeeds in 

improving human health and well-being, and the proposed system is a critical component of the 

system of systems.

The following are general recommendations for establishing and operating a health information 

system:

• Establish a forum for identifying appropriate sets of indicators that can be used to 

evaluate and improve human health and well-being. 

• Determine the data, data analysis tools, and data dissemination requirements for these 

indicators to be used as part of health IS.

• Integrate with other components of the global Earth observations system of systems. 

(i.e., the urban land cover project that characterizes the built environment) to generate 

the needed information

• Determine the cost, feasibility, and technical requirements for establishing each of the 

proposed indicators,

• Identify critical methods and development needs for partial or full implementation of a 

health information system (i.e., real time sensors that provide higher spatial and 

temporal resolutions, flexible indicators, models and information systems, 

bioinformatic tools, GIS)
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• Establish mechanisms for transferring these or other new technologies into a health 

information system as they become available.

• Develop the partnerships and infrastructure for developing, operating, and enhancing a 

health information system.

• Pilot test a suite of the most feasible indicators.

• Initiate methods/develop activities in sensor/measurement technology, data analysis 

tools, and information archival/dissemination.

• Develop systems that provide both real-time availability along with archived data for 

trends and long-term effects.

• Develop a core users group that will have access to and demonstrate the utility of the 

information.

• Build an across the board system for training and education at the intersection of 

environment and health observations, data collection and analysis.

• Develop and monitor well defined measures that will demonstrate success.

• Provide data and data products at a reasonable cost

Background 

All the components of this integrated Earth observation system contribute to improving human 

health and well-being. Researchers, service providers, policy makers, and the public use Earth 

observations to make decisions and take actions. These decisions and actions help reduce the 

impact of disasters, protect and manage natural resources, adapt to and mitigate climate variation, 

support sustainable agriculture, forecast weather, protect areas valued for recreational, religious, or 

aesthetic purposes, and prevent disease/dysfunction due to environmental exposures or conditions 

that increase the likelihood of transmission of water- or vector-borne diseases.

The ability to predict the appearance and intensity of diseases has long been a goal of public health 

workers, economic planners and ordinary citizens. For those diseases that are influenced by 

environmental factors, the development of predictive models will open the door to the possibility 

that if one could link risk of disease with certain variables, one could eventually apply these 

models to predict occurrence and possibly control or prevent these diseases in human populations.

Enhanced Earth observations that lead to better air quality data and the ability to predict air 

pollution episodes would contribute to improvements in human health via: reduced incidence, 

acute attacks and deaths from chronic respiratory diseases such as asthma; fewer air pollutionrelated emergency room visits; and fewer days absent from school or work. Air pollution affects 

the environment in many ways that ultimately impact on our health and well-being: by reducing 

visibility, damaging crops, forests, and buildings; acidifying lakes and streams; stimulating the 

growth of algae in estuaries; and the build-up, or bioaccumulation of toxics (e.g., mercury) in fish 

and animals. Rapid development and urbanization around the globe has created air pollution that 

threatens people everywhere, as air pollution can travel great distances across oceans and national 

boundaries.

Characteristics of Existing Earth Observation Capabilities
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The IEOS anticipates a thoughtful mix of system elements to address the goals of societal benefits. 

This is true of the area of human health and well-being. To make progress on complex questions 

requires a variety of data from populations, the Earth, atmosphere, weather and other areas, 

combined with monitoring, modeling, and decision support research and systems. As such this 

issue become “cross cutting” with all the other issues contemplated by IEOS.

The IEOS contemplates using a variety of measures and monitoring along with models, indicators, 

and decision support systems to address the requirements of users. A fairly extensive suite of 

measures have been developed and applied over the years, some specific to these issues and others 

adapted from other applications to focus on human health and well-being. 

The use of these systems for human health studies has focused primarily on studies of land surface 

variables and their application to epidemiological studies. Earth remote sensing systems has been 

used since the launch of Landsat in 1972, and a combination of remote sensing and surface 

measures has provided useful data and information for other important health issues such as 

extreme weather, air pollution, UV radiation, ocean/coastal issues, and contaminant transport. 

Socioeconomic data, including data on both human activities and health, are essential to 

understanding fully the impact of environmental factors on human health and well-being. It is the 

linkage or combination of those data with environmental measurements that allows for research in 

these areas to proceed and for preventive and remedial strategies to be developed and 

implemented. Although the scope of this program is limited to data and data products that come 

from observing the Earth, the agencies responsible for its implementation should collaborate with 

the organizations that collect and process socioeconomic data to provide user-friendly links to 

relevant data and data products. Of special note is the major Centers for Disease Control and 

Prevention (CDC) effort to improve environmental public health tracking which will provide 

critical health data to tie into the various environmental monitoring systems.

A description of the application of existing remote sensing systems to many of these major health 

issues follows.

Epidemiology

The use of a combination of data sources including remote sensing for studies is based upon the 

fact that the temporal and spatial distribution of water- and vector-borne diseases (as well as their 

vectors) are dependent upon complex factors. These factors include a combination of human, 

demographic, socioeconomic, habitation, and environmental factors such as temperature, soil type 

and moisture, humidity, landscape structure, rainfall, vegetation, and water bodies, most of which 

can be measured, observed, and/or modeled with data from a combination of existing and planned 

systems. These environmental variables influence the suitability of any site as a habitat for both 

vectors and pathogens as well as their viability, abundance, breeding success, and transmission. 

Remote sensing and in situ observations contribute valuable data on these environmental variables 

from which epidemiological and demographic information can be developed. The resulting 

observations and information can be applied to: a) categorizing, mapping, and modeling parasite, 

pathogen, vector, and host habitats, b) observing changes in habitats, c) predicting related changes 

in host or vector populations, and d) creating risk maps useful for control programs.
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The primary remote sensing systems, which have been used for the land characterization aspects 

of epidemiological studies for infectious and vector-borne diseases, are passive remote sensing 

systems such as the MSS (Multispectral Scanner), TM, NOAA’s Advanced Very High Resolution 

Radiometer (AVHRR), and the Systeme Pour l’Observation de la Terre (SPOT) of France. High 

spatial resolution sensors (generally, resolution less than 1km by 1km) include the Landsat series 

of satellites, beginning in 1972, the SPOT series, initiated in 1986, and, more recently, IKONOS 

and MODIS (NASA’s Moderate Resolution Imaging Spectroradiometer). While these sensors 

offer higher resolution imagery and have been used for a number of epidemiological studies, 

factors such as cloud cover, data availability, low temporal frequency, and/or high cost have 

limited the use of these systems. 

Low spatial resolution sensors include: the NOAA series, operating since 1978, which carry the 

AVHRR; the Meteosat series from the European Organization for the Exploitation of 

Meteorological Satellites (EUMETSAT), first launched in 1977, carrying the High Resolution 

Radiometer (HRR) and designed for meteorological applications. These sensors suffer from cloud 

cover, but often higher data availability or coverage that helps address temporal issues.

USGS land cover data characteristics and a variety of geospatial data sets (terrain, hydrology, 

soils, geology, transportation) plus census data are important data sources for epidemiology 

studies. The USGS National Biological Information Infrastructure (NBII) is an electronic 

information network made up of many partners that provides access to biological data and 

information on our nation’s plants, animals, and ecosystems. Data and information maintained by 

federal, state, and local agencies, universities, nongovernmental organizations and the private 

sector are linked through the NBII gateway and made accessible to a variety of audiences, 

including decision makers, researchers, natural resource managers, educators, and the general 

public. 

The NBII Wildlife Disease Information Node is developing an integrated monitoring and 

information system to document the prevalence and spread of wildlife and zoonotic diseases both 

spatially and temporally via a nationwide web-based interactive mapping application and a webbased animal mortality reporting system that could be used to analyze disease trends, distribution, 

relationships, and patterns. In addition, disease reporting systems such as CDC’s ArboNet are 

important systems for integration into an Earth observation system.

Characterizing land use patterns and land cover is vital to understanding relationships between 

human populations, environmental stressors and disease. Remote sensing of changes in land 

use/land cover patterns (urbanization, defoliation, etc.) are currently available from the Landsat 

series of observations including IKONOS and MODIS as well as the aircraft system AVIRIS. 

This information is useful for characterizing population growth patterns (e.g., urban/suburban 

sprawl) between official U.S. census reports.

Satellites have yielded data products including normalized difference vegetation index, middle 

infrared reflectance, land surface temperature, air temperature and altimetry useful to health 

researchers. Studies supported by the National Institute of Allergy and Infectious Diseases 
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(NIAID) have been conducted on a variety of diseases using satellite technology including 

cholera, malaria, echinococcosis, sleeping sickness, Lyme disease, schistosomiasis, West Nile 

virus, and Venezuelan equine encephalitis. Researchers have also studied Rift Valley Fever, 

Ebola, onchocerciasis, trypanosomiasis, dengue fever, and bluetongue disease using data derived 

from various satellite technologies. Much of this work would be improved by increased spatial, 

temporal, and spectral resolution, as well as improved correlations with epidemiology, 

demographics, and on-the-ground or in situ “truthing.”

The following is a list of resources used by health researchers on an ad hoc basis. Although these 

systems represent major resources and significant amounts of work, they remain far removed from 

the potentially productive data demands of health researchers. Information on these websites 

reflects the necessity of remote sensing (RS) expertise to describe the capabilities of current 

instruments to scientists and to create user-friendly, standardized data products in collaboration 

with the consuming researcher. Individual research teams have developed several other data 

products for use in specific projects. These are not “in place” and fall under the category of 

data/data product sharing.

Elevation data: The Land Processes Distributed Active Archive Center (DAAC) website at the 

United States Geological Survey (USGS) provides 1km x 1km spatial resolution (GTOPO30—

global topographical data) elevation data. Other higher resolution elevation data are available from 

USGS through its web site at http://edc.usgs.gov/products/elevation.html. In addition, the Shuttle 

Radar Topography Mission (SRTM) provides useful Interferometric Synthetic Aperture Radar 

(IFSAR) data from over 80 percent of the landmass of the Earth between 60 degrees North and 56 

degrees South latitudes in February 2000. Digital Chart of World and the DEMs available in that 

product supplies uniform coverage for the World.

Weather: A large series of National Oceanic and Atmospheric Administration (NOAA) weather 

data systems are collected and archived. These examples are discussed elsewhere, but some 

important examples include: 

• Real-time rainfall estimation, where accumulations (1-, 3-, 6-, and 24- hours) in the 

Americas is available every half hour through NOAA from Geostationary 

Operational Environmental Satellite (GOES) data, and resolution is 4 km 

(http://orbit35i. nesdis.noaa.gov/arad/ht/ff/index.html). 

• Tropical Rainfall Measuring Mission (TRMM), which reports daily and monthly 

rainfall products for selected areas are available through the National Aeronautics 

and Space Administration (NASA) Goddard Space Flight Center (GSFC). The 

system is called TRMM Online Visualization and Analysis System (TOVAS) 

(http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/hydrology/. TRMM_analysis.html).

• The Global Precipitation estimation, supplying monthly mean precipitation data 

from the Global Precipitation Climatology Project (GPCP) on 2.5 x 2.5 degree 

(latitude x longitude) grids from 1986-2000 http://cics.umd.edu/~yin/GPCP/. 
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• Monthly data on precipitation estimates from several sources is provided on a 1 x 1 

degree grid from Jan 1979-Jan 2001; source is NASA/DAAC

(http://yang.gmu.edu/~yang/nasacd/www/gpcp_global_precip.html).

Wind Speed, Direction, and Height: Upper atmosphere winds are observed by GOES 

maintained by the National Oceanic and Atmospheric Administration/National Environmental 

Satellite, Data, and Information Service (NOAA/NESDIS). Central and North America are 

covered. These data can yield water vapor winds, infrared cloud drift winds, and visible clouddrift winds. (http://www.orbit.nesdis.noaa.gov/smcd/opdb/goes/ winds/wind.html) 

Sea Surface Winds: Global, near real time data derived from NASA’s Quick Scatterometer 

(QuickSCAT), European Remote-Sensing Satellite-2 (ERS-2) and Defense Meteorological 

Satellite Program/Special Sensor Microwave Imager (DMSP/SSMI) are available as a 22-hour 

composite. (http://wwwo2c.nesdis.noaa. gov/owinds/winds_browse.htm) 

Sea Surface Temperature (SST): Near-real time (hourly) data on SST are composed and posted 

on the NOAA CoastWatch Ocean Product Server every 3 hours from NOAA/NESDIS; historical 

data is archived and available through the Satellite Active Archive (SAA). 

(http://wwwo2c.nesdis.noaa.gov/cwatch/ gsst_browse_framed.htm) 

Sea Height Anomaly: Sea height and significant wave height from the Ocean Topography 

Experiment (TOPEX/Poseidon) are available through NOAA/NESDIS – NASA with a 2-day 

delay; height resolution under the satellite is 4-5 cm (http://www.aoml.noaa.gov/phod/dataphod/ 

work/trinanes/INTERFACE/index.html) 

Ocean Color: Sea-Viewing Wide Field of View Sensor (SeaWiFS) provides daily near real time 

chlorophyll concentrations through NASA/GSFC/DAAC (http://seawifs.gsfc.nasa.gov/cgibrs/ 

seawifs_subreg_12.pl) and ocean true color at 4 km resolution (http://seawifs.gsfc. 

nasa.gov/cgibrs/seawifs_subreg.pl?N=3). 

Land Surface Reflection and Emission: University of Maryland Moderate Resolution Imaging 

Spectroradiometer (MODIS) Land Products are available through the Land Rapid Response 

System of the University of Maryland and NASA. Resolution varies from 250 m to 1 km. 

(http://rapidfire.sci.gsfc.nasa.gov/)

Aerosol and Ozone : The Total Ozone Mapping Spectrometer (TOMS) follows dust storms, 

forest fires, and biomass burning. The latest 3-day composite index is available through 

http://toms.gsfc.nasa.gov/aerosols/today_aero.html; the daily total global ozone column is also 

available at http://toms.gsfc.nasa.gov/teacher/ ozone_overhead.html 

Vegetation Index: The Satellite Probatoire d’Observation de la Terre 4 (SPOT-4) polar orbiting 

satellite provides an indication of vegetation in the Normalized Difference Vegetation Index at 4 

km resolution; 10-day and monthly periods from 1998-2002 are available, and 1982-present data 

are available from NOAA/AVHRR through the Advanced Relay and Technology Mission 

(ARTEMIS) and agrometeorology (AGROMET) Data and Information of the Food and 
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Agriculture Organization (FAO) of the United Nations (http://metart.fao.org/~~/gbr/EVVGTGL.htm) 

Water vapor: Infrared, visible, and water vapor images are available from GOES-8/10, GMS-5 

and Meteostat-7, and the NASA Global Hydrology and Climate Center server at 

http://wwwghcc.msfc.nasa.gov/GOES/. Water vapor data are also available at 

http://www.archive.arm.gov/. 
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Human Activity and Location Patterns

Patterns of human activities and locations are necessary to estimate accurately and forecast human 

exposures. For instance, in a framework called Landscan the capability currently exists to 

integrate census data on people’s home and work locations with GIS data to quantify more 

accurately commuting activities. This allows for improved understanding of traffic patterns and 

the time an individual or population spends in transit potentially exposed to motor vehicle 

emissions. Similar technologies are being used by EPA, and they could be extended to 

characterize better other activities and locations.

Extreme Weather and Climate-Related Events

There is a lot of discussion as to what issues on human health and disasters/hazards should be 

addressed here versus the disasters/hazards societal benefit. The corresponding technical 

reference document, Reduce Loss of Life and Property from Disasters, can provide the reader a 

richer evaluation of these issues.

Events can have direct and/or indirect effects on all types of human settlements and activities. 

Weather, climate, and extreme weather-related events like drought and storms, hurricanes, 

tornados, and cyclones with excessive rainfall, often resulting in serious flooding can create health 

risks directly through injury, infection, and mortality as well as indirectly from epidemics of 

water-borne diseases such as cholera and typhoid fever and vector-borne diseases such as malaria 

and dengue fever. In addition, extreme weather can also impact the health and well-being of 

populations through forced movement of populations, loss of shelter, cont amination of drinking 

water, destruction of infrastructure, loss of healthcare facilities, and loss of food production and 

associated malnutrition

A wealth of remote sensing resources for weather and climate information is available to urban 

and rural planners and other decision-makers for addressing environment-related health problems. 

The visible and infrared sensors aboard NOAA's GOES (Geostationary and Polar-Orbiting 

Weather Satellites) and POES (Polar Orbiting Satellites) series make available views of weather 

phenomena on both coasts and oceans of the U.S. and South America, along with Europe’s 

Meteosat, Japan’s Geostationary Meteorological Satellite (GMS), and India’s Insat. 

NASA’s Tropical Rainfall Measuring Mission (TRMM), a joint mission between NASA and the 

National Space Development Agency of Japan (NASDA), monitors and studies tropical rainfall 

and the associated energy release which helps drive global atmospheric circulation, which, in turn, 

shapes weather and climate around the world. Seawinds, carried on Quickscat, measures winds 

over the oceans, which are critical in hurricane assessment. The TOPEX/Poseidon (Topography 

Experiment) and follow-on, JASON missions, provide sea surface height, a key to ocean 

circulation and global climate. 

MODIS and MOPITT (Measurements of Pollution in the Troposphere) on NASA’s Terra 

spacecraft, monitor a variety of weather and climate parameters such as temperature, clouds, 

moisture, atmospheric pollutants, and aerosols. The Earth’s radiation budget, critical to climate 
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studies, is provided by CERES (Clouds and the Earth’s Radiant Energy System) on TRMM and 

Terra; ACRIMSAT (Active Cavity Radiometer Irradiance Monitor) measures the total of solar 

energy, which reaches Earth, important to climate and global warming studies. Climate data on 

cloud and radiative processes for three climate regions (the U.S. Southern Great Plains, the 

Tropical Western Pacific, and the North Slope of Alaska) are available at 

http://www.archive.arm.gov/. These regional data are used to improve both cloud system models 

and general circulation models.

Some of the other important remote sensing systems that provide weather and climate 

observations and data useful to health studies are the MISR (Multi-Angle Imaging 

Spectroradiometer) on Terra (observes temporal changes in dust, clouds, and surface); the U.S. 

Defense Meteorological Satellite Program (DMSP) and its suite of measurements of such 

phenomena as clouds, lightning, and rainfall; the Earth Radiation Budget (ERBS) for climaterelated processes; UARS (Upper Atmosphere Research Satellite) for energy input, chemistry, and 

dynamics of the upper atmosphere, and coupling between the upper and lower atmosphere; and 

TOMS (the Total Ozone Mapping Spectrometer) which provides daily mapping of the Earth’s 

atmospheric ozone globally. 

Air quality/air pollution

Air pollution affects the environment in many ways that ultimately impact on our health and wellbeing: by reducing visibility, damaging crops, forests, and buildings; acidifying lakes and 

streams; stimulating the growth of algae in estuaries; and the build-up, or bioaccumulation of 

toxics (e.g., mercury) in fish and animals. Rapid development and urbanization around the globe 

have created air pollution that threatens people everywhere, as air pollution can travel great 

distances across oceans and national boundaries.

Exposure to air pollution from both natural and anthropogenic causes is considered to be one of 

the most serious world-wide health problems, and is expected to become worse with changes in 

the global climate and increased industrialization throughout the world. Exposure to air pollution 

may cause or exacerbate asthma, other pulmonary diseases, and cardiovascular disease. 

Epidemiologic studies conducted over the last ten years document increased rates of allergic 

respiratory disease. Urban particulate air pollution is associated with the rising rates of asthma 

and rhinitis. Individual susceptibility to air pollution is associated with genetic and dietary factors 

and occurs as a genetic predisposition to development of asthma and allergy or as a co-factor, 

exacerbating disease severity. A recent study reports an increase in heritable gene mutations in the 

offspring of male mice exposed to urban air pollution and supports the conjecture that air pollution 

poses a genetic risk to humans and wildlife. Particulate concentration is increased by motor 

vehicles, urbanization, and industrial processes, and by natural and man-made disasters.

Why now? Over 141 million people live in U.S. counties that exceed National Ambient Air 

Quality Standards. The potential of Air Quality (AQ) data, modeling, indicators, and forecasting 

for societal benefit is great in developing regions and in countries with substantial and increasing 

industrialization and urbanization. An IEOS program targeted to air quality could provide 

contributions to integrated data streams; enhanced capabilities from measurement platforms, as 
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well as access to data to foster forecast modeling; promote good will through capacity building; 

improve urban, local and regional understandings of air quality degradation; and develop decision 

support systems to respond to urban needs and decision-making.

A potential outcome would be an enhanced observational system integrated with modeling, 

indicators, and decision support tools which would improve the ability to forecast air quality 

across large parts of the country (and in other parts of the world) for which forecasts are not 

currently available, and could provide better information about emissions and transport 

mechanisms on regional to international scales. It is vital to provide important information to help 

the public avoid harmful exposures and to help air quality managers cope more effectively with air 

pollution episodes over the short and long terms.

Understanding air quality and its influence on people and the environment requires enhanced 

surface-based observations. Existing surface monitoring networks should be integrated with air 

quality observations from other platforms, including satellites, ships and aircraft, and used to 

develop and evaluate improved predictive indicators, models and decision support tools.

In situ and remote measurements of atmospheric trends for particulate transport as a function of 

altitude, wind direction, and velocity will facilitate rapid identification of geographically at-risk 

populations. These data, coupled with in situ measurements and indicators of particle 

concentration and size, and measurements of individual susceptibility to air pollution, would 

permit analysis of exposure and onset or exacerbation of allergic disease over time. 

For decades weather forecasters have used satellites to help forecast weather. Researchers are 

now showing that satellites can also help with forecasting air quality. In summer 2003, NASA 

and the EPA will prototype the use of satellite data in EPA’s AIRNow Air Quality Index (AQI), 

an index for reporting daily air quality, as a forecast tool. Through AIRNow, the AQI tells how 

clear or polluted the air is and the potential health effects. EPA includes five major air pollutants 

in the AQI: ground-level ozone, particulate matter (PM), carbon monoxide, sulfur dioxide, and 

nitrogen dioxide. (See Figure 1) EPA uses a network of monitors to record pollutant ground 

concentrations that are used to calculate the AQI level. State and local agencies report the local 

AQI to the public daily. Forecasts can help local officials & the media anticipate pollution levels 

and announce public health warnings.
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Current State of Science Observes O3, 

NO2, H2CO, SO2in UV-VIS

Trace 

Gases 

and 

Aerosols 

Important 

for Air 

Quality

CO & PM in IR

Figure 1. Air Quality Measurements

The EPA’s AQI provides a daily indication of pollutant levels in local areas around the United 

States. EPA uses ground monitors to record pollution levels and produce the AQI for five air 

pollutants (PM, O3, NO2, CO, SO2). NASA has numerous satellites collecting information on 

atmospheric conditions, including air pollutants (See Figure 2). For gaseous pollutants, there are 

several low-resolution measurements for global scale mapping (e.g., TOMS, GOME (Global 

Ozone Monitoring Experiment), MOPITT, Shuttle measurements, future EOS AURA and the 

European Envisat). For aerosols, the optical thickness may be retrieved by low-resolution sensors 

(TOMS) for global scale mapping, moderate-resolution sensors (e.g., AVHRR, MODIS, 

SeaWiFS) for continental to regional scale mapping, and high-resolution sensors (e.g., Landsat, 

EO-1) for regional to local scale mapping. NASA and EPA have compared their respective 

satellite and ground measurements and found strong correlations in their measurements. 

Although satellite measurements are useful in understanding total atmospheric loadings of select 

parameters (e.g. aerosol optical depth), they do not provide sufficient detail to characterize 

ground-level concentrations. In order to predict and understand human exposures to both gaseous 

and aerosol air pollutants, ground-level or in situ observations are necessary, as are enhanced 

geostationary satellite observations (see Figure 3). Currently there are a number of ground-based 

air monitoring networks and databases maintained by EPA (AIRS, CASTNET, IMPROVE and 

others) that provide archives of long-term air monitoring. Several air pollutants are measured 

continuously in real-time (e.g. PM2.5/PM10, CO, O3, NOx, and SO2).
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Current Derived Tropospheric

Observables for Air Quality

TOMS, AVHRR, Column

MODIS, MISR,

SeaWIFS, GOME, 

SCIAMACHY, GOES

Particulate Matter 

(PM2.5)

(as aerosol optical 

depth)

Carbon monoxide (CO) MOPITT, AIRS Column

Nitrogen dioxide (NO2)* GOME, SCIAMACHY Column

Sulfur dioxide (SO2) GOME, SCIAMACHY Column

Formaldehyde (H2CO) GOME, SCIAMACHY Column

TOMS/SBUV, AIRS

Current Sensors

Ozone (O3)* Column

Pollutant Measurement

*requires removal of stratospheric overburden

Figure 2. NASA Satellites Collecting Data on Air Quality

GEO provides the appropriate 

time resolution for air quality

O3, aerosols, & 

precursors 

change rapidly 

during the day.

Stars indicate typical times for Low Earth Orbit (LEO) measurements

Circles indicate typical times for Geostationary Earth Orbit (GEO)

hourly measurements

Red and blue lines indicate continuous ground-based measurements

GEO

LEO

Figure 3. Comparison of Ground Level and Satellite Measurements
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Water quality/water pollution

Over one billion people in the world are without safe drinking water. Source water and 

downstream waters are compromised, and water treatment is uncommon. Water quantity is also a 

problem, affecting the source, and also limiting the capability to dilute polluted waters. 

Water pollution has been studied extensively to assess environmental health. The primary water 

quality issues are associated with surface water, recreational waters and drinking water, each of 

which pose different challenges in understanding the impacts to public health and the 

environment. Surface waters include those used for transportation or economic interests as well as 

those used for drinking water. Issues associated with recreational waters include water-borne 

pathogens and contaminants that may have direct health effects or enter the aquatic food chain and 

finally are consumed by humans. Drinking water contaminants are primarily pathogens and 

chemicals that are consumed by humans, animals, and plants, and, thus, pose human health and 

environmental risks. Drinking water is further compromised by the absence of or limited nature of 

water treatment and subsequent discharge.

Ground-based observations and monitoring networks are vital part of these efforts and need 

maintenance and enhancement to continue to assess water quality. Remote sensing of surface 

waters has been possible for some time using a variety of satellite platforms including SEAWIFS, 

AVIRIS, MODIS and others. These observations have been useful in assessing, in particular, 

primary productivity (algal blooms, plankton growth, etc.), which may be impacted by 

environmental stressors.

Ground-based observations and monitoring networks are also an important component in 

assessing water quality and water pollution. EPA, USGS, NOAA and others have an extensive 

background in conducting monitoring networks and archiving data on surface waters and drinking 

water (e.g., BASINS, AQUA). Examples include the Watershed Assessment, Tracking and 

Environmental Results (WATERS), Safe Drinking Water Information System (SDWIS) and 

PRAWN – the Program Tracking database for Advisories, Water quality standards and Nutrients. 

PRAWN is an updated database containing information specific to surface and recreational waters. 

The USGS National Water Quality Programs (NAQWA) provide access to data from over 1.5 

million sites around the country, including real-time and historic stream flow and stage data, 

ground water levels, water quality data, and site information at 

http://water.usgs.gov/owq/data.html. NOAA has a number of programs that track water in the 

atmosphere, on the Earth and in water systems.

In conjunction with in situ measurements, models, indicators and remote-sensing capabilities, 

existing databases serve as powerful tools useful in assessing environmental and public health.

UV Radiation

Ozone depletion and the associated increases of ground-level ultraviolet radiation are a serious 

health concern. Excessive ultraviolet radiation (UV) is well known to have a number of harmful 

effects on humans, such as sunburn and skin cancer, cataracts, and immune system suppression. 
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In addition to ground-based systems for measurement of UV radiation levels, a mature remote 

sensing system established in 1978 continues to provide daily measurements of UV radiation at 

the Earth’s surface on a global basis from the Earth Probe/Total Ozone Mapping Spectrometer 

(TOMS). This system provides data and information in real time on the web and is used routinely 

for decision-making and early warning systems as well as for retrospective time series studies 

using the long-term data sets.

Ocean/Coastal Issues

Data on winds over the ocean, critical for hurricane and storm assessment, are monitored by 

Seawinds aboard Quickscat. Sea surface height and wave height are both derived from altimetry, 

most commonly from TOPEX/Poseidon, operated by NASA and France’s Centre National 

d’Etudes Spatiales (CNES) and follow-on, JASON. Sea surface temperature, sea surface height 

and wave height have been useful in recent studies investigating the relationship between cholera 

outbreaks in Bangladesh and sea surface temperature, sediment load, phytoplankton abundances, 

and sea surface height. 

Of the key ocean and coastal health-related issues recently defined, the most readily-addressed 

through remote sensing and in situ measures are harmful algal blooms (HABs), certain aspects of 

biotoxins, the dynamics of infectious diseases, pollutants, and extreme weather hazards. 

Evaluations of the ocean for health purposes is best performed with combinations of in situ

(moored, buoys, shipboard, or surface-mounted) and remote sensor instruments to characterize the 

dynamics of this complex three-dimensional, patchy system. A number of remote systems have 

proven useful for observing the oceans for health purposes including sensors to measure ocean 

color, sea surface temperature, wave height, and sea surface height. 

Observing ocean color is a means of determining ocean clarity and, therefore, enables detection of 

algal blooms, sediments, nutrients, and some contaminants important to studies and monitoring of 

harmful algal blooms (HABs), biotoxins, certain pathogens, and pollution. The systems most 

useful for these applications are SeaWiFS, launched in 1997 and the higher-resolution MODIS, 

launched in 1999. Sea surface temperature can be used for observing ocean circulation and ocean 

currents that transport algal blooms, pollutants and pathogens, and can be obtained from the 

NOAA, AVHRR, and MODIS thermal bands.

Although the coastal states have no common data system for data they collect, a few have 

monitoring programs designed to prevent human illness from shellfish poisoning syndromes and 

to monitor the environment for blooms and forecast their development and movement. In 

addition, state shellfish monitoring programs detect toxins in different fisheries species either to 

provide advance warning of outbreaks or to delineate areas that require harvest restrictions. Some 

states also have environmental monitoring programs for plankton and fish in coastal estuaries and 

bays to provide early warning of blooms. These programs monitor the abundance of a few 

harmful algae species either directly (i.e., counting cells), indirectly (i.e., satellite remote sensing), 

by measuring the levels of HAB toxins in both water and shellfish, and/or by determining 

environmental conditions conducive to HAB formation.
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Local agencies perform routine analysis for bacterial contamination. They select among standard 

procedures and standard indicator bacteria and a monitoring schedule for collecting water samples 

and culturing for indicator bacteria. Results are obtained in 24-72 hours. In many instances, 

based on experience, indicator bacteria are simply assumed to be at high levels following rainfall 

events.

Contaminant Transport and Deposition

There are a number of system and programs for direct tracking of environmental contaminants by 

in situ and remote sensing technologies. These compliment the diverse suite of existing Earth

remote sensing satellites routinely observing environmental parameters associated with the 

atmosphere, oceans, rivers, and sea ice which could be used for more aggressively monitoring the 

transport mechanisms that move contaminants from place to place. 

Atmospheric transport, described earlier in this section under the air quality discussion, may best 

be observed through TOMS, MOPITT, MODIS, SeaWiFS, AVHRR, and Landsat. To observe 

movement of rivers, sediments, and, indirectly, associated contaminants, the following systems 

could be utilized: polar-orbiting microwave data from Radarsat and Synthetic Aperture Radar 

(SAR), and visible IR (infrared) data from SeaWiFS, AVHRR, and MODIS. 

Movements of ocean waters, sediments, algal blooms and some pollutants may be observed 

through TOPEX/POSEIDON, SeaWiFS, MODIS, and/or AVHRR. Finally, sea ice extent, 

concentration, motion, and velocity are being monitored by global passive microwave (SMMR, 

SSM/I), synthetic aperture radar (Radarsat, ERS-1, ERS-2), and polar VIS/IR (MODIS, AVHRR, 

SeaWiFS). (Radarsat, ERS-1, ERS-2), and polar VIS/IR (MODIS, AVHRR, SeaWiFS).

Use of Genomics

Recent scientific advances have demonstrated that relatively long segments of DNA can be 

isolated directly from environmental samples. This capability will enhance our understanding of 

the genetic diversity and functions of microbial communities such as those related to ocean 

biogeochemical cycles and climate change. Determining the DNA sequence of the collective 

genome (also called “community” or “meta” genome) of the many organisms will allow inference 

of protein complexes and regulatory networks and, if done over time, on changes in the make up 

and overall health of a given ecosystem. This information will provide insights into the 

community’s metabolic capabilities, including those of members that cannot be grown in 

laboratory cultures.

For example, ocean microbial communities play a critical role in regulating atmospheric carbon 

dioxide and the global climate by removing billions of tons of carbon from the air each year. 

Monitoring how populations change in different areas over time can provide a window into these 

vital processes and yield new strategies for mitigating global climate change.

In recent years, the genomes of numerous marine microorganisms, including the most abundant 

photosynthetic microorganisms in ocean surface waters (Synechococcus and Prochlorococcus), 
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have been sequenced. The knowledge gained from further explorations into individual as well as 

metagenomes can be applied to develop high throughput ecogenomic sensors that will yie ld a new 

understanding of ocean processes, including those affected by climate change, pollution, or other 

local or global events. Such sensors can be incorporated into the advanced observation systems 

being proposed by Ocean.US (www.ocean.us) and the National Ocean Partnership Program 

(NOPP, www.nopp.org), a 15-agency consortium. 

Thus far, the biological research planned for the Integrated Ocean Observing System (IOOS) is 

limited to conventional measurements of species and abundance of fish and zooplankton, species 

of phytoplankton, and optical observations. This new capability would greatly enrich IOOS data 

with genomic observations and advance the shared goal of improving predictions of climate 

change and its effects on coastal populations.

A number of scientists have pioneered the application of genome science to ocean research in 

fairly small scale, short-term studies performed from ship platforms. The high-throughput 

approaches envisioned for ecogenomic sensors would merge the knowledge gained from genome 

research programs with nanotechnologies and smart sensors to refine the measurements of 

important biological nutrients and other physical and chemical parameters of nanoscale 

environments—the same scale at which microbes live. These can be placed on IOOS platforms 

and on autonomous underwater vehicles, such as depth-profiling carbon explorers, to survey the 

metagenomes of deeper U.S. coastal waters and major ocean basins. The data collected will lead to 

a comprehensive and predictive understanding of ocean cycles and the effects of global climate 

change, pollution, and other environmental perturbations on the world’s oceans.

Living organisms integrate environmental information and reflect the physical-chemical 

characteristics of the surrounding environment. Ecogenomic sensors could help to answer key 

questions such as the following:

How is climate change affecting key microbial communities involved in carbon fixation and 

sequestration?

Is the balance changing between autotrophic (carbon dioxide fixing) and heterotrophic (carbon 

dioxide producing) microbial communities?

Have changes occurred in sentinel species that can warn of impending ecosystem changes? For 

example, are red tide or Pfiesteria species increasing in abundance? Such increases would have

broad economic impacts.

Ultimately, applying the exciting science of genome research programs to planned ocean 

observation systems such as IOOS will provide a tangible, high-impact product that address global 

scientific and societal needs.

4. Major Gaps and Challenges

In order to create a comprehensive, useful Earth observation system, it is necessary to enable the 

easy transfer of environmental information to researchers, response communities, and 
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policymakers. Thus, it is important to develop user-friendly systems for quick access to Earth 

science data. However, many factors have hindered the use of space- and ground-based data for 

health applications. Some of the most important are:

1. Lack of appropriate spatial, temporal and spectral resolution measurements by the 

current ground or in situ and satellite sensors. 

2. Lack of good communication and understanding between the data producer 

community and users in the health and environment fields of research.

3. Complexities associated with health and environment relationships due to the diversity 

and number of variables.

4. Absence of continuous temporal and spatial data sets required for the study of specific 

diseases or disorders, including human activity patterns.

5. Difficult access to data and value-added products due to differences in format, 

resolution, projection, computer systems and lack of an integrated system with 

generally accepted standards for unified studies.

6. Limited access and high cost of high-resolution in situ satellite remote sensing data.

7. Insufficient technology transfer methods to move from research to operational 

environments, and need for an information system.

8. Inadequate development of remote sensing and ground-based methods to continuously 

monitor environmental pollutants (including speciation) or their indicators affecting 

human health.

9. Lack of ongoing observation systems available for collecting human activity or human 

exposure data. Data are currently only available on a study-by-study basis.

A focused effort is needed to improve technology transfer and development of user-friendly tools, 

indicators, models and decision support systems for the mass distribution of data and products. In 

addition, effective implementation of these systems requires the promotion of both public and 

private sector use and dissemination of observation data/products and effective technology transfer 

in order to extend the combined use of ground or surface measures, remote sensing, and models 

and decision support systems beyond the traditional science community to be applied to the needs 

of decision-makers and the public. This, in turn, requires the development of information systems 

to communicate more efficiently observations, information, indicators, models and decision 

support systems. In particular, the combination of in situ measurements and remote sensing data 

along with geographic information systems (GIS), global positioning systems (GPS), models, 

indicators and others are fundamental tools for the planning, analysis, surveillance and 

intervention in the control and management of infectious diseases outbreaks. To take full 
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advantage of these technologies, they need to be fully integrated with one another in order to 

benefit the end-user in a timely and cost-effective way. 

A much better understanding of the transmission of infectious disease would be obtained by 

increased use of high-resolution hyperspectral sensors. The ability to call up quickly overflights 

during cholera epidemics, for example, would be invaluable. Multitemporal images at 3-4 

resolution of regions with seasonal epidemics of diseases influenced by environmental factors 

would be helpful for establishing local conditions in oceans, estuaries, coasts, and rivers as 

diseases emerge, if a data-purchase arrangement can be made appropriate to research applications 

and the budgets of the relevant countries.

Many infectious diseases are greatly impacted by the weather and by patterns of agriculture. 

Qualitative and quantitative analysis of agriculture and vegetation cover remains a key ne ed. 

Improved resolution will assist to identify, understand, and predict crop yields and evaluate the 

scale of potential problems in the food supply and its transportation, such as crop failure and 

famine or unexpectedly high yields that may presage a booming rodent population and associated 

disease risks. Salinity and turbidity are important features, but while many studies have shown that 

salinity is correlated with spectral reflectance, this is quite difficult to control for, and improved 

products would be helpful. 

An immediate need is to greatly improve the spatial resolution of Earth observation for specific 

epidemic areas that are also well-served by on-the-ground disease, demographic, ecological, or 

other information (e.g., at field sites). This will form the basis for developing new correlates and 

will inform the evaluation of historical remote sensing data with historical data on epidemics and 

the establishment of disease prevalence patterns. The number of diseases that can be productively 

studied with poor spatial resolution is very limited. 

The interactions of pathogen populations with human populations represent a critical area of 

human health research. In cases where transmission between humans involves water, an aerosol, 

or a vector-mediated stage, the space between humans becomes critical in determining if disease 

transmission is positive or negative. The better the spectral, spatial, and temporal resolution, the 

more likely it is that true associations will be identified, and the more applicable remote sensing 

will become to infectious disease prediction and control. It is essential that a concerted effort be 

directed to developing user-directed data products that are supported by on-the-ground physical, 

biological, epidemiological, and census studies. Additionally, it may be appropriate for userdirected specifications to be included in new space- or airplane-based instrumentation that will be 

available to participants to obtain data contemporaneously with unexpected disease emergence.

It is important to note that most research linking environmental exposure to the increased 

prevalence or exacerbation of asthma and allergy is based on in situ measurements in the local 

environment. Significant bodies of information exist within discreet scientific domains. For 

example, geologists have studied quartz particulates in dust clouds; aerosol physicists have studied 

aerosolized pollen behavior, but the behavior of mixed materials within a single cloud and the 

biological consequence of mixed exposure are not clearly understood. Currently, access to 

satellite data is limited, there is minimal support for data sharing, and very few multidisciplinary 
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teams exist that are equipped to evaluate the relationship of these physical phenomena to disease 

outcomes and public health practice.

Application of enhanced in situ and remote sensing data and techniques to air quality evaluations 

is very promising, and a potential area for early, demonstrable results. Efforts like the State of 

New York GRID air quality forecasting system, a joint effort between the State, EPA and NOAA, 

should be encouraged to demonstrate the promise of forecasting conditions for the public and 

decision-maker, but also track the results to see if forecasting produces improved air quality by 

people and governments making decisions that reduce pollution.

Additional challenges include the following needs:

• A framework within the scientific community regarding data sharing – health, plant, 

animal, and environmental

• Agreed-upon standards for comparison of disparate sources of data and for 

establishment of interoperable systems

• Conversion of paper documents that contain useful date to a standardized digital 

format 

• Provision of temporal and spatial data with enough parameters to be useful in both 

static and dynamic models

• Validation of historical, baseline and real-time data 

• Improved metadata

• Uninterrupted time series environmental data – historical and future

• Integration or linkage of data collected in a laboratory with that for the same 

environmental agent collected in the natural environment

• Collection of data at appropriate spatial scales to inform relevant regulatory 

action/emergency response

• Improved Data archiving to allow for a better understanding of the development of 

chronic diseases and diseases resulting from long-term environmental exposures 

• More extensive databases on human activities to integrate with pollutant 

concentrations to estimate exposures

• Integration and display of data from multiple scientific disciplines in a meaningful way 

in order to create a successful integrated observation system that is useable by 

members of the environment; human, animal, and plant health communities, and by 

decision makers

• Improved surveys of food contaminants and consumption patterns

• Better indicators for bacterial/chemical contamination of water resources

• Routine monitoring of sea surface temperature to aid in predictions of bacterial 

contamination in recreational and shell fishing areas.

• Appropriate spatial and temporal resolution data to relate directly to exposure or 

human health. Models should be developed to predict or forecast exposures.

• Archive model outputs for use in future health and epidemiological studies to 

determine relationships between environmental exposures and disease

• Continued research on use of genomics in monitoring for environmental factors that 

influence human health and well-being
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5. Future Earth Observation Systems that May Fill Gaps

The current in situ and remote sensing technologies offer great potential for human health studies. 

It is important to maintain and enhance existing systems. Clearly, the advent of geostationary 

sensor systems with improved spatial and spectral resolution could allow study of air, weather, 

wetland, water and related phenomena that have influence. A day/night sensing capability is 

important in the UV, visible, near, middle and far infrared as well as the microwave regions. A 

denser network of air and water quality observations would be very helpful.

A number of efforts could be enhanced by the use of synthetic aperture radar (SAR), including the 

disasters and hazards societal benefit. This technology is especially useful because it is capable of 

operating day or night and can obtain data through clouds. While a number of technical 

difficulties such as data interpretation, calibration issues, software, and problems related to 

topography have prevented this technology from widespread use in public health studies to date, 

the potential for its application to public health issues is great because it would enable collection 

of information on important parameters such as accurate land cover change characterization, 

delineation of water bodies and flooding extent, and soil moisture. 

The future NPOESS system will have much of the capability of the MODIS instrument. It will 

provide vegetation, land use/cover variability (as a replacement for Landsat), surface temperature 

and some soil moisture capability, along with cloud and aerosol detection. However, the spatial 

resolution will not be much different from current instruments. The need for very high spatial 

resolution sensors to monitor mosquito-breeding sites will continue. For precipitation 

measurements, the Global Precipitation Mission has great promise, but it is going to be delayed to 

about the end of the decade for launch. 

For coastal managers, new remote sensing technologies such as optical detectors, autonomous 

underwater vehicles and satellite sensors other than SeaWiFS are being developed to detect and 

track HAB movements in time to take proactive measures to protect public health. The NCCOS 

Center for Sponsored Coastal Ocean Research (CSCOR), through the ECOHAB and MERHAB 

programs, supports research on rapid and highly selective tools and sensors for monitoring and 

testing of harmful algal blooms. These prototype tools are aiding in the assessments of public 

health impacts of harmful algal blooms, the detection of toxins and harmful species at low 

concentrations, and to understand the effects of sub-lethal exposure to toxins. New remote 

sensing technologies such as optical detectors, autonomous underwater vehicles and satellite 

sensors are also being developed to detect and track HAB movements in time for coastal managers 

to take proactive measures to protect public health. Some of this technology has already been 

incorporated into ongoing testing programs and has allowed for the proactive opening and closing 

of shellfish harvests. Efforts are underway to incorporate successful sensors into regional 

observing systems.

In addition, CSCOR supports development of a suite of coupled physical-biological ecosystem 

models to enable timely ecological forecasts for a variety of key management concerns such as 

harmful algal blooms, hypoxia, fisheries, and cumulative coastal impacts. These models will 
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ultimately be transferred to state and federal management entities and incorporated into regional 

observing systems.

Recent scientific advances have demonstrated that relatively long segments of DNA can be 

isolated directly from environmental samples. This capability will enhance our understanding of 

the genetic diversity and functions of microbial communities in soil and water and offers the 

opportunity to develop new sensors for the presence of organisms that impact on human health or 

for ecosystem changes that enhance the likelihood of their proliferation (e.g., red tide or 

pfiesteria).

6. Interagency and International Partnerships

Due to the multiple factors involved in addressing environmental health issues, scientists from 

many disparate disciplines who are not accustomed to working together are needed to address 

these issues. Therefore, to create a successful integrated observation system usable by members of 

both the environment and health research, management, and policy communities, partnerships 

among these disciplines and stakeholders are essential. Strong partnerships help ensure that the 

appropriate data sets are collected, integrated, interpreted, and used properly. While there are a 

number of interagency partnerships, which exist at this time, most were developed on a project 

basis and are frequently between researchers within individual agencies and institutions. These 

partnerships are generally specific to the project under development and are contingent on 

continued researcher interest and funding. It will be critical to make an aggressive effort to 

develop a system of comprehensive partnerships among agencies, states, and other parties in order 

to create a useable as well as useful observation system. In addition, Consistent practices, 

interoperability, and information sharing among State and local agencies that gather data are 

needed.

Examples of existing partnerships include: NOAA/NWS provides weather forecasts to CDC staff 

who are involved in research on the effects of heat waves and in working with State and Local 

officials to prevent heat-related morbidity and mortality. Similarly, HHS and FEMA for their 

disaster preparedness and response roles rely on NOAA/NWS to predict the location and severity 

of extreme weather events. EPA and NOAA have partnered to produce multiday forecasts of air 

pollution and air quality in cities throughout the U.S. NIEHS researchers use EPA data on air and 

water quality for health effects studies. UCAR/NCAR provides UV exposure data for melanoma 

studies. University researchers in the U.S. and abroad supported by the NOAA/EPA/NSF/EPRI 

Program on Climate Variability and Human Health use observational data from NOAA, NASA, 

CDC, and state and local public health agencies to characterize the link between vector-borne 

diseases and climate with the goal of developing early warning systems for disease outbreaks. 

NIAID and NASA have an interagency agreement to support training for African scientists in the 

use of new technologies for the control of malaria. The purpose of the initial effort was to 

determine if remotely sensed information could be used to develop predictive models for risk of 

malaria transmission. 
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Bacterial contamination is monitored by local public health agencies, and these same agencies use 

the data. NOAA, EPA and other Federal agencies assist by providing updated methodologies. 

National databases on bacterial contamination are updated by collecting data from state agencies 

that, in turn, collect it from the local agencies that made the measurements. The USGS National 

Biological Information Infrastructure (NBII), which is composed of multisector partnerships 

(Federal, state, and local agencies; universities; private industries, and nongovernmental 

organizations), provides increased access to biological data and information on our nation’s plants, 

animal, and ecosystems to a variety of audiences including researchers, natural resource managers, 

decision makers, and the general public.

Environmental monitoring that crosses national borders is often best coordinated by the 

appropriate international organizations. For example, the international aspects of bacterial water 

quality monitoring are best handled through the World Health Organization or, in the Americas, 

through the Pan American Health Organization. New partners from the remote sensing and 

environmental community could provide useful contributions to those monitoring activities. 

7. U.S. Capacity Building Needs

Relatively few individuals presently are able to bridge the gap between the Earth observation data 

and the health communities that use that data and data products. Clearly the full value of Earth

observation data being used with health data will not be realized until we have more individuals 

trained in this specialty. For example, training for both the malaria teams and those charged with 

developing predictive models for climate and other factors that regulate mosquito vector 

populations, and therefore, the transmission of the parasite is imperative. 

Education and training for people who design, build, and operate observing systems, who analyze 

data, and who produce data products are ongoing needs. Conversely, building institutional 

willingness and capacity in public health to move beyond surveillance and response to prediction 

and prevention by effectively using observational data in new decision support tools will be 

essential. The federal sector should continue to work with state, local and private sector service 

providers and authorities to enhance planning and response capabilities.

The need for education and training at all levels in developing countries is as great as the need for 

equipment to gather and process data. Examples where the U.S. is working to increase capacity 

in developing countries include the Fogarty International Center at NIH/HHS International 

Research Training in Environmental and Occupational Health Program, which provides shortterm, long-term, degree-oriented and post-doctoral training to developing country scientists in 

their home countries and in the U.S. It also provides grants for collaborative research between 

U.S. and developing country scientists through its Health, Environment and Economic 

Development Program now operating in 11 countries. NASA, NOAA, EPA (STAR grants and 

fellowships), and other Federal agencies also have programs for capacity building in related areas. 

It is important to continue and expand these special efforts to build appropriate capacity in 

developing nations where health and well-being problems are often overwhelming. This is a 

complicated issue--in developing countries, for example, it is not necessarily a lack of knowledge 
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that often prevents enforcement of standards; rather, limited public health funds that are devoted to 

more pressing problems.

8. Conclusions

Healthy Public – Societal Imperatives

A growing world population, projected to roughly double in the next few decades, will 

increasingly demand access to crucial resources like clean water and plentiful food. The 

concentration of populations is shifting from rural areas to urban centers, many in low-lying 

coastal regions or seismically active zones. In the United States, more than half of the population 

lives within 50 miles of our coasts, areas particularly vulnerable to storm surges and flooding, and 

water and air quality issues. We rely upon coastal regions for healthy fisheries, and reliable 

transport and navigation. Increased dependence on infrastructure networks (roads, power grids, 

oil and gas pipelines) increases our potential vulnerability to natural disasters, and requires 

improved understanding of the complex workings of Earth systems in order to protect society and 

manage our resources in a more efficient and effective way. 

The ability to predict the appearance and intensity of diseases has long been a goal of public health 

workers, economic planners and ordinary citizens. For those diseases that are influenced by 

environmental factors, the development of predictive indicators and models will open the door to

the possibility that if one could link risk of disease with certain variables, one could eventually 

apply these indicators and models to predict occurrence and possibly control or prevent these 

diseases in human populations.

All the components of the integrated Earth observation system contribute to improving human 

health and well-being. Researchers, service providers, policy makers, and the public use Earth 

observations to make decisions and take actions. These decisions and actions help reduce the 

impact of disasters, protect and manage natural resources, adapt to and mitigate climate variation, 

support sustainable agriculture, forecast weather, protect areas valued for recreational, religious, or 

aesthetic purposes, and prevent disease/dysfunction due to environmental exposures or conditions 

that increase the likelihood of transmission of water- or vector-borne diseases.

Considerations for Future Systems

• Higher spatial and temporal resolution. The combination of improved and enhanced 

ground or surface measures and high spatial resolution and repeat coverage over an 

area are among the most critical parameters for future instruments, regardless of the 

channels utilized. 

• Flexible information system. The system must allow for continuous updating with

new and additional information in a near-real time scenario for flexibility in the types 

of information and the method of update.
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• Improved access and use of remote sensing data. Easier access to improved and 

enhanced ground or surface measures and use of remote sensing data is needed, as well 

as capacity building, communications and outreach to foster the use of data, 

information, models and decision support systems

• More continuous temporal and spatial data sets for disease studies. Developing 

methodologies to measure environmental stressors in real-time across large spatial 

domains will enable better prediction and forecasts of exposures and possibly the 

development of diseases caused by exposures.

• Expansion and development of interdisciplinary (health-environment) research and 

activities. 

• Formation of a distributed federation of data bases (including ground based and health 

data). The collection of quality data to predict changing environmental conditions is 

needed. Provisions for sharing environmental and human, plant, and animal data on a 

timely basis in a distributed federation of databases designed to make existing 

information more accessible need to be put in place in the form of an information 

system. Standards to compare disparate sources of data are needed, and adequate 

metadata should be developed for all data collected. The use of bioinformatics and 

state-of-the-art information technology capabilities (e.g., geospatial, visualization) to 

increase understanding of the effects of environmental factors on human health and 

well-being should be encouraged. Models that can handle multidisciplinary data, 

including a national capability in infectious disease modeling, should be further 

developed. 

• Interoperability. Coordinated data management and interoperability across agencies 

and user groups is required a system of Earth observation systems.

• Development and implementation of a surveillance program to monitor the presence in 

the environment of disease organisms, their vectors and natural reservoirs.

• A surveillance and monitoring program for air, water and land pollution episodes. 

Improved assessment of pollution episodes caused by natural and anthropogenic 

processes will lead to better protection of public health and the environment. 

• A surveillance and monitoring program for assessing human activities and locations. 

Without better knowledge of human activity patterns and the locations of people it will 

be very difficult to forecast or estimate exposures to pathogens, vectors, or 

environmental stressors.

• Development of improved sensors for HABs and their toxins 
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• Increased interdisciplinary research to develop and integrate modeling, retrospective, 

broad-scale, and process studies that underpin the decision support tools needed to 

solve real-world problems. 

• Develop improved and faster indicators for the human disease potential of recreational 

and shell fishing waters.

• Continued support for national biological information systems, such as the USGS 

National Biological Information Infrastructure (NBII) and the NBII Wildlife Disease 

Information Node. Data and information maintained by federal, state, and local 

agencies, universities, and the private sector are linked through the NBII gateway and 

made accessible to decision makers, researchers, natural resource managers, educators, 

and the general public.

• Develop satellite-based sensors to measure vertical profile of atmospheric 

contaminants (PM, air toxics), especially at ground level. This is especially important 

to better characterize inhalation exposures of toxic airborne compounds.

• Develop remote sensing capabilities to monitor emissions inventories from natural and 

anthropogenic sources in real-time. Current emission inventories are either selfreported or based on a few measurements scaled on an annual basis. Improved 

databases of emissions inventories will enable better prediction of source impacts on 

the environment and public health.

• Build an across-the-board system for training and education at the intersection of 

environment and health observations, data collection and analyses.

• Increase research on use of genomics in monitoring for environmental factors that 

influence human health and well-being.