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The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-07-04_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KHQ_2018-07-04_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-07-04_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KKB_2018-07-04_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-07-04_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKT_2018-07-04_final
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-07-07_final
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_50KKB_2018-07-07_final
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-07_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2018-07-14_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKT_2018-07-14_final
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-07-17_final
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-17_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JGN_2018-07-24_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-07-24_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50KKB_2018-07-24_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-07-24_final
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKT_2018-07-24_final
2018-07-27 12:13:22	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final
2018-07-27 12:13:22	ga_s2am_ard_3-2-1_50KKB_2018-07-27_final
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49JGN_2018-07-27_final
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHQ_2018-07-27_final
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KGQ_2018-07-27_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JGN_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KHQ_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KHR_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50KKB_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KGQ_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKT_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLQ_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLR_2018-09-02_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JTM_2018-09-03_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JGN_2018-09-05_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHQ_2018-09-05_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHR_2018-09-05_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_50KKB_2018-09-05_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGP_2018-09-05_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGQ_2018-09-05_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JNM_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JNN_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JPN_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JQS_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_51JUL_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JNP_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JNQ_2018-09-06_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JPR_2018-09-06_final
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JNN_2018-09-06_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNN_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JLQ_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JLR_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JMN_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JMP_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JMQ_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNP_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNQ_2018-09-09_final
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JPR_2018-09-09_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLR_2018-09-12_final
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KHQ_2018-09-15_final
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KHR_2018-09-15_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNN_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLQ_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLR_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JMN_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JMP_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JMQ_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNP_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNQ_2018-09-19_final
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JPR_2018-09-19_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHR_2018-09-25_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_50KKB_2018-09-25_final
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-09-25_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JGN_2018-09-25_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KHR_2018-09-25_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KGP_2018-09-25_final
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KGQ_2018-09-25_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JNN_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPN_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQS_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JNP_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JNQ_2018-09-26_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPR_2018-09-26_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JNN_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLQ_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLR_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMN_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMP_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMQ_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JNP_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JNQ_2018-09-29_final
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JPR_2018-09-29_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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