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Moderate-Resolution Imaging Spectroradiometer

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Title: Moderate-Resolution Imaging Spectroradiometer  
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Subject: Black Saturday bushfires, Infobox body of water/testcases, Ocean color, 2009 Australian dust storm, Arctic
Collection: Earth Observation Satellites, Satellite Meteorology and Remote Sensing, Spacecraft Instruments
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Moderate-Resolution Imaging Spectroradiometer

Ash plumes on Kamchatka Peninsula, eastern Russia.
Hurricane Katrina near Florida peninsula.
California wildfires.
Solar irradiance spectrum and MODIS bands.
External view of the MODIS unit.
Exploded view of the MODIS subsystems.
Detailed, photo-like view of Earth is based largely on observations from MODIS.

The Moderate-resolution Imaging Spectroradiometer (MODIS) is a payload scientific instrument built by Santa Barbara Remote Sensing[1] that was launched into Earth orbit by NASA in 1999 on board the Terra (EOS AM) Satellite, and in 2002 on board the Aqua (EOS PM) satellite. The instruments capture data in 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). Together the instruments image the entire Earth every 1 to 2 days. They are designed to provide measurements in large-scale global dynamics including changes in Earth's cloud cover, radiation budget and processes occurring in the oceans, on land, and in the lower atmosphere. MODIS utilizes four on-board calibrators in addition to the space view in order to provide in-flight calibration: Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), Spectral Radiometric Calibration Assembly (SRCA), and a v-groove black body.[2] MODIS has used the Marine Optical Buoy for vicarious calibration. MODIS is succeeded by the VIIRS instrument on board the Suomi NPP satellite launched in 2011 and future Joint Polar Satellite System (JPSS) satellites.

The MODIS Characterization Support Team (MCST) is dedicated to the production of high quality MODIS calibrated product which is a precursor to every geophysical science product. A detailed description of the MCST mission statement and other details can be found at MCST Web.[3]


  • Applications 1
  • Specifications 2
  • MODIS Bands 3
  • MODIS data 4
    • MODIS Level 3 datasets 4.1
    • Availability 4.2
  • See also 5
  • References 6
  • External links 7


With its low spatial resolution but high temporal resolution, MODIS data is useful to track changes in the landscape over time. Examples of such applications are the monitoring of vegetation health by means of time-series analyses with vegetation indices,[4] long term land cover changes (e.g. to monitor deforestation rates),[5][6][7][8] global snow cover trends,[9][10] water inundation from pluvial, riverine, or sea level rise flooding in coastal areas,[11] change of water levels of major lakes such as the Aral Sea,[12][13] and the detection and mapping of wildland fires in the United States. The United States Forest Service's Remote Sensing Applications Center analyzes MODIS imagery on a continuous basis to provide information for the management and suppression of wildfires.[14]


Orbit 705 km, 10:30 a.m. descending node (Terra) or 1:30 p.m. ascending node (Aqua), sun-synchronous, near-polar, circular
Scan Rate 20.3 rpm, cross track
Swath 2330 km (cross track) by 10 km (along track at nadir)
Telescope 17.78 cm diam. off-axis, afocal (collimated), with intermediate field stop
Size 1.0 x 1.6 x 1.0 m
Weight 228.7 kg
Power 162.5 W (single orbit average)
Data Rate 10.6 Mbit/s (peak daytime); 6.1 Mbit/s (orbital average)
Quantization 12 bits
Spatial Resolution 250 m (bands 1–2) 500 m (bands 3–7) 1000 m (bands 8–36)
Design Life 6 years


Band Wavelength
Primary Use
1 620–670 250 Land/Cloud/Aerosols
2 841–876 250
3 459–479 500 Land/Cloud/Aerosols
4 545–565 500
5 1230–1250 500
6 1628–1652 500
7 2105–2155 500
8 405–420 1000 Ocean Color/
9 438–448 1000
10 483–493 1000
11 526–536 1000
12 546–556 1000
13 662–672 1000
14 673–683 1000
15 743–753 1000
16 862–877 1000
17 890–920 1000 Atmospheric
Water Vapor
18 931–941 1000
19 915–965 1000
Band Wavelength
Primary Use
20 3.660–3.840 1000 Surface/Cloud
21 3.929–3.989 1000
22 3.929–3.989 1000
23 4.020–4.080 1000
24 4.433–4.498 1000 Atmospheric
25 4.482–4.549 1000
26 1.360–1.390 1000 Cirrus Clouds
Water Vapor
27 6.535–6.895 1000
28 7.175–7.475 1000
29 8.400–8.700 1000 Cloud Properties
30 9.580–9.880 1000 Ozone
31 10.780–11.280 1000 Surface/Cloud
32 11.770–12.270 1000
33 13.185–13.485 1000 Cloud Top
34 13.485–13.785 1000
35 13.785–14.085 1000
36 14.085–14.385 1000

MODIS data

MODIS Level 3 datasets

The following MODIS Level 3 (L3) datasets are available from NASA, as processed by the Collection 5 software.[15]

Daily 8-day 16-day 32-day Monthly Yearly Grid Platform Description
MxD08_D3 MxD08_E3 MxD08_M3 1° CMG Terra, Aqua Aerosol, Cloud Water Vapor, Ozone
MxD10A1 MxD10A2 500 m SIN Terra, Aqua Snow Cover
MxD11A1 MxD11A2 1000 m SIN Terra, Aqua Land Surface Temperature/Emissivity
MxD11B1 6000 m SIN Terra, Aqua Land Surface Temperature/Emissivity
MxD11C1 MxD11C2 MxD11C3 0.05° CMG Terra, Aqua Land Surface Temperature/Emissivity
MxD13C1 MxD13C2 0.05° CMG Terra, Aqua Vegetation Indices
MxD14A1 MxD14A2 1000 m SIN Terra, Aqua Thermal Anomalies, Fire
MCD45A1 500 m SIN Terra+Aqua Burned Area
250 m SIN 500 m SIN 1000 m SIN 0.05° CMG 1° CMG Time window Platform Description
MxD09Q1 MxD09A1 8-day Terra, Aqua Surface Reflectance
MxD09CMG Daily Terra, Aqua Surface Reflectance
MCD12Q1 MCD12C1 Yearly Terra+Aqua Land Cover Type
MCD12Q2 Yearly Terra+Aqua Land Cover Dynamics

(Global Vegetation Phenology)

MxD13Q1 MxD13A1 MxD13A2 MxD13C1 16-day Terra, Aqua Vegetation Indices
MxD13A3 MxD13C2 Monthly Terra, Aqua Vegetation Indices
MCD43A1 MCD43B1 MCD43C1 16-day Terra+Aqua BRDF/Albedo Model Parameters
MCD43A3 MCD43B3 MCD43C3 16-day Terra+Aqua Albedo
MCD43A4 MCD43B4 MCD43C4 16-day Terra+Aqua Nadir BRDF-Adjusted Reflectance


Raw MODIS data stream could be received in real-time using a tracking antenna, thanks to the instrument's direct broadcast capability.[16]

Alternatively, the scientific data is made available to the public via several World Wide Web sites and FTP archives, such as:

  • ECHO Reverb – the next generation metadata and service discovery tool,[17] which has replaced the former Warehouse Inventory and Search Tool (WIST);
  • LAADS Web – Level 1 and Atmosphere Archive and Distribution System (LAADS) web interface;
  • LANCE-MODIS – Land Atmosphere Near real-time Capability for EOS[18]
  • – LAADS underlying FTP server;
  • – Earth land surface datasets;
  • – snow and ice datasets.

Most of the data is available in the HDF-EOS format — a variant of Hierarchical Data Format prescribed for the data derived from Earth Observing System missions.[19]

Image based on observations from MODIS.

See also


  1. ^ NASA Website "MODIS Components"] . Retrieved 11 Aug 2015. 
  2. ^ NASA Website "MODIS Design"] . Retrieved 11 Aug 2015. 
  3. ^ MCST Web "MODIS Characterization Support Team"] . Retrieved 18 Jul 2015. 
  4. ^ LU, L., KUENZER, C., WANG, C., GUO, H., Li, Q., 2015: Evaluation of three MODIS-derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring. Remote Sensing, 2015, 7, 7597-7614; doi:10.3390/rs70607597
  5. ^ LEINENKUGEL; P., WOLTERS, M., OPPELT, N., KUENZER, C., 2014: Tree cover and forest cover dynamics in the Mekong Basin from 2001 to 2011. Remote Sensing of Environment, Vol. 158, 376–392
  6. ^ KLEIN, I., GESSNER, U. and C. KUENZER, 2012: Regional land cover mapping in Central Asia using MODIS time series. Applied Geography 35, 1-16
  7. ^ LU, L., KUENZER, C., GUO, H., Li, Q., LONG, T., LI, X., 2014: A Novel Land Cover Classification Map Based on MODIS Time-series in Xinjiang, China. Remote Sensing, 6, 3387-3408; doi:10.3390/rs6043387
  8. ^ GESSNER, U.; MACHWITZ, M.; ESCH, T.; TILLACK, A.; NAEIMI, V.; KUENZER, C.; DECH, S. (2015): Multi-sensor mapping of West African land cover using MODIS, ASAR and TanDEM-X/TerraSAR-X data. Remote Sensing of Environment. 282-297
  9. ^ DIETZ, A., KUENZER, C., and C. CONRAD, 2013: Snow cover variability in Central Asia between 2000 and 2011 derived from improved MODIS daily snow cover products. International Journal of Remote Sensing 34 (11), 3879-3902
  10. ^ DIETZ, A., WOHNER, C., and C. KUENZER, 2012: European snow cover characteristics between 2000 and 2011 derived from improved MODIS daily snow cover products. Remote Sensing, 4, 2432-2454, doi:10.3390/rs4082432
  11. ^ KUENZER, C, KLEIN, I., ULLMANN; T., FOUFOULA-GEORGIOU, E., BAUMHAUER, R., DECH, S., 2015: Remote Sensing of River Delta Inundation: exploiting the Potential of coarse spatial Resolution, temporally-dense MODIS Time Series. Remote Sensing, 7, 8516-8542
  12. ^ KLEIN, I., DIETZ, A., GESSNER, U., DECH, S., KUENZER, C., 2015: Results of the Global WaterPack: a novel product to assess inland water body dynamics on a daily basis. Remote Sensing Letters, Vol. 6, No. 1, 78-87
  13. ^ "Shrinking Aral Sea."NASA Earth Observatory. Retrieved: 30 September 2014.
  14. ^ "MODIS Active Fire Mapping Program FAQs." United States Forest Service. Retrieved: 30 September 2014.
  15. ^ "MODIS Products Table". Retrieved 2011-06-12. 
  16. ^ "Direct Broadcast at MODIS Website". Retrieved 2009-06-02. 
  17. ^ "About Reverb". Retrieved 2011-11-07. 
  18. ^ "LANCE-MODIS". NASA Goddard Space Flight Center. Retrieved 2014-09-15. 
  19. ^ "HDF-EOS Tools and Information Center". Retrieved 2009-06-02. 

External links

  • Official NASA site
  • MODIS bands and spectral ranges (broken link)
  • MODIS Images of the Day
  • MODIS Image of the Day - Google Gadget referring to MODIS image of the day.
  • Gallery of Images of Interest
  • MODIS Land Product Subsetting Tool for North America from Oak Ridge National Laboratory
  • MODIS Rapid Response system (near real time images)
  • NASA OnEarth (Web service for MODIS imagery)
  • Visible Earth: Latest MODIS images
  • MODIS Sinusoidal: Projection 6842 - MODIS Sinusoidal
  • Python: accessing near real-time MODIS images and fire data from NASA’s Aqua and Terra satellites (Python)
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