*Landsat Collection 1 data is available for use and will replace Landsat Pre-Collection data in the future. For simplicity, the Landsat Collection 1 processing level designations (L1TP, L1GT, L1GS) will be used for the remainder of this page. For a comparison between Landsat Collection 1 and Pre-Collection processing levels, see this page.
Landsat science data products inherit the geometry of Landsat Level-1 data products. To incorporate these data into time series analysis, the pixels of the data need to be aligned. The exceptional geometry of the Landsat 8 OLI/TIRS systematic product provides an opportunity to improve the reference database used to precisely and accurately geolocate the Landsat data products.
To assure Landsat Level-1 data are suitable for time-series analysis, products need to be co-registered. The root-mean-square error (RMSE) reported in the metadata (MTL.txt) file can be used to filter the precision and terrain corrected Level-1 data products to meet application specific requirements. Landsat processing levels and the related accuracies of each are described below.
Landsat scenes are processed to a Level-1 precision and terrain corrected product (L1TP), if possible. In the case of insufficient reference data, a systematic and terrain corrected L1GT or a systematic L1GS product will be created instead. L1GT products are created when the systematic product has consistent and sufficient locational accuracy to permit the application of a terrain model. L1GS products are created when the locational accuracy is not sufficient to apply terrain correction. Three primary reasons L1GS scenes are created include 1) insufficient number of ground control points, such as small islands or Antarctica, 2) opaque clouds that obscure the ground, or 3) locational errors greater than the search distance for ground control.
Precision and Terrain Correction provides radiometric and geodetic accuracy by incorporating ground control points while employing a Digital Elevation Model (DEM) for topographic displacement. Geodetic accuracy of the product depends on the image quality and the accuracy, number, and distribution of the ground control points (GCP):
The information provided in the metadata file can be used to evaluate the geodetic accuracy of the L1TP data product.
Systematic Terrain Correction provides systematic, radiometric, and geometric accuracy, while employing a Digital Elevation Model (DEM) to correct for relief displacement:
Landsat 7 and Landsat 8 data over Antarctica are processed to an L1GT, since it has not been possible to generate ground control in Antarctica suitable for the generation of an L1TP product. The Radarsat Antarctic Mapping Project Digital Elevation Model Version 2 (RAMP V2 DEM) is the terrain correction source for Antarctica.
Systematic Correction provides systematic radiometric and geometric corrections, which are derived from data collected by the sensor and spacecraft.
Landsat TM and MSS images may be offset from its correct spatial location by thousands of meters, preventing the use of terrain correction for systematic products.
The success rate for creating L1TP products varies by sensor, but also by cloud cover. The table below displays each cloud-cover class and lists the proportion of images that process to an L1TP, those that fallback to an L1GT or L1GS after a failed attempt to produce an L1TP (clouds or poor ephemeris data), and the proportion that are planned to produce an L1GT (night, Antarctica or insufficient land features). These values were generated from the most recent Landsat Level-1 Product Generation System (LPGS) software version.
Figure 1. Level-1 Products Registration Success by Cloud Cover, based on LPGS release version 12.8.0, August 2016
*Landsat 1-7: All path/row combinations are separated internally into two groups; path/rows that will undergo precision and terrain correction, and path/rows that will not be precision and terrain corrected. If precision and terrain correction is attempted and successful, the scene becomes an L1TP. If precision correction is unsuccessful, the scene becomes an L1GT FB (fallback). If precision and terrain correction is not applied, the scene will become an L1GS (or L1GT for Landsat 7).
*Landsat 8: All path/rows are separated into two groups; path/rows that have produced at least one L1TP scene, and path/rows that have never produced an L1TP scene. Precision and terrain correction is attempted on all Landsat 8 scenes. If precision correction fails from the path/row group that has produced at least one L1TP, the scene becomes an L1GT FB (fallback). If precision correction fails from a path/row that has never produced an L1TP (which is likely), then the scene will become an L1GT (no fallback).
The distribution of the RMSE for each sensor shows significant improvement as sensor and spacecraft technologies evolve.
Figure 2. Landsat 8 OLI Collection 1 L1TP RMSE: Less than 12 meters in 92.4 percent of the data
Figure 3. Landsat 7 ETM+ Collection 1 L1TP RMSE: Less than 12 meters in 96.5 percent of the data
Figure 4. Landsat 4-5 TM Collection 1 L1TP RMSE: Less than 12 meters in 96.2 percent of the data
Figure 5. Landsat 1-5 MSS Pre-Collection L1T RMSE: Less than 12 meters in 0.2 percent of the data
Ground Control Points (GCPs) are defined as points on the surface of the earth of known location used to geo-reference Landsat Level-1 imagery. The Landsat Ground Control Point Search allows you to extract ground control point binary files over your area of interest.
In 2014, improvements to GCP files began – these include removing outdated files, and creating new, time-specific and seasonal GCP’s. The GCP Improvement Plan provides an overview of the goals and plans for the effort. Because the updated GCPs will be more accurate, users may consider re-ordering previously downloaded images, as new GCPs may allow scenes that once could only be processed to systematic L1GT products to be processed as a precision and terrain corrected L1TP.
These new GCPs allowed Landsat 8 scenes that once processed only to systematic Level-1 (L1GT) product to process a precision and terrain corrected Level-1T (L1TP). Additionally, GCPs that were contained within large bodies of water were removed from use during Level-1 processing. Although the presence of these points typically has little effect on the quality of the geometric registration of the L1TP data, the removal of these GCPs indicated that generating L1TP products was possible.
Phase 1 updated the accuracy within a number of GCPs in high priority areas, known to have large offsets in the original points. The new GCPs allowed scenes that once created only a systematic Level-1GT product to process a precision Level-1TP. 171 paths/rows covering the following areas were updated:
Desert regions where shifting dunes caused existing GCPs to become obsolete and other anomalous locations in which an apparent bias remained.
Phase 1 updates were implemented in the following Landsat Level-1 Product Generation System (LPGS) releases (noted in the MTL file):
Landsat 1-7: PROCESSING_SOFTWARE_VERSION = "LPGS_12.5.0"
The GCP Improvement Plan provides the triangulation results for the paths/rows improved in Phase 1.
In April 2015, a software issue was fixed. The GCP image chips used to perform the precision correction for L1TP products are in a UTM projection. When the set of GCPs to use is identified for a specific scene, some of the chips might be in different UTM zones – so some of the image chips are reprojected to get all the chips into the correct UTM zone for the scene being processed.
It was discovered that the chip reprojection software had a rounding bug that added a bias to the image chip location. On average, the bias would be roughly half of a 30m pixel. The impact was considered minor enough that no data has been reprocessed to correct this. The impact should always be less than half a pixel and usually much, much less than that (depending on how many chips with the location bias end up being used in the precision solution).
Landsat 8: PROCESSING_SOFTWARE_VERSION = “LPGS_2.5.0” for this correction.
Phase 2 includes 1,151 WRS-2 paths/rows, covering island areas and inland regions where the estimated absolute accuracy of the original Global Land Survey 2000 (GLS2000)-based ground control varied between 50-75 meters. This update affected:
Specific updates to GCPs used over Australia in order for that region to be more consistent with the Australian Geographic Reference Image (AGRI).
The metadata file (MTL.txt) delivered with the reprocessed Level-1 scenes include a new field, to indicate newly processed data:
The FILE_DATE will be updated with a date after January 11, 2016
Phase 3 updated 918 path/rows, covering high latitude arctic regions where the existing GLS2000-based ground control points were found to contain errors of 50 meters or more. In addition to correcting the existing GCPs and adding new GCPs where the existing coverage is sparse or absent, this update implements improvements to the digital elevation model (DEM) used for Greenland, and for the islands of Svalbard and Jan Mayen Land. This DEM update uses more accurate data recently created by the Greenland Ice Mapping Project (GIMP) and the Norwegian Polar Institute (NPI).*
*The new Greenland DEM data are described in this publication:
Howat, I., A. Negrete, and B. Smith. 2015. MEaSURES Greenland Ice Mapping Project (GIMP) Digital Elevation Model, Version 1. The 90-meter resolution data set was used. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi:http://dx.doi.org/10.5067/NV34YUIXLP9W. Accessed 29 January 2016.
*The new NPI DEMs for Svalbard and Jan Mayen Land are described in the following publications:
Norwegian Polar Institute. (2014). Terrengmodell Svalbard (S0 Terrengmodell). The 50-meter resolution data set was used. Tromsø, Norway: Norwegian Polar Institute. https://data.npolar.no/dataset/dce53a47-c726-4845-85c3-a65b46fe2fea Accessed 10 February 2016.
Norwegian Polar Institute. (2014). Terrengmodell Jan Mayen (J0 Terrengmodell). The 25-meter resolution data set was used. Tromsø, Norway: Norwegian Polar Institute. https://data.npolar.no/dataset/e2b2417e-9926-4519-b6a9-7eefb3bb1012 Accessed 10 February 2016.