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
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LXJ_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LXK_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYJ_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYK_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYL_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYM_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYN_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYP_2016-04-15_final.stac-item
2016-04-15 10:18:55	ga_s2am_ard_3-2-1_54LYQ_2016-04-15_final.stac-item
2016-04-15 10:22:04	ga_s2am_ard_3-2-1_54KXE_2016-04-15_final.stac-item
2016-04-15 10:22:04	ga_s2am_ard_3-2-1_54KYE_2016-04-15_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXN_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXP_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXQ_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXR_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXS_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54JXT_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXA_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXB_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXC_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXD_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXE_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXF_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXU_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KXV_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYA_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYB_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYC_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYD_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYE_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYF_2017-06-16_final.stac-item
2017-06-16 10:11:32	ga_s2am_ard_3-2-1_54KYV_2017-06-16_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LXJ_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LXK_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYJ_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYK_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYL_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYM_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYN_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYP_2017-06-19_final.stac-item
2017-06-19 10:18:54	ga_s2am_ard_3-2-1_54LYQ_2017-06-19_final.stac-item
2017-06-19 10:22:04	ga_s2am_ard_3-2-1_54KXE_2017-06-19_final.stac-item
2017-06-19 10:22:04	ga_s2am_ard_3-2-1_54KYE_2017-06-19_final.stac-item
2017-06-23 10:06:40	ga_s2am_ard_3-2-1_54HXE_2017-06-23_final.stac-item
2017-06-23 10:06:40	ga_s2am_ard_3-2-1_54HXF_2017-06-23_final.stac-item
2017-06-23 10:06:40	ga_s2am_ard_3-2-1_54HXG_2017-06-23_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KXE_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KXF_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KXG_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KYE_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KYF_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54KYG_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LXH_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LXJ_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LXK_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYH_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYJ_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYK_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYL_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYM_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYN_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYP_2017-06-29_final.stac-item
2017-06-29 10:17:04	ga_s2am_ard_3-2-1_54LYQ_2017-06-29_final.stac-item
2017-07-20 09:52:25	ga_s2am_ard_3-2-1_54HXC_2017-07-20_final.stac-item
2017-07-20 09:52:25	ga_s2am_ard_3-2-1_54HXD_2017-07-20_final.stac-item
2017-07-20 09:52:25	ga_s2am_ard_3-2-1_54HXE_2017-07-20_final.stac-item
2017-07-20 09:52:25	ga_s2am_ard_3-2-1_54HXF_2017-07-20_final.stac-item
2022-09-18 10:12:10	ga_s2am_ard_3-2-1_54KXF_2022-09-18_final.stac-item
2022-09-18 10:12:23	ga_s2am_ard_3-2-1_54KXE_2022-09-18_final.stac-item
2022-09-18 10:12:37	ga_s2am_ard_3-2-1_54KXD_2022-09-18_final.stac-item
2022-09-18 10:12:48	ga_s2am_ard_3-2-1_54KYC_2022-09-18_final.stac-item
2022-09-18 10:12:52	ga_s2am_ard_3-2-1_54KXC_2022-09-18_final.stac-item
2022-09-18 10:13:03	ga_s2am_ard_3-2-1_54KYB_2022-09-18_final.stac-item
2022-09-18 10:13:06	ga_s2am_ard_3-2-1_54KXB_2022-09-18_final.stac-item
2022-09-18 10:13:17	ga_s2am_ard_3-2-1_54KYA_2022-09-18_final.stac-item
2022-09-18 10:13:21	ga_s2am_ard_3-2-1_54KXA_2022-09-18_final.stac-item
2022-09-18 10:13:35	ga_s2am_ard_3-2-1_54KXV_2022-09-18_final.stac-item
2022-09-18 10:13:50	ga_s2am_ard_3-2-1_54KXU_2022-09-18_final.stac-item
2022-10-11 10:21:57	ga_s2am_ard_3-2-1_54KYF_2022-10-11_final.stac-item
2022-10-11 10:22:01	ga_s2am_ard_3-2-1_54KXF_2022-10-11_final.stac-item
2022-10-11 10:22:09	ga_s2am_ard_3-2-1_54KYE_2022-10-11_final.stac-item
2022-10-11 10:22:15	ga_s2am_ard_3-2-1_54KXE_2022-10-11_final.stac-item
2022-10-18 10:13:26	ga_s2am_ard_3-2-1_54KYV_2022-10-18_final.stac-item
2022-10-18 10:13:29	ga_s2am_ard_3-2-1_54KXV_2022-10-18_final.stac-item
2022-10-18 10:13:44	ga_s2am_ard_3-2-1_54KXU_2022-10-18_final.stac-item
2022-10-18 10:13:58	ga_s2am_ard_3-2-1_54JXT_2022-10-18_final.stac-item
2022-10-18 10:14:13	ga_s2am_ard_3-2-1_54JXS_2022-10-18_final.stac-item
2022-10-18 10:14:27	ga_s2am_ard_3-2-1_54JXR_2022-10-18_final.stac-item
2022-10-18 10:14:41	ga_s2am_ard_3-2-1_54JXQ_2022-10-18_final.stac-item
2022-10-18 10:14:48	ga_s2am_ard_3-2-1_54JXP_2022-10-18_final.stac-item
2022-10-18 10:14:48	ga_s2am_ard_3-2-1_54JXQ_2022-10-18_final.stac-item
2022-10-18 10:14:56	ga_s2am_ard_3-2-1_54JXP_2022-10-18_final.stac-item
2022-10-18 10:15:10	ga_s2am_ard_3-2-1_54JXN_2022-10-18_final.stac-item
2022-10-25 10:04:46	ga_s2am_ard_3-2-1_54JXQ_2022-10-25_final.stac-item
2022-10-25 10:05:00	ga_s2am_ard_3-2-1_54JXP_2022-10-25_final.stac-item
2022-10-25 10:05:15	ga_s2am_ard_3-2-1_54JXN_2022-10-25_final.stac-item
2022-10-25 10:05:29	ga_s2am_ard_3-2-1_54JXM_2022-10-25_final.stac-item
2022-10-25 10:05:37	ga_s2am_ard_3-2-1_54JXM_2022-10-25_final.stac-item
2022-10-25 10:05:37	ga_s2am_ard_3-2-1_54JXL_2022-10-25_final.stac-item
2022-10-25 10:05:44	ga_s2am_ard_3-2-1_54JXL_2022-10-25_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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