Luvall, Jeffrey C.

NASA Technical Reports Server

1 
 
Nasa’s Public Health Program: How We Can Use NASA Satellite Data To Study 
Global Public Health Issues 
 
Jeffrey C. Luvall 
NASA Marshall Space Flight Center 
Huntsville, AL 
jluvall@nasa.gov 
 
 
https://ntrs.nasa.gov/search.jsp?R=20120001683 2019-08-30T18:57:50+00:00Z
2 
http://science.nasa.gov/media/medialibrary/2010/08/30/2010SciencePlan_TAGGED.pdf 
 
2010 NASA Science Plan 
The 2010 Science Plan identifies the direction NASA has 
received from the Administration and Congress, advice received 
from the nation's science community, principles and strategies 
guiding the conduct of our activities, and challenges we face. 
The plan that results enables NASA, as Administrator Bolden 
says, to "do the best science, not just more science."  
 
The NASA Earth Science strategic goal is stated as, “Advance 
Earth System Science to meet the challenges of climate and 
environmental change.” 

Aqua 
Terra 
Aura 
EO-1 Landsat-7 
ACRIMSAT 
Jason 
OSTM/Jason 2 
SORCE 
TRMM 
GRACE 
CALIPSO 
CloudSat 
Current NASA Earth 
Remote Sensing 
Observatories 
QuikSCAT 
NASA Applied Sciences Program 
Mission Statement 
 
 
Advance the realization of societal and 
economic benefits from NASA Earth 
science by identifying societal needs, 
conducting applied research and 
development, and collaborating with 
application developers and users. 
Technology 
Missions /  
Observations 
Data and 
Archives 
Research 
and Analysis 
Models / 
Predictions 
Policy 
Decisions 
Forecasting 
Results of 
NASA Earth 
Science Research 
Societal Needs 
Applied Sciences 
Program 
Response  
& Recovery 
 
Management 
Decisions 
NASA Applied Sciences Architecture 
Ecological 
Forecasting 
Agricultural 
Efficiency 
Air Quality 
Weather 
Climate 
Water 
Resources 
Disaster 
Management 
Public Health 
Applied Sciences Program 
Eight Program Elements 
8 Patz et al., 2000 
http://www.usgcrp.gov/usgcrp/Library/nationalassessment/healthimages.htm 
Why public health? 
Source:  GEO, 2003 
9 
EMERGING
RE-EMERGING
ZOONOTIC
VECTOR-BORNE
* Modified from Morens et al. 2004 Nature 430:242
Global Emerging Diseases*
New Environmental Threats 
This visible image of the Gulf oil slick was taken on May 9 at 19:05 UTC (3:05 p.m. 
EDT) from MODIS aboard NASA's Aqua satellite.  Crude oil brings volatile organic 
compounds into the air which can react with nitrogen oxides to produce ozone. 
 
Focus Areas of Public Health 
The Public Health application area focuses on 
Earth science applications to public health 
and safety, particularly regarding infectious 
disease, emergency preparedness and 
response, and environmental health issues.  
The application explores issues of toxic and 
pathogenic exposure, as well as natural and 
man-made hazards and their effects, for risk 
characterization/mitigation and improvements 
to health and safety. 
 
Dust Surveillance in the Southwest USA  
Upper Left:  Dust observed from the NOAA GOES 12 satellite 
at 20:26 UTC on December 15, 2003.  The red dashed line 
encircles a large dust storm occurring in west Texas.  
 
Lower Left:  DREAM modeled dust concentration 
distribution for 20:00 UTC on December 15, 2003, before 
ingesting NASA MODIS land cover observations.  
 
Lower Right:  DREAM modeled dust concentration 
distribution for 20:00 UTC on December 15, 2003, after 
ingesting NASA MODIS land cover observations.  Note that 
the DREAM model much more accurately represents the 
NOAA GOES 12 observed dust storm after ingesting NASA 
Earth science satellite observations.  
http://phairs.unm.edu 
http://nmtracking.unm.edu 
The dust projects in the desert SW have three primary components: 1) improving forecasts of fine particulates by assimilating monthly masks of PM into 
the DREAM model (nested inside the WRF of NOAA); 2) incorporating MODIS AOD and modeled fine particulates from DREAM into CMAQ to estimate 
aerosol concentrations over the 4-corners region of Utah, Arizona, Colorado and New Mexico; and 3), integrating the products from these data and 
models into the New Mexico EPHTS for analysis and dissemination.   
 
By using monthly data for barren land distribution, it is possible to identify PM sources through change detection methods. The PM sources are derived 
from a 16-day NDVI land cover product combined with an improved land cover classification algorithm to inventory land patterns that alternate between 
cropped and barren ground.  
 
Results have shown that the timing of dust storms in the desert SW can be accurately forecast with 48 hours notice 67% of the time.   
      
Burbank
Riverside
Palm Springs
Indio
El Paso
Selma
Mission
1500 
 
  
1200 
 
 
 
  900 
 
 
 
  600 
 
 
 
  300 
 
 
 
      0 
µg
/m
3  
 Black = PM10 observed (AIRNow data); Red=PM10 (ED/eta Run 15a); Green=PM10 (ED/eta Run 20a) 
Dust Storm, 
January 4- 6, 
2007 
Dust Surveillance in the 
Southwest USA  
Investigators:  S. Morain, UNM; W. Sprigg, UA 
Daily 48-hour dust forecasts now available on a website 
(http://nmtracking.unm.edu) linked with the NM DoH EPHT web portal.  Data 
are then available to the national EPHTN.  Experimental dust advisories are 
now being issued at the request of the  Albuquerque Public Schools and the 
NM DoH. 
 
ENPHASYS Daily Average Dust 
Forecast >35µg/m3, April 2009 
Sample Advisories 
 
Southwest NM:  For April 6-8, 
expect moderate windblown 
dust late in the evening on the 
6th, dissipating gradually 
through the night but increasing 
and peaking in concentration 
between 12N and 3PM on the 
7th. There is a chance for 
moderate dust between 6 AM 
and 8 AM on the 8th 
Dust Surveillance in the 
Southwest USA  
15 
16 
17 
18 
19 
20 
Man ploughs the sea like a leviathan, he soars 
through the air like an eagle; his voice circles the 
world in a moment, his eyes pierce the heavens; 
he moves mountains, he makes the desert to 
bloom; he has planted his flag at the north pole 
and the south; yet millions of men each year are 
destroyed because they fail to outwit a mosquito. 
 
  -- Paul F. Russell, 1931 
Collaboration with DOD, USGS, USAID, and 
Columbia U. on Malaria 
Problem:  Malaria kills up to 3 million people yearly worldwide, many 
of whom are children. In addition, malaria costs African nations 
approximately $12 billion in economic productivity. The health 
and economic consequences of malaria make it a destabilizing 
phenomenon.  Accurate characterization of malaria risk is 
important because of its impact on US military and 
humanitarian personnel and operations. Global climate change 
may expand malaria risk areas to new locales, particularly 
higher altitudes. 
 
Solution:  NASA and DOD (through GSAT) and USGS, USAID, and 
Columbia U. (through MEWS)  are partners in utilizing 
environmental parameters such as precipitation, temperature, 
and vegetative cover to better characterize malaria 
transmission risks. 
 
NASA Research Results:  Model predictive capabilities and 
observations from NASA Earth-observing satellites such as 
Terra, Aqua, and TRMM. 
 
Status:  Current and future malaria risks have been forecast in a 
quantitative, dynamic, and accurate manner in Thailand, 
Afghanistan, and Indonesia.  Rolling 10-day rainfall anomaly 
products and 8-day Vectorial Capacity products are produced 
for Africa and these data are disseminated on the web as both 
graphic and GIS products (available at the ADDS website:  
http://earlywarning.usgs.gov/fews/africa/index.php).   
 
Precipitation is one of the main environmental 
determinants that promotes malaria transmission. 
The precipitation distribution in provincial resolution, 
based on NASA TRMM observations, is shown for 
the four Thailand season from 2000 to 2001. 
This image shows 
vegetation density 
(NDVI) over Africa in 
May 2008. By closely 
monitoring vegetation in 
regions affected by 
increased rainfall, 
scientists can identify 
areas at increased risk 
for outbreaks of malaria.  Investigators:  R. Kiang, M. Brown, NASA Goddard 
 
 
Left: NDVI anomalies for January  2010 are above normal in southern Africa. During December-February rainfall and NDVI were 
above normal indicating elevated risk of RVF activity for January and February. 
 
Right: Enhanced RVF risk map incorporating livestock, human population data, SRTM digital data, and NDVI resulting in a two-level 
risk category at regional scale. Confirmed February 2010 RVF outbreaks in South Africa are identified by circles. The advanced 
awareness on the developing RVF threat gave partners such as WHO and FAO the opportunity to plan and execute disease 
outbreak prevention, preparedness, and “control-and-response” actions, including advising farmers to vaccinate livestock.  Monthly 
risk maps available at: http://www.geis.fhp.osd.mil 
 
Investigator:  J. Pinzon, SSAI 
Collaboration with DOD on Rift Valley Fever in 
Africa 
Collaboration with Columbia U. on 
Meningitis in the African Sahel 
 
The project is exploring environmental 
and demographic risk factors as 
predictors for meningitis outbreaks in 
the African Sahel, particularly in Niger. 
 
The approach will take advantage of 
different sources of environmental 
information: in-situ data, model 
outputs and satellite observations 
(including those from the Multi-angle 
Imaging Spectroradiometer and 
TRMM). The latter are an important 
contribution in areas of sparse data 
coverage, poor real-time reporting, 
and limited access to reliable 
environmental information – such as 
the Sahel.  
 
A large plume of African dust  blows out over the 
Atlantic Ocean. This true color image of the dust event 
was acquired on February 11, 2002, by MODIS. 
Particles contained in dust clouds are suspected to be 
responsible for nasal irritations facilitating meningitis 
transmission in Africa. 
Investigator:  S. Trzaska, IRI/Columbia U. 
Neglected  dieseases in Latin America & Caribbean 
 
 Denge 
 Schistosomiasis 
 Dust induced Asmtha 
 soil-transmitted helminths  
 Chagas 
 TB 
Filariasis  
Fascioliasis  
Triatomines (Reduviidae: Triatominae) - spatial distribution 
Leishmaniasis 
Leprosy 
Hookworm    
 
  
 
 
 

World Health Organization 2006 
P. J. Hotez, M. E. Bottazzi, C. Franco-Paredes, S. K. Ault, and M. R. Periago. 2008 
The Neglected Tropical Diseases of Latin America and the Caribbean: A Review of Disease Burden and Distribution and a 
Roadmap for Control and Elimination. PLoS Negl Trop Dis. 2008 September; 2(9): e300. 
  
P. J. Hotez, M. E. Bottazzi, C. Franco-Paredes, S. K. Ault, and M. R. Periago. 2008 
The Neglected Tropical Diseases of Latin America and the Caribbean: A Review of Disease Burden and Distribution and a 
Roadmap for Control and Elimination. PLoS Negl Trop Dis. 2008 September; 2(9): e300. 
  
Strengths of satellite observations: 
 
 1. Measure environmental variables 
important to vector life cycles- ppt, soil moisture, 
temperature. 
 2. Land use/cover mapping 
 3. Ecological variables 
 4. large spacial coverage 
 5. Temperature 
Precipitation 
Relative humidity 
Wind 
Solar radiation 
Topography 
Fresh water rivers, ponds, lakes 
 
models 
Land Data Assimilation System (LDAS) that will be used to drive spatially-explicit ecological models of Anoph  
Precipitation from TRMM, and GPM 
Land Cover Type from MODIS, Landsat, ASTER, LDCM 
Soil Moisture from AMSR-E (where applicable) and SMAP 
Terrestrial Water Storage from GRACE and GRACE II 
Surface Temperature form MODIS, Landsat, ASTER, LDCM 
Vegetation Fraction/ Leaf Area Index from MODIS, Landsat, ASTER, LDCM 
Topography from SRTM 
 
Benjamin Zaitchik is also looking to better warn the public of health risks in his project, Development 
of a Detection and Early Warning System for Malaria Risk in the Amazon  
Land Data Assimilation System (LDAS)  
http://ldas.gsfc.nasa.gov/ 
MODIS (Terra & Aqua) 
 Environmental Tracking for Public Health 
Surveillance.  Stan Morain, Taylor & Francis 
Group/Balkema Press in summer, 2012 

HyspIRI Visible Shortwave Infrared 
(VSWIR) Science Measurements 
Science Questions: 
• What is the composition, function, and health of 
land and water ecosystems?   
• How are these ecosystems being altered by 
human activities and natural causes?   
• How do these changes affect fundamental 
ecosystem processes upon which life on Earth 
depends? 
 
Red tide algal bloom in Monterey Bay, CA 
Map of dominant tree species, Bartlett Forest, NH 
Imaging spectrometer: 55kg / 41W 
Schedule: 4 year phase A-D, 3 years operations 
All components have flown in space 
Measurement: 
• 380 to 2500 nm in 10nm channels 
• Accurate 60 m sampling 
• 19 days revisit  mapping mission 
• Global land and shallow water 
 
 
Aquatic Terrestrial 
36 
HyspIRI Thermal Infrared Multispectral 
(TIR) Science Measurements 
Science Questions: 
TQ1. Volcanoes/Earthquakes (MA,FF) 
– How can we help predict and mitigate earthquake and volcanic hazards through 
detection of transient thermal phenomena? 
• TQ2. Wildfires (LG,DR) 
– What is the impact of global biomass burning on the terrestrial biosphere and 
atmosphere, and how is this impact changing over time? 
• TQ3. Water Use and Availability, (MA,RA) 
– How is consumptive use of global freshwater supplies responding to changes in climate 
and demand, and what are the implications for sustainable management of water 
resources?  
• TQ4. Urbanization/Human Health, (DQ,GG) 
– How does urbanization affect the local, regional and global environment? Can we 
characterize this effect to help mitigate its impact on human health and welfare? 
• TQ5. Earth surface composition and change, (AP,JC) 
– What is the composition and temperature of the exposed surface of the Earth? How do 
these factors change over time and affect land use and habitability? 
Measurement: 
• 7 bands between 7.5-12 µm and 1 band  
at 4 µm 
• 60 m resolution, 5 days revisit   
• Global land and  shallow water 
 
 Volcanoes 
Urbanization 
Water Use and Availability 
Surface  
Temperature Evapotranspiration 
Andean volcano heats up  
0
0.1
0.2
0.3
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0.6
0.7
0.8
0.9
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3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00
Wavelength (um)
R
el
at
iv
e 
Sp
ec
tr
al
 R
es
po
ns
e
H1 (m21)
H2 (m28)
H3 (a10)
H4 (a11)
H5 (a12)
H6
H7
H8 (m32)
Multispectral Scanner: 60kg / 103W 
Schedule: 4 year phase A-D, 3 years 
operations 
High Heritage 
TIR 
HyspIRI Mission Concept - 2010 
Payload 
Science Instruments:  
• VSWIR: Imaging Spectrometer 
• 380-2500 nm in 10 nm bands 
• 60m spatial resolution 
• Day-side ( 23% duty cycle) 
• 55 Kg, 41 W 
• TIR: Thermal Infrared Scanner  
• 8 bands between 3-12 µm 
• 60m spatial resolution 
• Day and night-side (100% duty cycle) 
• 60 Kg, 103 W 
Intelligent Payload Module (IPM) 
• 24/7 Direct Broadcast capability 
• subset of science data 
• X-band @ 20 Mbps 
• 11 Kg, 86 W 
  
 Implementation 
Launch Date:  2014 - 2020 
Lifetime: 3 years, with consumables for 5 
Cost : Low to Moderate cost Mission 
Partners: JPL, GSFC 
Mission Class: C, with selected redundancy 
Hardware Model: Protoflight 
  
Mission Architecture 
• Orbit: 626 km Sun-Synchronous, 10:30am LTDN 
• Repeat: 19 day VSWIR / 5 day TIR 
• Downlink: Contacts nearly every orbit to Svalbard 
(North) and Troll (Antarctica) 
• Science Data: 5.7 Tbits/day 
• Launch Vehicle:  Taurus 3210, 2m fairing, 790 kg 
capability 
Spacecraft 
Launch Mass:  687 kg, JPL DP Margin: 30% 
Required Power: 680W, 7.1 m2 array (965 W capability) 
P/L Data Rate: 384 Mbps 
Downlink Data Rate: 800 Mbps Dual-pol X-band 
Stabilization: 3-axis 
Pointing: Control =720 arcsec (per axis 3σ) 
           Knowledge = 5.6 arcsec (Pitch/Roll axis 3σ);  
                                         15 arcsec (Yaw axis 3σ) 
           Stability = 5 arcsec/sec (per axis 3σ) 
 
 
MODIS Data Sources 
  
 
       Atmosphere   http://modis-atmos.gsfc.nasa.gov/ 
        Land 
                http://edcdaac.usgs.gov/dataproducts.asp & http://modis-land.gsfc.nasa.gov/ 
         Ocean 
                http://oceancolor.gsfc.nasa.gov 
 
 
Landsat Data Products 
 
               http://landsat.usgs.gov/products_productinformation.php/ 
 
 
 
 
 
 
SERVIR  
Regional Platform for Science and Policy  
in the Americas, Africa, and Asia 
Using earth observations and predictive models for 
environmental management, disaster response, and 
climate change adaptation.  
• Data and Models 
• Online Maps 
• Visualizations 
• Decision Support 
• Training 
• Partnerships 
Tracking Fires in Guatemala Mexico 
Training and Capacity Building 
Flood Forecasting in Africa 
.gov/ph 
 
.gov/rs 
 
.org 
 
.edu 
 
 
.int 
 
.mil 
NASA’s Public Health Partners 
Future Observations for Health – Near 
Term 
• NPOESS Preparatory Mission (NPP)  --  2011  
– NPP will serve as a bridge mission between the NASA Earth-
observing research satellites Terra, Aura, and Aqua and the 
operational Joint Polar Satellite System (JPSS) constellation. 
 
• Landsat Data Continuity Mission (LDCM)  --  2012 
 
• Global Precipitation Mission (GPM) – 2013 
– Will provide accurate observations of the intensity and 
distribution of global precipitation. GPM builds on the heritage of 
the TRMM mission and is in partnership with JAXA. 
 
 
• Hyperspectral Infrared Imager (HyspIRI) –  2020s 
– HyspIRI will employ a hyperspectral imager and a thermal 
infrared scanner to monitor a variety of ecological and 
geological features at a wide range of wavelengths, including 
data on changes in vegetation type and deforestation for 
ecosystem management . 
 
• Soil Moisture Active Passive (SMAP) – 2014 
• SMAP will use a combined radiometer and high-resolution 
radar to measure surface soil moisture and freeze-thaw state. 
 
Future Observations for Health – 
Decadal Survey 
Aqua 
Terra 
Aura 
Aquarius 
SORCE TRMM 
Landsat-7 
ACRIMSAT 
Jason 
OSTM/Jason 2 
2011 
NPP 
GRACE 
CloudSat 
EO-1 
CALIPSO 
QuikSCAT 
Aqua 
Terra 
Aura 
SORCE TRMM 
Jason 
OSTM/Jason 2 
2012 
Aquarius 
Landsat-7 
NPP 
GRACE 
CloudSat 
CALIPSO 
LDCM 
Aqua 
Terra 
Aura 
SORCE TRMM 
OSTM/Jason 2 
2013 
NPP 
LDCM 
Aquarius 
Landsat-7 
CloudSat 
CALIPSO 
GPM  
OCO-2 
Aqua 
SORCE 
OSTM/Jason 2 
2014 
NPP 
GPM  
Aquarius 
LDCM 
SMAP 
Landsat-7 
OCO-2 
Applied Sciences Program 
http://appliedsciences.nasa.gov 
http://weather.msfc.nasa.gov/conference/phconference_home_sa.html 
 
 
National Aeronautics and 
Space Administration 
 
Earth Science Enterprise 
Applications Plan 
April 2004 
Epidemiology in the 21st Century 


NASA's Public Health Program: How We Can Use NASA Satellite Data To Study Global Public Health Issues

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