HLSS30 v002

Aerosol QA bits from the USGS Land Surface Reflectance Code (LaSRC) model output have been added into the Function of Mask (Fmask) data layer. The added two bits indicate the aerosol levels: high, medium, low, and climatology aerosol.

HLS surface reflectance products are currently at stage 1 validation. Stage 2 validation of the HLS products is ongoing and will be made available on the individual data product landing pages when complete.

Additional information related to cloud and aerosol quality along with QA mappings are provided under section 6.4 of the User Guide.

Unrealistically high aerosol and low surface reflectance over bright areas. The atmospheric correction over bright targets occasionally retrieves unrealistically high aerosol and thus makes the surface reflectance too low. High aerosol retrievals, both false high aerosol and realistically high aerosol, are masked when quality bits 6 and 7 are both set to 1 (see Table 9 in the User Guide); the corresponding spectral data should be discarded from analysis.

Fmask omission errors. There are known issues regarding the Fmask band of this data product that impacts HLSS30 data prior to February 1, 2022. The HLS Fmask data band may have omission errors in water detection for cases where water detection using spectral data alone is difficult, and omission and commission errors in cloud shadow detection for areas with great topographic relief. This issue does not impact other bands in the dataset.

NDVI generation spike difference. There is a spike difference in HLSL30 and HLSS30 when generating NDVI index from granules after 2021 which was resolved with the integration of Landsat 9 in January 2023; however, it was not back processed. The HLS team is aware of this issue and is currently working on a fix.

TOA and surface reflectance values. European Space Agency (ESA) started to add 1000 units to the scaled top of atmosphere (TOA) and surface reflectance in late January of 2022, and Interagency Implementation and Advanced Concepts Team (IMPACT) accordingly subtracts 1000 units after the TOA data is read. Users unaware of this change saw a jump in the time series.

Inconsistent snow surface reflectance between Landsat and Sentinel-2. The HLS snow surface reflectance can be highly inconsistent between Landsat and Sentinel-2. When assessed on same-day acquisitions from Landsat and Sentinel-2, Landsat reflectance is generally higher than Sentinel-2 reflectance in the visible bands.

Unrealistically high snow surface reflectance in the visible bands. By design, the Land Surface Reflectance Code (LaSRC) atmospheric correction does not attempt aerosol retrieval over snow; instead, a default aerosol optical thickness (AOT) is used to drive the snow surface reflectance. If the snow detection fails, the full LaSRC is used in both AOT retrieval and surface reflectance derivation over snow, which produces surface reflectance values as high as 1.6 in the visible bands. This is a common problem for spring images at high latitudes.

Unrealistically low surface reflectance surrounding snow/ice. Related to the above, the AOT retrieval over snow/ice is generally too high. When this artificially high AOT is used to derive the surface reflectance of the neighboring non-snow pixels, very low surface reflectance will result. These pixels will appear very dark in the visible bands. If the surface reflectance value of a pixel is below -0.2, a NO_DATA value of -9999 is used. In Figure 1, the pixels in front of the glaciers have surface reflectance values that are too low.

Figure 1 Example of very low reflectance ahead of glaciers in HLS.L30.T22WET.2022224T144957.v2.0

Unrealistically low reflectance surrounding clouds. Like for snow, the HLS atmospheric correction does not attempt aerosol retrieval over clouds and a default AOT is used instead. But if the cloud detection fails, an artificially high AOT will be retrieved over clouds. If the high AOT is used to derive the surface reflectance of the neighboring cloud-free pixels, very low surface reflectance values will result. If the surface reflectance value of a pixel is below -0.2, a NO_DATA value of -9999 is used.

Unusually low reflectance around other bright land targets. While the HLS atmospheric correction retrieves AOT over non-cloud, non-snow bright pixels, the retrieved AOT over bright targets can be unrealistically high in some cases, similar to cloud or snow. If this unrealistically high AOT is used to derive the surface reflectance of the neighboring pixels, very low surface reflectance values can result as shown in Figure 2. If the surface reflectance value of a pixel is below -0.2, a NO_DATA value of -9999 is used. These types of bright targets are mostly man-made, such as buildings, parking lots, and roads.

Figure 2 Example of low reflectance in HLS.L30.T19TCH.2020142T152609.v2.0 around pixel 1324, 1860

Dark plumes over water. The HLS atmospheric correction does not attempt aerosol retrieval over water. For water pixels, the AOT retrieved from the nearest land pixels is used to derive the surface reflectance, but if the retrieval is incorrect, e.g. from a cloud pixel, this high AOT will create dark stripes over water, as shown in Figure 3. This happens more often over large water bodies, such as lakes and bays, than over narrow rivers.

Figure 3 Example of dark plumes over water in HLS.L30.T04QGH.2021188T205358

Fmask configuration was deficient for 2-3 months in 2021. The HLS installation of Fmask failed to include auxiliary digital elevation model (DEM) and European Space Agency (ESA) Global Surface Water Occurrence data for a 2-3 month run in 2021. This impacted the masking results over water and in mountainous regions.

Failure in applying Sentinel-2 image quality mask. Sentinel-2 Multispectral Instrument (MSI) infrequently experiences data packet loss that results in corrupted Level 1 images. To flag the data corruption, ESA originally created quality masks in Geography Markup Language (GML) vector format and then in raster format from January 2022. HLS has developed code to apply a correction, but the fix has not been applied as of May 2024. An example of this can be seen in Figure 4.

Figure 4 Example of failed application of Sentinel-2 image quality mask (HLS.S30.T37PFM.2023008T074311.v2.0)

Artifacts in consolidating two MSI data strips. Occasionally Sentinel-2 switches ground receiving stations while beaming down the imagery. This switch creates two data strips. The leading/trailing edges of the two data strips may be corrupted; therefore, when they are “stitched” into the same MGRS tile, artifacts of 1-2 pixels across the track are visible as shown in Figure 5. HLS processing has developed a remedy by taking advantage of the data redundancy near the leading/trailing edges, but the fix has not been applied as of May 2024.

Figure 5 Example of artifact in HLS.S30.T11SLU.2022278T183231.v2.0

The reflectance “scale_factor” and “offset” for some L30 and S30 bands were not set. The HLS reflectance scaling factor is 0.0001 and offset is 0. However, this information was not set in the Cloud Optimized GeoTIFF (COG) files of some bands for a small number of granules. The lack of this information creates a problem for automatic conversion of the reflectance data, requiring explicit scaling in applications. The problem has been corrected, but the affected granules have not been reprocessed.

Incomplete map projection information. For a time, HLS imagery was produced with an incomplete coordinate reference system (CRS). The metadata contains the Universal Transverse Mercator (UTM) zone and coordinates necessary to geolocate pixels within the image but might not be in a standard form, especially for granules produced early in the HLS mission. As a result, an error will occur in certain image processing packages due to the incomplete CRS. The simplest solution is to update to the latest version of Geospatial Data Abstraction Library (GDAL) and/or rasterio, which use the available information without error.

Isolated Sentinel-2 L1C geolocation problem. In rare cases for Sentinel-2, the geolocation for an orbit can be significantly off. ESA deletes the L1C data from its archive upon discovery of the problem, but the deleted data may have already been used by HLS. Currently, HLS processing is not synchronized with the ESA Sentinel-2 L1C archive update.

The UTC dates in the L30/S30 filenames may not be the local dates. UTC dates are used by ESA and the U.S. Geological Survey (USGS) in naming their Level 1 images, and HLS processing retains this information to name the L30 and S30 products. Landsat and Sentinel-2 overpass eastern Australia and New Zealand around 10AM local solar time, but this area is in either UTC+10:00 or +11:00 zone; therefore, the UTC time for some orbits is in fact near the end of the preceding UTC day. For example, HLS.S30.T59HQS.2016117T221552.v2.0 was acquired in the 22nd hour of day 117 of year 2016 in UTC, but the time was 10:15:52 of day 118 locally. Approximately 100 minutes later HLS.S30.T56JML.2016117T235252.v2.0 was acquired in the next orbit in eastern Australia.

This issue also occurs for Landsat. For example, HLS.L30.T59HQS.2016117T221209.v2.0 was acquired on the same day as the first S30 example given above, but both on day 118 of 2016 locally. Adding to the confusion for L30, in the same region, Landsat 8 and 9 can each overpass once in one of the two adjacent WRS-2 Paths (91/92/93) over a two-day period on a local calendar, but based on UTC time, the two overpasses can appear to be on the same day. For example, in the following seemingly same-day pair, the second L30 is actually for day 168 locally:
HLS.L30.T55GCN.2023167T000407.v2.0
HLS.L30.T55GCN.2023167T235747.v2.0
Bear in mind, the date peculiarity for the data occurs when the overpass time is during the late hours of a UTC day.

The atmospheric ancillary data from the wrong date was used for LaSRC. Related to the above, for eastern Australia and New Zealand, L30 and S30 surface reflectance on certain days was created using the atmospheric ancillary data from a date that was one day too early. The exact geographic extent of the affected HLS products and the impact on the surface reflectance quality are under investigation. Practice caution when using data with overpass times during the late hours of a UTC day.