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
2019-06-27 11:24:03	ga_s2am_ard_3-2-1_51KWQ_2019-06-27_final.stac-item
2019-06-27 11:24:10	ga_s2am_ard_3-2-1_51KZP_2019-06-27_final.stac-item
2019-06-27 11:24:10	ga_s2am_ard_3-2-1_52KBU_2019-06-27_final.stac-item
2019-06-27 11:24:13	ga_s2am_ard_3-2-1_51KYP_2019-06-27_final.stac-item
2019-06-27 11:24:16	ga_s2am_ard_3-2-1_51KXP_2019-06-27_final.stac-item
2019-06-27 11:24:19	ga_s2am_ard_3-2-1_51KWP_2019-06-27_final.stac-item
2019-06-27 11:24:23	ga_s2am_ard_3-2-1_51JZN_2019-06-27_final.stac-item
2019-06-27 11:24:23	ga_s2am_ard_3-2-1_52JBT_2019-06-27_final.stac-item
2019-06-27 11:24:27	ga_s2am_ard_3-2-1_51JYN_2019-06-27_final.stac-item
2019-06-27 11:24:31	ga_s2am_ard_3-2-1_51JXN_2019-06-27_final.stac-item
2019-06-27 11:24:34	ga_s2am_ard_3-2-1_51JWN_2019-06-27_final.stac-item
2019-06-27 11:24:37	ga_s2am_ard_3-2-1_51JZM_2019-06-27_final.stac-item
2019-06-27 11:24:37	ga_s2am_ard_3-2-1_52JBS_2019-06-27_final.stac-item
2019-06-27 11:24:41	ga_s2am_ard_3-2-1_51JYM_2019-06-27_final.stac-item
2019-06-27 11:24:45	ga_s2am_ard_3-2-1_51JXM_2019-06-27_final.stac-item
2019-06-27 11:24:48	ga_s2am_ard_3-2-1_52JBR_2019-06-27_final.stac-item
2019-06-27 11:24:49	ga_s2am_ard_3-2-1_51JWM_2019-06-27_final.stac-item
2019-06-27 11:24:56	ga_s2am_ard_3-2-1_51JYL_2019-06-27_final.stac-item
2019-06-27 11:25:00	ga_s2am_ard_3-2-1_51JXL_2019-06-27_final.stac-item
2019-06-27 11:25:03	ga_s2am_ard_3-2-1_51JWL_2019-06-27_final.stac-item
2019-06-27 11:25:08	ga_s2am_ard_3-2-1_51JVL_2019-06-27_final.stac-item
2019-06-27 11:25:10	ga_s2am_ard_3-2-1_51JYK_2019-06-27_final.stac-item
2019-06-27 11:25:14	ga_s2am_ard_3-2-1_51JXK_2019-06-27_final.stac-item
2019-06-27 11:25:17	ga_s2am_ard_3-2-1_51JWK_2019-06-27_final.stac-item
2019-06-27 11:25:21	ga_s2am_ard_3-2-1_51JVK_2019-06-27_final.stac-item
2019-06-27 11:25:25	ga_s2am_ard_3-2-1_51JYJ_2019-06-27_final.stac-item
2019-06-27 11:25:29	ga_s2am_ard_3-2-1_51JXJ_2019-06-27_final.stac-item
2019-06-27 11:25:32	ga_s2am_ard_3-2-1_51JWJ_2019-06-27_final.stac-item
2019-06-27 11:25:35	ga_s2am_ard_3-2-1_51JVJ_2019-06-27_final.stac-item
2019-06-27 11:25:38	ga_s2am_ard_3-2-1_51JYH_2019-06-27_final.stac-item
2019-06-27 11:25:43	ga_s2am_ard_3-2-1_51JXH_2019-06-27_final.stac-item
2019-06-27 11:25:47	ga_s2am_ard_3-2-1_51JWH_2019-06-27_final.stac-item
2019-06-27 11:25:49	ga_s2am_ard_3-2-1_51JYG_2019-06-27_final.stac-item
2019-06-27 11:25:50	ga_s2am_ard_3-2-1_51JVH_2019-06-27_final.stac-item
2019-06-27 11:25:57	ga_s2am_ard_3-2-1_51JXG_2019-06-27_final.stac-item
2019-06-27 11:26:01	ga_s2am_ard_3-2-1_51JWG_2019-06-27_final.stac-item
2019-06-27 11:26:05	ga_s2am_ard_3-2-1_51JVG_2019-06-27_final.stac-item
2019-06-27 11:26:10	ga_s2am_ard_3-2-1_51JUG_2019-06-27_final.stac-item
2019-06-27 11:26:12	ga_s2am_ard_3-2-1_51JXF_2019-06-27_final.stac-item
2019-06-27 11:26:16	ga_s2am_ard_3-2-1_51JWF_2019-06-27_final.stac-item
2019-06-27 11:26:19	ga_s2am_ard_3-2-1_51JVF_2019-06-27_final.stac-item
2019-06-27 11:26:22	ga_s2am_ard_3-2-1_51JUF_2019-06-27_final.stac-item
2019-06-27 11:26:26	ga_s2am_ard_3-2-1_51HXE_2019-06-27_final.stac-item
2019-06-27 11:26:30	ga_s2am_ard_3-2-1_51HWE_2019-06-27_final.stac-item
2019-06-27 11:26:34	ga_s2am_ard_3-2-1_51HVE_2019-06-27_final.stac-item
2019-06-27 11:26:37	ga_s2am_ard_3-2-1_51HUE_2019-06-27_final.stac-item
2019-06-27 11:26:40	ga_s2am_ard_3-2-1_51HXD_2019-06-27_final.stac-item
2019-06-27 11:26:45	ga_s2am_ard_3-2-1_51HWD_2019-06-27_final.stac-item
2019-06-27 11:26:48	ga_s2am_ard_3-2-1_51HVD_2019-06-27_final.stac-item
2019-06-27 11:26:52	ga_s2am_ard_3-2-1_51HUD_2019-06-27_final.stac-item
2019-06-27 11:27:03	ga_s2am_ard_3-2-1_51HVC_2019-06-27_final.stac-item
2019-06-27 11:27:06	ga_s2am_ard_3-2-1_51HUC_2019-06-27_final.stac-item
2019-06-28 10:53:33	ga_s2am_ard_3-2-1_52KHA_2019-06-28_final.stac-item
2019-06-28 10:53:37	ga_s2am_ard_3-2-1_52KGA_2019-06-28_final.stac-item
2019-06-28 10:53:40	ga_s2am_ard_3-2-1_53KMQ_2019-06-28_final.stac-item
2019-06-28 10:53:44	ga_s2am_ard_3-2-1_53KLQ_2019-06-28_final.stac-item
2019-06-28 10:53:47	ga_s2am_ard_3-2-1_53KKQ_2019-06-28_final.stac-item
2019-06-28 10:53:47	ga_s2am_ard_3-2-1_52KHV_2019-06-28_final.stac-item
2019-06-28 10:53:51	ga_s2am_ard_3-2-1_52KGV_2019-06-28_final.stac-item
2019-06-28 10:53:54	ga_s2am_ard_3-2-1_53KMP_2019-06-28_final.stac-item
2019-06-28 10:53:58	ga_s2am_ard_3-2-1_53KLP_2019-06-28_final.stac-item
2019-06-28 10:54:02	ga_s2am_ard_3-2-1_53KKP_2019-06-28_final.stac-item
2019-06-28 10:54:02	ga_s2am_ard_3-2-1_52KHU_2019-06-28_final.stac-item
2019-06-28 10:54:04	ga_s2am_ard_3-2-1_53JMN_2019-06-28_final.stac-item
2019-06-28 10:54:05	ga_s2am_ard_3-2-1_52KGU_2019-06-28_final.stac-item
2019-06-28 10:54:13	ga_s2am_ard_3-2-1_53JLN_2019-06-28_final.stac-item
2019-06-28 10:54:16	ga_s2am_ard_3-2-1_52JHT_2019-06-28_final.stac-item
2019-06-28 10:54:16	ga_s2am_ard_3-2-1_53JKN_2019-06-28_final.stac-item
2019-06-28 10:54:20	ga_s2am_ard_3-2-1_52JGT_2019-06-28_final.stac-item
2019-06-28 10:54:26	ga_s2am_ard_3-2-1_52JFT_2019-06-28_final.stac-item
2019-06-28 10:54:27	ga_s2am_ard_3-2-1_53JLM_2019-06-28_final.stac-item
2019-06-28 10:54:31	ga_s2am_ard_3-2-1_52JHS_2019-06-28_final.stac-item
2019-06-28 10:54:31	ga_s2am_ard_3-2-1_53JKM_2019-06-28_final.stac-item
2019-06-28 10:54:34	ga_s2am_ard_3-2-1_52JGS_2019-06-28_final.stac-item
2019-06-28 10:54:38	ga_s2am_ard_3-2-1_52JFS_2019-06-28_final.stac-item
2019-06-28 10:54:42	ga_s2am_ard_3-2-1_53JLL_2019-06-28_final.stac-item
2019-06-28 10:54:45	ga_s2am_ard_3-2-1_53JKL_2019-06-28_final.stac-item
2019-06-28 10:54:49	ga_s2am_ard_3-2-1_52JGR_2019-06-28_final.stac-item
2019-06-28 10:54:52	ga_s2am_ard_3-2-1_52JFR_2019-06-28_final.stac-item
2019-06-28 10:54:56	ga_s2am_ard_3-2-1_53JLK_2019-06-28_final.stac-item
2019-06-28 10:55:00	ga_s2am_ard_3-2-1_53JKK_2019-06-28_final.stac-item
2019-06-28 10:55:03	ga_s2am_ard_3-2-1_52JGQ_2019-06-28_final.stac-item
2019-06-28 10:55:07	ga_s2am_ard_3-2-1_52JFQ_2019-06-28_final.stac-item
2019-06-28 10:55:09	ga_s2am_ard_3-2-1_53JLJ_2019-06-28_final.stac-item
2019-06-28 10:55:14	ga_s2am_ard_3-2-1_53JKJ_2019-06-28_final.stac-item
2019-06-28 10:55:18	ga_s2am_ard_3-2-1_52JGP_2019-06-28_final.stac-item
2019-06-28 10:55:20	ga_s2am_ard_3-2-1_53JLH_2019-06-28_final.stac-item
2019-06-28 10:55:21	ga_s2am_ard_3-2-1_52JFP_2019-06-28_final.stac-item
2019-06-28 10:55:27	ga_s2am_ard_3-2-1_52JEP_2019-06-28_final.stac-item
2019-06-28 10:55:29	ga_s2am_ard_3-2-1_53JKH_2019-06-28_final.stac-item
2019-06-28 10:55:32	ga_s2am_ard_3-2-1_52JGN_2019-06-28_final.stac-item
2019-06-28 10:55:36	ga_s2am_ard_3-2-1_52JFN_2019-06-28_final.stac-item
2019-06-28 10:55:39	ga_s2am_ard_3-2-1_52JEN_2019-06-28_final.stac-item
2019-06-28 10:55:44	ga_s2am_ard_3-2-1_53JKG_2019-06-28_final.stac-item
2019-06-28 10:55:46	ga_s2am_ard_3-2-1_52JGM_2019-06-28_final.stac-item
2019-06-28 10:55:50	ga_s2am_ard_3-2-1_52JFM_2019-06-28_final.stac-item
2019-06-28 10:55:54	ga_s2am_ard_3-2-1_52JEM_2019-06-28_final.stac-item
2019-06-28 10:55:58	ga_s2am_ard_3-2-1_53JKF_2019-06-28_final.stac-item
2019-06-28 10:56:01	ga_s2am_ard_3-2-1_52JGL_2019-06-28_final.stac-item
2019-06-28 10:56:05	ga_s2am_ard_3-2-1_52JFL_2019-06-28_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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