A two digit number that separates image and payload correction (PCD) quality is used by the LPS for Landsat 7. The first digit represents image data quality and can range in value from 0 to 9. The second digit represents PCD quality and can range in value from 0 to 9. The formula for the combined score is:
image score * 10 + PCD score
The following paragraphs describe how the image quality
and PCD quality scores are assigned.
Image Quality Component
The image quality digit is based on the number and distribution of bad scans or equivalent bad scans in a scene. It is computed by dividing the total number of filled minor frames for a scene by 6313 (the nominal number of image data minor frames in a major frame for 30 meter bands). This will give a number of equivalent bad scans.
The distribution of filled minor frames is characterized as being either clustered or scattered. A cluster of 128 bad scans will still yield a scene with a cluster 246 good scans which is almost 2/3 of a scene. A scattering of 128 band scans may make the entire image worthless.
What defines clustering versus scattering? It is proposed that bad scan lines are clustered if they occur within a grouping of 128 contiguous scans (approximately 1/3 of a scene). Errors are characterized as scattered if they occur outside the bounds of 128 contiguous scans. The image score is assigned according to the rules in Table 12.1.
| Table 12.1 Scene Quality Score - Image Quality Component | |
| Score | Image Quality |
| 9 | no errors detected, a perfect scene |
| 8 | <= 4 equivalent bad scans, clustered |
| 7 | <= 4 equivalent bad scans, scattered |
| 6 | <= 16 equivalent bad scans, clustered |
| 5 | <= 16 equivalent bad scans, scattered |
| 4 | <= 64 equivalent bad scans, clustered |
| 3 | <= 64 equivalent bad scans, scattered |
| 2 | <= 128 equivalent bad scans, clustered |
| 1 | <= 128 equivalent bad scans, scattered |
| 0 | > 128 equivalent bad scans, scattered (> 33% of the scene is bad) |
PCD Quality Component
The PCD quality digit is based on the number and distribution of filled PCD minor frames. There are approximately 7 PCD major frames for a standard WRS scene comprised of 375 scans. Each PCD major frame consists of 128 minor frames or 16,384 bytes. Clustering of filled PCD minor frames indicates that errors are localized whereas scattering indicates that numerous or all major frames may be affected.
What defines clustering versus scattering? Each PCD minor frame has 16 jitter measurements and corresponds to 30 milliseconds or approximately 1/2 of a scan. Two minor frames correspond to a single scan while 256 minor frames (i.e., 2 PCD major frames) corresond to 128 scans or approximately 1/3 of a scene.
Like the image data, it is proposed that bad PCD minor frames are clustered if they occur within a grouping of 2 contiguous PCD major frames (1/3 of a scene). Errors are characterized as scattered if they occur outside the bounds of contiguous PCD major frames. The PCD score is assigned according to the rules in Table 12.2.
| Table 12.2 Scene Quality Score - PCD Quality Component | |
| Score | PCD Quality |
| 9 | no PCD errors detected |
| 8 | <= 8 bad minor frames, clustered |
| 7 | <= 8 bad minor frames, scattered |
| 6 | <= bad minor frames, clustered |
| 5 | <= 32 bad minor frames, scattered |
| 4 | <= 128 bad minor frames, clustered |
| 3 | <= 128 bad minor frames, scattered |
| 2 | <= 256 bad minor frames, clustered |
| 1 | <= 256 bad minor frames, scattered |
| 0 | > 256 bad minor frames, scattered (> 33% of the scene is bad) |
Scene Quality
The score calculated using the methods described above are recorded in the scene level metadata under the keyword SCENE_QUALITY. Using this scoring system the highest possible rating for an image would be 99, the lowest 00. The score treats missing image data more critically than missing or filled PCD data. For example, an image with 16 filled scans that are scattered and with errorless PCD would have a 59 score whereas an image with intact image data and a 32 filled PCD minor frames that are scattered would receive a score of 95. The rationale is that PCD is less important because missing values can always be extrapolated or interpolated to enable level 1 processing. Missing image data cannot be retrieved and thus impacts the user more severely than missing PCD. The score construct unambiguously alerts the user to image data deterioration.
