USGS EROS Archive - Advanced Very High Resolution Radiometer (AVHRR) - Orbital Pass Generation and Stitching
Orbital Pass Generation
Nearly 45,000 individual observations were acquired during the first 30 months of this project. The number of individual scenes and overall data volume, an estimated 4.0 terabytes, are large by contemporary standards. As a result a new process was developed to improve data management.
Back to Advanced Very High Resolution Radiometer (AVHRR)
Orbital Pass Stitching
Orbital stitching is the process of combining a group of consecutive AVHRR observations to form an orbital pass. The global land 1-km AVHRR data set consists of only the afternoon (ascending) passes, and no descending (night time) data, from the NOAA polar orbiting satellites. As a result only half of the data from an individual orbit is needed. When the afternoon observations are stitched, a pole to pole half-orbital pass is generated. Combining the observations reduces the data volume by eliminating redundant data from the overlap areas between receiving stations, improves data quality by removing dropped and bad scan lines, and facilitates data distribution and product generation by reducing the overall number of units of data that must be handled.
Data quality of the individual observations was a major concern. Examination of the data received from the ground stations and the tape recorded LAC data identified several data quality problems. The most common problems were dropped lines, anomalous line and pixel noise and repeated lines. Dropped lines are generally replaced with the zero value automatically during the acquisition process. These were easy to locate and present very little problem in subsequent processing. The other problems were much more serious.
Anomalous lines and pixels were very difficult to detect because they contain non-zero values. The anomalous lines were generally common to all channels, whereas single pixel noise was not. The anomalous values in the lines and pixels cover the complete data range. However, the anomalous lines and pixels generally occurred at the beginning or end of an image and were assumed to be related to problems associated with acquisition and loss of signal due to low antenna angles at the horizon. Repeated lines were not very common and were also assumed to be associated with acquisition and loss of signal due to low antenna angles at the horizon.
Detection of the bad data was necessary in order to avoid serious problems in subsequent processing. The problems were very evident following the production of the first 10-day normalized difference vegetation index (NDVI) composite. The anomalous lines and pixels produced either very high or low NDVI values. The problems with the low NDVI values were apparently corrected by the maximum NDVI compositing process because pixels from other observations with higher NDVI values were selected for the composite. However, the problems that produced high NDVI values were carried throughout the process and remained in the composite. They were most evident in areas with low NDVI. The lines showed up as linear features and the pixels showed up as speckles in the data. The data in the composite become useless in areas where the bad data occur on a daily basis.
Once the bad data were present in the composite, there was no effective method for removing it. Therefore, it was necessary to detect them in the raw data. Two bad data detection algorithms were developed; one for lines and the other for pixels. The algorithms were used on the raw data prior to stitching. Bad lines and pixels were detected using a series of tests of different combinations of channels. If a bad line or pixel was detected it was set to the zero value. Zero values were handled in such a way that there were no detrimental effects on subsequent processing. The effect of the bad data detection algorithms was monitored and the algorithms were adjusted to optimize bad data detection and minimize false detections.
The stitching process began with the southernmost observation (the observation in the group with the earliest start time). The start time of the next observation was used to determine if an overlap area or gap existed between observations. When the end time of the previous observation in the half-orbit pass was later than the start time of the next observation, an overlap area existed. Instead of automatically copying each record from the half-orbit pass that overlaps with the next observation, each scan line was read and checked to determine if the line contained valid data.
The most frequent form of invalid data was a dropped line. A dropped line, a record containing all zEDC, was identified by a gap between the consecutive time stamps. ZEDC were added to the pass by the acquisition systems to maintain the proper along-track perspective.
When a zero value (a line or pixel that was detected as missing or bad data) was encountered in the first observation, the coincident record from the overlap area was read to determine if it was valid data. If this record was valid, it was used to replace the zero values in the half-orbit pass. If a replacement line was not found, the zero value was left and processing continued. After the overlap area was completed the remainder of the observation was copied to the half-orbit pass. This process was repeated until all the observations had been added to the half-orbital pass.
If a gap between observations existed when the start time of the next pass was later than the end time of the orbital pass, the gap was zero filled in the half-orbit pass to maintain the proper along-track perspective. To conserve data storage, missing data at the beginning or end of the orbital pass, such as missed passes or ocean data, were not zero filled. Thus each half-orbital pass did not stretch from pole to pole.
The orbital stitching process will reduce the number of archive elements from approximately 50,000 images to 7,700 orbits and reduces data volume from 5.0 terabytes to approximately 3.0 terabytes.
Acquisition and Archive Status
From April 1, 1992, through September 13, 1994, the EDC received, archived, and created metadata and browse for over 45,000 scenes. Orbital segments will be produced chronologically beginning with data from April 1, 1992.
The raw data are an important product simply because many AVHRR data at 1-km were either unavailable, or at least very difficult to acquire from foreign receiving stations; these are now readily available from the archive of the EDC, ESA, and NOAA. The raw data are also most desirable for development of calibration, atmospheric correction, and other algorithms requiring the basic raw data. The raw data will initially be available on a scene basis as it is acquired by the ground receiving stations and eventually as part of an orbital segment. The use of the orbital segments will improve along track scene- framing so the user will be able to use a single continuous scene instead of having to mosaic multiple scenes to obtain coverage of a large study area.
Orbital Stitch Grouping
Orbital Pass Data Reduction
Two Stitched Orbits
Additional Information
Access Data
EarthExplorer can be used to search, preview, and download Advanced Very High Resolution Radiometer (AVHRR). The collection are located under the Advanced Very High Resolution Radiometer (AVHRR) category.
Digital Object Identifier (DOI)
Below are other science projects associated with this product.
USGS EROS Archive - Advanced Very High Resolution Radiometer - AVHRR
USGS EROS Archive - AVHRR Normalized Difference Vegetation Index (NDVI) Composites
Orbital Pass Generation
Nearly 45,000 individual observations were acquired during the first 30 months of this project. The number of individual scenes and overall data volume, an estimated 4.0 terabytes, are large by contemporary standards. As a result a new process was developed to improve data management.
Back to Advanced Very High Resolution Radiometer (AVHRR)
Orbital Pass Stitching
Orbital stitching is the process of combining a group of consecutive AVHRR observations to form an orbital pass. The global land 1-km AVHRR data set consists of only the afternoon (ascending) passes, and no descending (night time) data, from the NOAA polar orbiting satellites. As a result only half of the data from an individual orbit is needed. When the afternoon observations are stitched, a pole to pole half-orbital pass is generated. Combining the observations reduces the data volume by eliminating redundant data from the overlap areas between receiving stations, improves data quality by removing dropped and bad scan lines, and facilitates data distribution and product generation by reducing the overall number of units of data that must be handled.
Data quality of the individual observations was a major concern. Examination of the data received from the ground stations and the tape recorded LAC data identified several data quality problems. The most common problems were dropped lines, anomalous line and pixel noise and repeated lines. Dropped lines are generally replaced with the zero value automatically during the acquisition process. These were easy to locate and present very little problem in subsequent processing. The other problems were much more serious.
Anomalous lines and pixels were very difficult to detect because they contain non-zero values. The anomalous lines were generally common to all channels, whereas single pixel noise was not. The anomalous values in the lines and pixels cover the complete data range. However, the anomalous lines and pixels generally occurred at the beginning or end of an image and were assumed to be related to problems associated with acquisition and loss of signal due to low antenna angles at the horizon. Repeated lines were not very common and were also assumed to be associated with acquisition and loss of signal due to low antenna angles at the horizon.
Detection of the bad data was necessary in order to avoid serious problems in subsequent processing. The problems were very evident following the production of the first 10-day normalized difference vegetation index (NDVI) composite. The anomalous lines and pixels produced either very high or low NDVI values. The problems with the low NDVI values were apparently corrected by the maximum NDVI compositing process because pixels from other observations with higher NDVI values were selected for the composite. However, the problems that produced high NDVI values were carried throughout the process and remained in the composite. They were most evident in areas with low NDVI. The lines showed up as linear features and the pixels showed up as speckles in the data. The data in the composite become useless in areas where the bad data occur on a daily basis.
Once the bad data were present in the composite, there was no effective method for removing it. Therefore, it was necessary to detect them in the raw data. Two bad data detection algorithms were developed; one for lines and the other for pixels. The algorithms were used on the raw data prior to stitching. Bad lines and pixels were detected using a series of tests of different combinations of channels. If a bad line or pixel was detected it was set to the zero value. Zero values were handled in such a way that there were no detrimental effects on subsequent processing. The effect of the bad data detection algorithms was monitored and the algorithms were adjusted to optimize bad data detection and minimize false detections.
The stitching process began with the southernmost observation (the observation in the group with the earliest start time). The start time of the next observation was used to determine if an overlap area or gap existed between observations. When the end time of the previous observation in the half-orbit pass was later than the start time of the next observation, an overlap area existed. Instead of automatically copying each record from the half-orbit pass that overlaps with the next observation, each scan line was read and checked to determine if the line contained valid data.
The most frequent form of invalid data was a dropped line. A dropped line, a record containing all zEDC, was identified by a gap between the consecutive time stamps. ZEDC were added to the pass by the acquisition systems to maintain the proper along-track perspective.
When a zero value (a line or pixel that was detected as missing or bad data) was encountered in the first observation, the coincident record from the overlap area was read to determine if it was valid data. If this record was valid, it was used to replace the zero values in the half-orbit pass. If a replacement line was not found, the zero value was left and processing continued. After the overlap area was completed the remainder of the observation was copied to the half-orbit pass. This process was repeated until all the observations had been added to the half-orbital pass.
If a gap between observations existed when the start time of the next pass was later than the end time of the orbital pass, the gap was zero filled in the half-orbit pass to maintain the proper along-track perspective. To conserve data storage, missing data at the beginning or end of the orbital pass, such as missed passes or ocean data, were not zero filled. Thus each half-orbital pass did not stretch from pole to pole.
The orbital stitching process will reduce the number of archive elements from approximately 50,000 images to 7,700 orbits and reduces data volume from 5.0 terabytes to approximately 3.0 terabytes.
Acquisition and Archive Status
From April 1, 1992, through September 13, 1994, the EDC received, archived, and created metadata and browse for over 45,000 scenes. Orbital segments will be produced chronologically beginning with data from April 1, 1992.
The raw data are an important product simply because many AVHRR data at 1-km were either unavailable, or at least very difficult to acquire from foreign receiving stations; these are now readily available from the archive of the EDC, ESA, and NOAA. The raw data are also most desirable for development of calibration, atmospheric correction, and other algorithms requiring the basic raw data. The raw data will initially be available on a scene basis as it is acquired by the ground receiving stations and eventually as part of an orbital segment. The use of the orbital segments will improve along track scene- framing so the user will be able to use a single continuous scene instead of having to mosaic multiple scenes to obtain coverage of a large study area.
Orbital Stitch Grouping
Orbital Pass Data Reduction
Two Stitched Orbits
Additional Information
Access Data
EarthExplorer can be used to search, preview, and download Advanced Very High Resolution Radiometer (AVHRR). The collection are located under the Advanced Very High Resolution Radiometer (AVHRR) category.
Digital Object Identifier (DOI)
Below are other science projects associated with this product.