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Frequently Asked Questions

Dark Target and Deep Blue

How is the surface reflectance in the Dark Target and Deep Blue products calculated and why are their reported values different?
Refelctance for the Dark Target product is reported in reflectance “units” using the following forumal 
R = (L / F0) * (pi / mu0), 
 where L is the radiance at the top of the atmosphere, F0 is the solar irradiance constant (for the given wavelength * distance to sun, etc), and mu0 is cosine of solar zenith angle. 
However, different instrument teams (MODIS, VIIRS, SeaWIFS) have chosen to report Level 1B “reflectance” in different forms.
In the case of MODIS, the reflectance aquired from the Level 1B product (L1B) is
R = (L / F0) * PI,  so if you want true “reflectance” you have to divide by mu0. 
At the same time, different retrieval teams (e.g. DT, DB) have chosen to do retrievals in different space. 
For Dark Target, we do our retrieval in terms of true reflectance units, so our reported “Mean_Reflectance_Land” SDSs have the 1 / mu0 applied.
The 6S atmospheric correction can be applied directly to these values. 
Deep Blue works in L/F0 space.  So, if you want “reflectance”, you have to apply the (pi/ mu0) to the “Deep_Blue_Spectral_TOA_Reflectance_Land”
In summary, if you want to do atmospheric correction from the data in the Level 2 file, 
    1) For DT:  Use what is reported. 
    2) For DB: Multiply by (PI/mu0).
What are the differences in cloud screening between the Dark Target and Deep Blue algorithms and why is the screening different?

The cloud screening procedures for the two products use similar principles but different tests due in part to different bands used in the retrieval algorithms and different pixel resolutions used in algorithms. Really 'cloud mask' is not 100% correct as a term, they are more like a 'suitable pixel mask', and both algorithms have different requirements for pixel type (e.g. Dark Target has  a surface brightness criterion).

The use of quality assurance (QA) flags as part of the logic for the merged dark target – deep blue product implies that both DT and DB agree on the quantitative meaning of their QA assignments (e.g., a value of 2 vs. 3). Can you comment?

Dark Target and Deep Blue quality assurance tests and definitions are independent and unrelated, and it is coincidental that they use the same (0-3) scale. Follow individual group recommendations for their products, or better yet, use only the prefiltered scientific data sets (SDSs).

What are the main reasons that the dark target and deep blue products are not well correlated over the Western US and Australia?

One reason is that AOD is normally low in these areas so AOD variability is similar in size to the retrieval error.  Another reason is that these areas may have bright surfaces and/or atypically colored soils which the two products will retrieve differently.



What is the dark target/deep blue merged product?

The merged product is a single SDS (AOD_550_Dark_Target_Deep_Blue_Combined) comprised of only high quality dark target (QA=3 over land, QA > 0 over ocean) and deep blue (QA 2 & 3) data to produce a global 10 Km product. Over ocean this product uses only dark target retrievals. Over land, monthly NDVI maps are used to assign which retrieval will fill the merged SDS. Over bright surfaces (NDVI < 0.2) the deep blue value is selected. Over dark vegetated surfaces (NDVI > 0.3) the dark target value is selected. In the range of (0.2 < NDVI <0.3), land if only one of the two algorithms produces a high QA value, that value is used in the product. If both retrievals produce a high QA value, the dark target and deep blue values will be averaged.

The advantage of the merged product is its ease of use to obtain the greatest global coverage of AOD. 

There are two potential risks in using this product:

1) The values where dark target and deep blue are averaged may be less accurate than either the deep blue or dark target areas.

2) The default assumptions that dark target will always be the superior product where NDVI > 0.3 and that deep blue will always be the superior product where NDVI < 0.2 may not always hold true.

How do I know when to use dark target or deep blue?

For advanced users it is best to know the details of the validation of each product and the locations and seasons where each product has the best performance. Additional information can be found here:

Please also refer to our page of validation maps:   It is suggested you use the links to the full sized maps on this page.

For less advanced users there is a merged dark target – deep blue product in Collection 6 (currently available for Aqua only). The name of the SDS is AOD_550_Dark_Target_Deep_Blue_Combined. Please see the answer to “What is the merged product?” for additional information.

What is the difference between dark target and deep blue?

This is a big question and we can only provide very general answers in this FAQ format.

Dark target has separate algorithms for land and ocean.  Deep blue in the MODIS aerosol products is a land retrieval only. All total column aerosol retrieval algorithms must account for and remove the surface reflectance signal to accurately determine the aerosol signal. Dark target and deep blue retrievals have different ways of accounting for the reflectance signal coming from the land surface.

Dark target uses a set of ratios and relationships between the 0.47, 0.67 and 2.1 µm channels to account for the surface signal.  This method works best over dark vegetated targets and does not work over bright land surfaces.

Deep blue uses maps and libraries of surface reflectance in the blue channels to account for the surface signal as well as spectral reflectance ratios.  This method works best over bright land surfaces but can also retrieve aerosols over most vegetated targets.

Additional differences between dark target and deep blue are:

1. Cloud masking methodology.

2. Dark target uses 500 M pixels in its retrieval algorithm.  Deep blue uses 1 Km pixels in its retrieval algorithm.

3.  In collection 6 dark target has a 3 Km and a 10 Km product.  Deep blue has only the 10 Km product.

Additional information from published papers on the dark target retrieval can be found in our reference section.

For more information on the deep blue retrieval please see the following references:

Retrieval and Algorithm Questions

How do you screen for clouds?

The cloud screening in the MODIS dark target aerosol algorithm is a series of internal and external tests, and is different over land and ocean. The details of the cloud masking scheme is described in section A2.2 of the ATBD. The Collection 6 aerosol products contain a new SDS called “Aerosol_Cldmask_Land_Ocean” which characterizes each 500 m input pixels as “clear” or “cloudy”

AOD over cities seems to have some problems. Why is that?

The MODIS Dark Target algorithm uses a set of ratios and relationships between the 0.47, 0.67 and 2.1 µm channels to account for the surface signal.

These relationships begin to break down over the brighter surfaces of urban areas.   Improving the product over cities is an active area of research.  Please contact us if you would like more information.



Why can’t the dark target algorithm retrieve data over bright surfaces?

The dark target retrieval algorithm assumes that aerosols over a surface will brighten the scene.  Where the surface is too bright this assumption breaks down. 

Tags: Retrieval

Product Details and Availability

How do I find images/products, for a particular location and date?

NASA’s ARSET site has a very nice overview of imagery and a summary table/chart of where to obtain images.  You can find that information here: 

ARSET Satellite Imagery.   You can also find some informaiton on our site in the links page under "Imagery Links"

To find products please see the FAQ question “How do I find MODIS products?”

Tags: Data
How can I tell if the aerosols being observed are dust or smoke?

Currently there is no definitive test or product parameter available to conclude that the MODIS aerosol product is measuring dust or smoke.  Over ocean a low fine mode fraction is a strong indicator of dust but is not definitive.  Often ancillary information must be included to try to make this determination.  This ancillary information can include: AERONET data, AIRS dust product (over ocean), MISR data, OMI aerosol index, VIIRS suspended matter product, back trajectories which link to a dust or smoke origin.

Why can’t I find fine mode AOD or Angstrom Exponent over land in collection 6?

This product is not accurate over land and the MODIS aerosol group decided not to include it in collection 6.  You can find it in the collection 5 products but we only recommend it for use as a very general qualitative indicator.

What is aerosol fine mode fraction?

Atmospheric aerosols generally have a bimodal distribution.  The smaller particles are referred to as the fine mode or accumulation mode aerosols. These particles have radii between 0.1 and 0.25 microns. The larger particles comprise the coarse mode. These particles generally have radii between 1.0 and 2.5 microns.  The aerosol fine mode fraction is the proportion of fine mode aerosols to the total. This is an optical measurement of the proportion by volume.

What is the difference between level 2 and level 3 data?

Level 2 data are Geophysical parameter data.  For MODIS this is distributed in 5 minute pieces referred to as granules. Level 3 processing produces Earth-gridded geophysical parameter data, which have been averaged, gridded, or otherwise rectified or composited in time and space. For more information on the overall structure of MODIS files please see the FAQ on the Ladsweb site.

Tags: Data
What is the difference between “best” and “average” ocean products?

The ocean algorithm attempts to match calculated reflectances to measured reflectances. To do this the ocean algorithm selects all combinations of the four fine mode and five coarse mode aerosol models and varies the amount of each to find solutions within pre-defined error limits.  All solutions within the error limits are used to calculate an “average” value.  The solution with the lowest error is used for the “best” value.  We recommend that users select the “average” value for ocean products.

For an additional explanation of this process please see the “Dark Target Ocean Algorithm” presentation in our educational and reference material section.

What is the difference between “Optical_Depth_Land_And_Ocean” and “Image_Optical_Depth_Land_And_Ocean”?

Both of these variables are merged land and ocean AOD at 0.55 µm from the dark target algorithms. The “Optical_Depth_Land_And_Ocean” SDS only contains high quality pixels (QA=3 over land, QA > 0 over ocean). The “Image_Optical_Depth_Land_And_Ocean” SDS contains all valid (non-fill) pixels; this product can be used to trace aerosol plumes and make aerosol maps, but should not be used for quantitative study.

How do I read MODIS data?

MODIS data is in HDF 4 format.  HDF files contain both data and metadata so there is no need to download separate data and data location files.  Most programming languages and software programs will have the capability to read MODIS HDF files.

A Tutorial for reading HDF4 files in python, C, FORTRAN, IDL, and Matlab are available here from Lille University.

Tags: Data
How are MODIS files named?

MODIS Aerosol HDF file names have this naming convention:



YYYY, DDD and HHMM are four digit year, three digit Julian day, and time of day in UTC, CCC is the collection (005 for Collection 5, 051 for Collection 5.1 and 006 for Collection 6), and YEARDAYHRMNSC represents when the file was processed.

The MOD04 and MYD04 files include many parameters, each stored as a Scientific Data Set (SDS) within the file.

Tags: Data
What is the best way for me to get files if I need a large data set?

The ladsweb FAQ provides a tremendous amount of information about MODIS files, file structure etc. including several methods to obtain large numbers of files.

Tags: Data
Where can I get MODIS data?

MODIS data for atmospheric products is available from several NASA websites. The primary location is the ladsweb site

Within ladsweb there are several ways to access the files depending on your needs.  A sample exercise that will guide you through most of these is available on our educational and reference materials page.

More advanced users may wish to use the FTP site for accessing MODIS files, at, accessible via most internet browsers or FTP clients.

Tags: Data

Product Quality and Validation

Why is the AOD product less accurate in the Western U.S.?

There are several possible reasons why the AOD product is less accurate in the Western U.S.  Some of these reasons include: bright land surfaces, high altitudes and or rapidly changing topography, and potential inaccuracies in the MODIS aerosol models for the Western U.S.

What are the quality flags (QA), what do they mean and where can I find them?

Quality (QA) flags are an indicator of the algorithm team’s assessment of the quality of the data.  QA flag values range from 0 – 3 where 0 is lowest quality. We advise using only highest quality data (QA=3) for land products.  For ocean products we advise using anything above QA zero.  In collection 6 data this information is included in the SDS “Land_Ocean_Quality_Flag”.

In collection 5 data the QA flags are embedded in the SDS “Quality_Assurance_Land” and “Quality_Assurance_Ocean.”  The QA values must be read and interpreted from these SDS parameters.

MODIS aerosol products can be generated on the LADSWEB site with only recommended quality data.

This can be accomplished as follows:

After selecting data from your search put in in the shopping cart.

Select “View Your Shopping Cart”.  At the bottom of the page select “Post process and order data”  Click “Order”.  On the next page select “Data Quality Screening Service (DQSS).  Click “Order”.  The default values on the next page will be the QA values of data which we recommend for users.  Click “Order” to order your data.

I have head that Terra's calibration is drifting. What does this mean?

 It is normal and expected that the response of some of the MODIS detectors will degrade over time.  Due to some hardware issues with Terra the response of some of the detectors have degraded at an accelerated rate.  The MODIS calibration team analyses the changes in response over time to adjust the calibration of the sensor.  The calibration changes are applied to the data so that the final products should only be minimally affected by the changes in response.  One main reason it is taking longer to create the Terra collection 6 products is the greater effort required to correct for the changes in response to properly calibrate the product.

Should I use Terra or Aqua data?

Users need to make this determination for themselves based on the particular needs of their study.  For Collection 5 we feel Aqua is the more reliatble sensor due to the issues discussed in the FAQ "Is there a difference between Terra vs Aqua AOD?"   However for many types of studies data from either sensor can be used. Collection 6 data will require further study but we expect Aqua to be the more reliable sensor.

Is there a difference in Terra vs Aqua AOD?

Although sensor and algorithm design are identical between the two sensors, over time the sensors have decayed at different rates.  The rate of decay of Terra has been greater than Aqua. Consequently there is a small offset between Terra and Aqua AOD (.015 in Collection 5). Additionally, there is a decreasing trend of global land AOD in Terra Collection 5 (Levy et al., 2010), which is not observed in Aqua. This has been traced to a calibration issue (e.g. Wang et al., 2012), and is expected to be corrected in Collection 6. In addition, there is a calibration issue in Terra that causes striping over land in both Collection 5 and Collection 6.

What is the estimated error in other derived and diagnostic variables?

At this point, the MODIS aerosol team has not evaluated the reliability of other parameters, including certain derived parameters (e.g. Mass Concentration) and diagnostic parameters (cloud fraction). The user is cautioned that there is no expected quantitative value to these parameters. 

What is the estimated error in the ocean Angstrom Exponent?

In Collection 6, the preliminary estimate error is 0.45; pixels with an AOD > 0.2 are expected to have a more accurate Angstrom Exponent.

What is the estimated error in AOD in the dark target product?

In collection 5 the estimated errors are:

   Land:   AOD * 0.15 +/- 0.05

   Ocean: AOD * 0.05 +/- 0.03

 These are global estimates from the entire data set.  Errors in the product vary from region to region and season to season. For a site by site analysis see the maps in our “Validation” section. The Collection 6 product is currently being analyzed and error estimates have not yet been published.

How is the MODIS aerosol product validated?

MODIS data is inter-compared with data collected from the AERONET worldwide network of ground stations (See  The MODIS and AERONET data are temporally and spatially matched using the following criteria:

Temporal:  All AERONET observations made within +/- 30 minutes of a MODIS overpass at an AERONET site.

Spatial: All MODIS data retrieved within a 25 Km radius of an AERONET location for the 10 Km product and within 7.5 Km for the 3 Km product.

A minimum of 20% of possible MODIS pixels and two AERONET measurements meeting the above criteria are required to include the point in the validation data base.

For more information on this method see “A spatio-temporal approach for global validation and analysis of MODIS aerosol products” by Ichoku et. al.(2002) and “Multi-sensor Aerosol Products Sampling System (MAPSS)” by Petrenko et al.  (2012).

For a more detailed answer see the Validation section of our website.

Ocean vs. Land Products

What is the difference between the ocean and land products?

Ocean and land products use completely different algorithms. For any dark target retrieval algorithm we must accurately account for surface effects and build correct models of the aerosols.  Due to the complexities of the land surface it is more difficult for the land retrieval to account for surface effects. In addition aerosol models are fixed for the land product based on season and location.  The ocean product selects coarse and fine mode models dynamically.

These two factors account for several differences in the two products.

1)  The greater error of the AOD in land product

2)  AOD values for land are available at 0.47, 0.55, 0.67  and 2.1 µm

    AOD values for ocean are available at 0.47, 0.55, 0.67,0.87,1.2, 1.6 and 2.1 µm

3) In collection 5 and 6 the ocean product contains parameters which report fine and coarse mode AOD separately and the fine mode fraction. Over land we do not have the ability to retrieve these parameters accurately. These parameters are reported over land in Collection 5, but we do not recommend their use. In Collection 6, only fine mode fraction is reported but it is a diagnostic of how the retrieval is operating and not a representative value of the actual fine mode fraction.

For additional information see the presentations on the ocean and land algorithms in the education and reference materials section.