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The Landsat 8 Pre-Collection Quality Assessment (QA) band is an important addition to Landsat 8 data files. Each pixel in the QA band contains integers that represent bit-packed combinations of surface, atmosphere, and sensor conditions that can affect the overall usefulness of a given pixel.

The Pre-Collection QA band is available for Landsat 8 OLI/TIRS Pre-Collection data only. The Landsat Collection 1 Quality Band web page provides information for Collection 1 Landsat 4-5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI)-only and Landsat 8 OLI/Thermal Infrared Sensor (OLI/TIRS)- combined data.

The table below displays the bits that are currently populated for Pre-Collection Landsat 8 OLI/TIRS scenes:

Pre-Collection QA Band Bits and Attributes

What are QA Bits?

The bit-packed information in the QA bands is translation of binary strings. As a simple example, the integer value “1” translates to the binary value “0001.” The binary value “0001” has 4 bits, written right to left as bits 0 (“1”), 1 (“0”), 2 (“0”), and 3 (“0”). Each of the bits 0-3 represents a yes/no indication of a physical value.

Used effectively, QA bits improve the integrity of science investigations by indicating which pixels might be affected by instrument artifacts or subject to cloud contamination. For example, NDVI calculated over pixels containing clouds will show anomalous values. If such pixels were included in a phenology study, the results might not show the true characteristics of seasonal vegetation growth. Cloud contaminated pixels will lower NDVI values, and measures like the timing of ‘green up’ or peak maturity would appear later than they actually occurred. A worse consequence would be that the reported reduction of vegetation growth would be taken as an indicator of environmental change, potentially prompting unnecessary land management policies or practices.

The Landsat QA Tools are no-cost tools that will extract bit-packed information in the Pre-Collection Landsat 8 QA band for easy interpretation.

Landsat 8 Pre-Collection Level-1 QA Band File (BQA.TIF)

Rigorous science applications seeking to optimize the value of pixels used in a study will find QA bits useful as a first level indicator of certain conditions. Otherwise, users are advised that this file contains information that can be easily misinterpreted and it is not recommended for general use.

Landsat 8 Pre-Collection Level-1 data products include a 16-bit QA file (.TIF). Robust image processing software capable of handling 16-bit data is necessary to compute statistics of the number of pixels containing each of the designated bits.

Quality Band (BQA.TIF) displayed as .jpg for reference only

Quality Band (BQA.TIF) displayed as .jpg for reference only
LDCM sample data Path 45 Row 30 Acquired April 23, 2013.

The QA image can be stretched to emphasize the light ("1"s) and dark ("0") pixels for a quick look at general quality conditions. In the Crater Lake, Oregon image above, the lighter pixels are likely to be affected by a quality condition, in this case snow or clouds.

The pixel values in the QA file must be translated to 16-bit binary form to be used effectively. The gray shaded areas in the table below show the bits that are currently being populated in the Level-1 QA Band, and the conditions each describe. None of the currently populated bits are expected to exceed 80% accuracy in their reported assessment at this time.

Landsat 8 Pre-Collection QA Bits, Read Right to Left

For the single bits (0, 1, 2, and 3):

  • 0 = No, this condition does not exist
  • 1 = Yes, this condition exists

For the Water bits (4-5)

  • 00 = No, this condition does not exist
  • 10 = Yes, this condition exists

For the Snow/Ice bits (10-11):

  • 00 = No, this condition does not exist
  • 11 = Yes, this condition exists

These conditions are detected by simple algorithms that currenlty indicate yes/no. They were allotted two bits each to leave room for more complex algorithms in the future.

The othe double bits (6-7, 8-9, 12-13, and 14-15), read from left to right, represent levels of confidence that a condition exists:

  • 00 = “Not Determined” = Algorithm did not determine the status of this condition
  • 01 = “No” = Algorithm has low to no confidence that this condition exists (0-33 percent confidence)
  • 10 = “Maybe” = Algorithm has medium confidence that this condition exists (34-66 percent confidence)
  • 11 = “Yes” = Algorithm has high confidence that this condition exists (67-100 percent confidence).

For example, a pixel with a value "56320" translates to the 16-bit binary string "1101 1100 0000 0000." Reading the binary string from right to left and using the table above as an interpretation legend, this pixel is:

  • Bit 0 = 0 = not fill
  • Bit 1 = 0 = not a dropped frame
  • Bit 2 = 0 = not terrain occluded
  • Bit 3 = 0 = unused
  • Bit 4-5 = 01 = not water
  • Bit 6-7 = 00 = unused
  • Bit 8-9 = 00 = unused
  • Bit 10-11 = 01 = snow/ice
  • Bit 12-13 = 10 = not cirrus
  • Bit 14-15 = 11 = cloudy

Certain values occur regularly and can be interpreted without unpacking them into 16-bit strings and using the table above as a reference. Some common pixel values and their meanings are included in the table below.

Common Values for Pre-Collection QA

LandsatLook Quality Image (.jpg)

The Landat 8 Pre-Collection LandsatLook 8-bit Quality Image (.jpg) is available to download when downloading Pre-Collection Landsat 8 data products. This file provides a quick view of the quality of the pixels to determine which scene would work best for each user's application. Only the highest confidence conditions are used to create the LandsatLook Quality image. Similar as stated above, this image may not be useful to all users. (Information on LandsatLook Images)

The table below gives the bits and colors associated with the LandsatLook Quality Image:

8-Bit LandsatLook QA Band

Landsat Look

Landsat Look "Quality" Image (QA.jpg) displayed as .jpg for reference only
LDCM/Landsat 8 sample data Path 45 Row 30 Acquired April 23, 2013.