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Remote Sensing Data Currently Available for Vector-borne Disease Modeling Penny Masuoka Uniformed Services University NASA Goddard Space Flight Center Katalin Kovacs Science Systems and Applications I NASA Goddard Space Flight Center

Remote Sensing Data Currently Available for Vector-borne Disease Modeling Penny Masuoka Uniformed Services University NASA Goddard Space Flight Center

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Remote Sensing Data Currently Available for Vector-borne

Disease Modeling

Penny MasuokaUniformed Services UniversityNASA Goddard Space Flight Center

Katalin KovacsScience Systems and Applications Inc.NASA Goddard Space Flight Center

Overview of Presentation

Multispectral Imagery – what’s available and what to order

Data Products- Weather Products- Vegetation Indices- Digital Elevation Models- Land Cover

Example Imagery and Data Products: MODIS

• Low resolutionGreater than 200 meter pixelsCountry or continental scale studies

• Medium resolution10 – 100 meter pixelsRegional studies

• High resolutionLess than 10 meter pixelsLocal studies

Which Images to Use?

Low Resolution - MODIS Image of Nile Delta - 1 km pixels

Pyramids

Medium Resolution

Cairo, Egypt

Subset ofLandsat Thematic MapperFalse Color IR

30 meter pixels

High Resolution

IKONOS image of the pyramids

1 meter pixels

The Resolution Trade Off

As spatial resolution increases:

• Spectral resolution (number of bands) decreases

• File size increases

• Cost increases

Lesson: Use the lowest resolution data that will get the job done.

How do you decide which resolution?

Example: Estimating Mosquito Habitat Area in Korea

Landsat – 30 meter pixelsLandsat – 30 meter pixelsIKONOS – 4 m pixelsIKONOS – 4 m pixels

Estimate of Habitat Area:5,712,291 m2

Estimate of Habitat Area:5,909,175 m2

Source: David Claborn and Penny Masuoka

Either Landsat or IKONOS images could be used to estimatemosquito habitat in Korea, but to cover a 100 by 100 km. area:

Sensor Cost

Landsat ETM+ $600 ($600 per 185 x 185 km. scene)

IKONOS $403,000 ($40.30 per sq. km.*)

*Price varies depending on location. ($27 per sq. km. in Central America)

DoD buyers must purchase through the National Geospatial-IntelligenceAgency (www.nga.mil) and cost may be higher, but any imagery that they already have is free.

Current High Resolution Multispectral SensorsSatellite Bands Resolution To Order

IKONOS Blue, Green, Red, NIR,

Pan

4 m. (multi)

1 m. (Pan)

www.spaceimaging.com

QuickBird 2 Blue, Green, Red, NIR, Pan

2.44-2.88 m. (multi)

61-72 cm. (Pan)

www.digitalglobe.com

Orbview 3 Blue, Green, Red, NIR,

Pan

4 m. (multi)

1 m. (Pan)

Still in check-out phase.

Products will be available from www.orbimage.com.

SPOT 5

HRV-IR

Green, Red, NIR, MIR

5 m. (pan)

10 m (multi)

20 m (MIR)

www.spot.com

A Few Current Medium Resolution Multispectral SensorsSatellite Bands Resolution To Order

Landsat

Enhanced Thematic Mapper +

7 multispectral,

Pan

30-60 m (multi)

15 m (Pan)

http://edcsns17.cr.usgs.gov/EarthExplorer/

EO-1

Advanced Land Imager

9 multispectral,

Pan

30 m (multi)

10 m (Pan)

http://edcsns17.cr.usgs.gov/EarthExplorer/

SPOT-4 Green, Red, NIR, MIR, Pan

20 m. (multi)

10 m. (Pan)

www.spot.com

Terra ASTER Green, Red, NIR, 6 SWIR , 5 TIR

15-90 meters

http://redhook.gsfc.nasa.gov/imswww/pub/imswelcome/index.html

IRS-P6 LISS3

Green, Red, NIR, MIR

24 meters http://www.spaceimaging.com/products/irs/index.htm

A Few Current Low Resolution Multispectral Sensors

Satellite Bands Resolution To Order

Terra MODIS Aqua MODIS

36 bands 250–1000 m http://redhook.gsfc.nasa.gov/imswww/pub/imswelcome/index.html

SPOT 4 and 5

Vegetation

Blue, Green, Red, NIR, MIR

1000 m www.spot.com

ENVISAT-1

AATSR

Green, Red, NIR, SWIR, 3 TIR

1000 meters http://envisat.esa.int/dataproducts/availability/

NOAA AVHRR Red, NIR, 3 TIR

1100 meters http://edcdaac.usgs.gov/1KM/1kmhomepage.html or http://edcsns17.cr.usgs.gov/EarthExplorer/

What we didn’t cover:RadarFuture SatellitesOthers: BILSAT,CBERS CCD, CBERS IR-MSS, CBERS WFI, ENVISAT MERIS, EROS A, ERS ATSR, IRS MOS, IRS WiFS, IRS OCM, Priroda/Mir MOMS, Priroda/Mir MSU-SK, Resurs OI N2 MSU-SK, etc.

Find out more about these and others on this NASA website:

http://geo.arc.nasa.gov/sge/health/sensor/sensor.html

Data Products Derived from Remote Sensing Data:

Weather Products (Precipitation, Temperature, Humidity)

Vegetation Indices

Digital Elevation Models

Land Cover

Weather Products

Uses: Can monitor conditions that affect vector-borne disease outbreaks.

Source:NCEP/NCAR Reanalysis data (derived from ground stations, satellite data and weather models):http://www.cdc.noaa.gov/cdc/reanalysis/reanalysis.shtml

Total precipitation January - March. Total precipitation July - September. Average temperature January - March. Average temperature July - September.

Source: Andrew Au, NASA

Vegetation IndicesUses: A high vegetation index indicates wet conditions that can be associated with a disease outbreak (such as Rift Valley Fever). Sources:MODIS vegetation indices:http://redhook.gsfc.nasa.gov/imswww/pub/imswelcome/index.htmlAVHRR Normalized Difference Vegetation Index (NDVI):http://edcdaac.usgs.gov/1KM/comp10d.html

Digital Elevation Models (DEM)

Uses:Elevation can be a limiting factor in the location of a disease.

Sources:NASA Shuttle Radar Topography Missionhttp://srtm.usgs.gov/index.html

GTOPO30http://edcdaac.usgs.gov/gtopo30/gtopo30.html

Global Land One-Kilometer Base Elevation (GLOBE)http://www.ngdc.noaa.gov/seg/topo/globe.shtml

Low High

Land Cover

Uses:

Land cover maps can be used to define vector habitat areas.

Source:

http://LPDAAC.usgs.gov/glcc/globe_int.html

Land cover map

Bartonellosis occurs in agricultural areas at elevations between 1800 and 3400 meters.

Weather data could be added to this model to decide when and where to spray pesticides.

Elevation Land Cover Areas at Risk for Bartonellosis

Example of Using Data Products: Bartonellosis in Peru

• MODerate-resolution Imaging Spectroradiometer – Spatial resolution: 250m (2 bands), 500m (5 bands), 1km (29 bands)– 36 spectral bands (Visible-IR)– Is on Terra and Aqua spacecraft– 40 science products with daily volume of 880GB per instrument– Available for free on the internet

Example: MODIS

MODIS Products

MODIS

OceanLand

Atmosphere

Products:MOD36 Ocean ColorMOD28 SST…

Products:MOD04 AerosolsMOD05 Water VaporMOD06 CloudMOD35 Cloud Mas…

Products:MOD09 ReflectanceMOD12 Snow CoverMOD13 VegetationMOD14 Thermal Anomaly

To learn more go to: http://modis.gsfc.nasa.gov/

MOD09 image

                                          

                                     

Smoke over the Eastern US

Source: http://modis.gsfc.nasa.gov/

MODIS Data products come in different

Spatial Resolution

250 m500 m1000 m4 km5 km5 min0.05 deg0.25 degEtc…

Temporal Resolution Versions

daily8-day composites16-day composites96-day compositesEtc…

Version3 v003Version4 v004

To learn more go to: http://modis.gsfc.nasa.gov/data/dataproducts.html

~But most products do NOT come with all these resolutions and versions~

… and Each MODIS Data product has several data layers

(some have 2 and some have 13 or more)

For Example the MOD13 500m product has 11 bands:1 500m 16-day NDVI2 500m 16-day EVI3 500m 16-day NDVI Quality4 500m 16-day EVI Quality5 500m 16-day Red Reflectance6 500m 16-day NIR Reflectance7 500m 16-day Blue Reflectance8 500m 16-day MIR Reflectance9 500m 16-day average view zenith angle10 500m 16-day average sun zenith angle11 500m 16-day average relative azimuth angle

What’s in a Name?

MOD13A1.A2003161.h11v05.004.2003183014032.hdf

Product short nameSpatial Resolution (in general)

A2=1kmA1=500mQ1=250m

Acquisition date year day of year formatSIN tile location horizontal and verticalversion

Hi! I’m Bob.

Terra MODIS product

names start with MODAqua MODIS product

names start with MYD

What are SIN and ISIN GRIDs?

MODLAND Val. – Jan. 22, 2001 4

ISIN GridISIN Grid

10 degree Tiles

Grid Cell Sizes:30 arcsec (0.93 km)15 arcsec (0.46 km)7.5 arcsec (0.23 km)

Source: Robert Wolfe

To order data go to:http://redhook.gsfc.nasa.gov/imswww/pub/imswelcome/index.html

To learn how to order data:http://redhook.gsfc.nasa.gov/~imswww/Tutorial/main.html

Confused?Confused?

Data products

Data products

Data Sets

Data Granules

Data Granules

Tiles

SIN

ISIN BinsBins

Try the Frequently Asked Questions Page: http://redhook.gsfc.nasa.gov/~imswww/3.5/imswelcome/imswww.faq.html

Layers

LayersBandsv003

v004

sear

ch

sear

ch

order

Once you find the data, you will need to

Free HDF tools: http://daac.gsfc.nasa.gov/MODIS/software.shtmlFree Projection tool: http://edcdaac.usgs.gov/tools/modis/

• Get it on your computer use FTP or read it in from media (8mm tape, CD, DVD)

• View it use a free HDF tool or an image processing software

• Reproject it use the free MODIS Reprojection Tool or GIS software

At this point you may be saying:

Help!!!I don’t know how to process

remote sensing data!

NASA may be able to help…

Example Customized MODIS Products for Federal Agencies: MODIS Rapid Response System

History– Summer 2000, MODIS images used by US Forest Service in

fighting fires in Montana/Idaho– 2001 Rapid Response system produced automated, near real

time MODIS images for monitoring fires and other natural hazards – Products are posted on the web within 3-6 hours from acquisition

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

Applications and Customers– US Forest Service - active fire locations– USDA Foreign Agricultural Service – monitoring crop stress and

drought– Department of Defense – mission planning/monitoring weather

and dust in Afghanistan and Iraq– Environmental Protection Agency – monitoring hazardous

material sites, Iraq war (smoke)

Example MODIS Rapid Response Product

                                          

                                     

Fires in Australia

Source: http://earthobservatory.nasa.gov/Study/Sentinel/

Feb 4, 2003

Discussion

There are many remote sensing images and products currently available.

Use of the images/products requires a great deal of expertise.

Partnerships between remote sensing scientists, modelers, entomologists, etc. will be necessary to create effective decision support systems for disease prevention.

Thanks to the following people for helpful suggestions on this talk:

Robert Venezia

Timi Vann

Brian Zeichner

Richard Wells