Search ga_s2am_ard_3 whole collection

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

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

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

ID of a dataset type:

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

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

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

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

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

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

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

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

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

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

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

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

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

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

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

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

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

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-04-02 09:22:41	ga_s2am_ard_3-2-1_56JLL_2017-04-01_final.stac-item
2017-04-05 09:32:15	ga_s2am_ard_3-2-1_56KLA_2017-04-05_final.stac-item
2017-04-05 09:32:15	ga_s2am_ard_3-2-1_56KLB_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56JLQ_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56JLR_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56JLS_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56JLT_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56KLA_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56KLU_2017-04-05_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_56KLV_2017-04-05_final.stac-item
2017-04-18 09:42:13	ga_s2am_ard_3-2-1_56KLA_2017-04-18_final.stac-item
2017-04-18 09:42:13	ga_s2am_ard_3-2-1_56KLB_2017-04-18_final.stac-item
2017-04-18 09:42:13	ga_s2am_ard_3-2-1_56KLD_2017-04-18_final.stac-item
2017-04-18 09:42:13	ga_s2am_ard_3-2-1_56KLV_2017-04-18_final.stac-item
2017-04-28 09:42:15	ga_s2am_ard_3-2-1_56KLA_2017-04-28_final.stac-item
2017-04-28 09:42:15	ga_s2am_ard_3-2-1_56KLB_2017-04-28_final.stac-item
2017-04-28 09:42:15	ga_s2am_ard_3-2-1_56KLD_2017-04-28_final.stac-item
2017-04-28 09:42:15	ga_s2am_ard_3-2-1_56KLU_2017-04-28_final.stac-item
2017-04-28 09:42:15	ga_s2am_ard_3-2-1_56KLV_2017-04-28_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLN_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLP_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLQ_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLR_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLS_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56JLT_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56KLA_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56KLB_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56KLU_2017-05-05_final.stac-item
2017-05-05 09:32:20	ga_s2am_ard_3-2-1_56KLV_2017-05-05_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56HLJ_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56HLK_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56HMJ_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56HMK_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLL_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLM_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLN_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLP_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLQ_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLR_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLS_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56JLT_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56KLA_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56KLB_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56KLU_2017-05-15_final.stac-item
2017-05-15 09:32:21	ga_s2am_ard_3-2-1_56KLV_2017-05-15_final.stac-item
2017-05-18 09:42:16	ga_s2am_ard_3-2-1_56KLA_2017-05-18_final.stac-item
2017-05-18 09:42:16	ga_s2am_ard_3-2-1_56KLB_2017-05-18_final.stac-item
2017-05-18 09:42:16	ga_s2am_ard_3-2-1_56KLU_2017-05-18_final.stac-item
2017-05-18 09:42:16	ga_s2am_ard_3-2-1_56KLV_2017-05-18_final.stac-item
2017-05-22 09:22:47	ga_s2am_ard_3-2-1_56HLK_2017-05-21_final.stac-item
2017-05-22 09:22:47	ga_s2am_ard_3-2-1_56JLL_2017-05-21_final.stac-item
2017-05-22 09:25:33	ga_s2am_ard_3-2-1_56HLJ_2017-05-21_final.stac-item
2017-05-22 09:25:33	ga_s2am_ard_3-2-1_56HLK_2017-05-21_final.stac-item
2017-05-22 09:25:33	ga_s2am_ard_3-2-1_56HMJ_2017-05-21_final.stac-item
2017-05-22 09:25:33	ga_s2am_ard_3-2-1_56HMK_2017-05-21_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56JLP_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56JLQ_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56JLR_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56JLS_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56JLT_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56KLA_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56KLB_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56KLU_2017-06-04_final.stac-item
2017-06-04 09:32:20	ga_s2am_ard_3-2-1_56KLV_2017-06-04_final.stac-item
2018-11-19 09:41:35	ga_s2am_ard_3-2-1_56KLF_2018-11-19_final.stac-item
2018-11-19 09:41:50	ga_s2am_ard_3-2-1_56KLE_2018-11-19_final.stac-item
2018-11-19 09:42:04	ga_s2am_ard_3-2-1_56KLD_2018-11-19_final.stac-item
2018-11-19 09:42:33	ga_s2am_ard_3-2-1_56KLB_2018-11-19_final.stac-item
2018-11-19 09:42:48	ga_s2am_ard_3-2-1_56KLA_2018-11-19_final.stac-item
2018-11-19 09:43:02	ga_s2am_ard_3-2-1_56KLV_2018-11-19_final.stac-item
2018-11-19 09:43:17	ga_s2am_ard_3-2-1_56KLU_2018-11-19_final.stac-item
2018-11-23 09:25:50	ga_s2am_ard_3-2-1_56HLJ_2018-11-22_final.stac-item
2018-11-26 09:32:51	ga_s2am_ard_3-2-1_56KLA_2018-11-26_final.stac-item
2018-11-26 09:33:05	ga_s2am_ard_3-2-1_56KLV_2018-11-26_final.stac-item
2018-11-26 09:33:20	ga_s2am_ard_3-2-1_56KLU_2018-11-26_final.stac-item
2018-11-26 09:33:34	ga_s2am_ard_3-2-1_56JLT_2018-11-26_final.stac-item
2018-11-26 09:33:49	ga_s2am_ard_3-2-1_56JLS_2018-11-26_final.stac-item
2018-11-26 09:34:03	ga_s2am_ard_3-2-1_56JLR_2018-11-26_final.stac-item
2018-11-26 09:34:18	ga_s2am_ard_3-2-1_56JLQ_2018-11-26_final.stac-item
2018-11-26 09:34:32	ga_s2am_ard_3-2-1_56JLP_2018-11-26_final.stac-item
2018-11-26 09:34:47	ga_s2am_ard_3-2-1_56JLN_2018-11-26_final.stac-item
2018-11-26 09:35:02	ga_s2am_ard_3-2-1_56JLM_2018-11-26_final.stac-item
2018-11-26 09:35:16	ga_s2am_ard_3-2-1_56JLL_2018-11-26_final.stac-item
2018-12-06 09:35:30	ga_s2am_ard_3-2-1_56HLK_2018-12-06_final.stac-item
2018-12-06 09:35:45	ga_s2am_ard_3-2-1_56HLJ_2018-12-06_final.stac-item
2018-12-09 09:41:48	ga_s2am_ard_3-2-1_56KLE_2018-12-09_final.stac-item
2018-12-09 09:42:02	ga_s2am_ard_3-2-1_56KLD_2018-12-09_final.stac-item
2018-12-09 09:42:31	ga_s2am_ard_3-2-1_56KLB_2018-12-09_final.stac-item
2018-12-09 09:42:46	ga_s2am_ard_3-2-1_56KLA_2018-12-09_final.stac-item
2018-12-09 09:43:00	ga_s2am_ard_3-2-1_56KLV_2018-12-09_final.stac-item
2018-12-09 09:43:15	ga_s2am_ard_3-2-1_56KLU_2018-12-09_final.stac-item
2019-04-22 09:25:33	ga_s2am_ard_3-2-1_56JLL_2019-04-21_final.stac-item
2019-04-22 09:25:42	ga_s2am_ard_3-2-1_56HMK_2019-04-21_final.stac-item
2019-04-22 09:25:46	ga_s2am_ard_3-2-1_56HLK_2019-04-21_final.stac-item
2019-04-22 09:25:57	ga_s2am_ard_3-2-1_56HMJ_2019-04-21_final.stac-item
2019-04-22 09:26:00	ga_s2am_ard_3-2-1_56HLJ_2019-04-21_final.stac-item
2019-05-02 09:25:33	ga_s2am_ard_3-2-1_56JLL_2019-05-01_final.stac-item
2019-05-02 09:25:43	ga_s2am_ard_3-2-1_56HMK_2019-05-01_final.stac-item
2019-05-02 09:25:46	ga_s2am_ard_3-2-1_56HLK_2019-05-01_final.stac-item
2019-05-02 09:25:58	ga_s2am_ard_3-2-1_56HMJ_2019-05-01_final.stac-item

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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