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
2019-05-03 10:36:21	ga_s2am_ard_3-2-1_53HPD_2019-05-03_final.stac-item
2019-05-03 10:36:25	ga_s2am_ard_3-2-1_53HND_2019-05-03_final.stac-item
2019-05-03 10:36:28	ga_s2am_ard_3-2-1_53HMD_2019-05-03_final.stac-item
2019-05-03 10:36:32	ga_s2am_ard_3-2-1_53HLD_2019-05-03_final.stac-item
2019-05-03 10:36:36	ga_s2am_ard_3-2-1_53HPC_2019-05-03_final.stac-item
2019-05-03 10:36:39	ga_s2am_ard_3-2-1_53HNC_2019-05-03_final.stac-item
2019-05-03 10:36:50	ga_s2am_ard_3-2-1_53HPB_2019-05-03_final.stac-item
2019-05-03 10:36:54	ga_s2am_ard_3-2-1_53HNB_2019-05-03_final.stac-item
2019-05-03 10:37:02	ga_s2am_ard_3-2-1_53HPA_2019-05-03_final.stac-item
2019-05-03 12:13:43	ga_s2am_ard_3-2-1_50KKB_2019-05-03_final.stac-item
2019-05-03 12:13:58	ga_s2am_ard_3-2-1_50KKA_2019-05-03_final.stac-item
2019-05-03 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-03_final.stac-item
2019-05-03 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-05-03_final.stac-item
2019-05-03 12:14:11	ga_s2am_ard_3-2-1_50KKV_2019-05-03_final.stac-item
2019-05-03 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-05-03_final.stac-item
2019-05-03 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-05-03_final.stac-item
2019-05-03 12:14:22	ga_s2am_ard_3-2-1_50KKU_2019-05-03_final.stac-item
2019-05-03 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-05-03_final.stac-item
2019-05-03 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-05-03_final.stac-item
2019-05-03 12:14:35	ga_s2am_ard_3-2-1_49JHN_2019-05-03_final.stac-item
2019-05-03 12:14:45	ga_s2am_ard_3-2-1_49JGN_2019-05-03_final.stac-item
2019-05-03 12:14:49	ga_s2am_ard_3-2-1_49JFN_2019-05-03_final.stac-item
2019-05-03 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-05-03_final.stac-item
2019-05-03 12:15:03	ga_s2am_ard_3-2-1_49JFM_2019-05-03_final.stac-item
2019-05-03 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-05-03_final.stac-item
2019-05-03 12:15:23	ga_s2am_ard_3-2-1_49JGK_2019-05-03_final.stac-item
2019-05-04 10:02:45	ga_s2am_ard_3-2-1_54KZC_2019-05-04_final.stac-item
2019-05-04 10:02:58	ga_s2am_ard_3-2-1_54KZB_2019-05-04_final.stac-item
2019-05-04 10:03:13	ga_s2am_ard_3-2-1_54KZA_2019-05-04_final.stac-item
2019-05-04 10:03:28	ga_s2am_ard_3-2-1_54KZV_2019-05-04_final.stac-item
2019-05-04 10:03:42	ga_s2am_ard_3-2-1_54KZU_2019-05-04_final.stac-item
2019-05-04 10:03:46	ga_s2am_ard_3-2-1_54KYU_2019-05-04_final.stac-item
2019-05-04 10:03:53	ga_s2am_ard_3-2-1_55JCN_2019-05-04_final.stac-item
2019-05-04 10:03:56	ga_s2am_ard_3-2-1_54JZT_2019-05-04_final.stac-item
2019-05-04 10:03:57	ga_s2am_ard_3-2-1_55JBN_2019-05-04_final.stac-item
2019-05-04 10:04:00	ga_s2am_ard_3-2-1_54JYT_2019-05-04_final.stac-item
2019-05-04 10:04:08	ga_s2am_ard_3-2-1_55JCM_2019-05-04_final.stac-item
2019-05-04 10:04:11	ga_s2am_ard_3-2-1_54JZS_2019-05-04_final.stac-item
2019-05-04 10:04:11	ga_s2am_ard_3-2-1_55JBM_2019-05-04_final.stac-item
2019-05-04 10:04:14	ga_s2am_ard_3-2-1_54JYS_2019-05-04_final.stac-item
2019-05-04 10:04:22	ga_s2am_ard_3-2-1_55JCL_2019-05-04_final.stac-item
2019-05-04 10:04:26	ga_s2am_ard_3-2-1_55JBL_2019-05-04_final.stac-item
2019-05-04 10:04:29	ga_s2am_ard_3-2-1_54JYR_2019-05-04_final.stac-item
2019-05-04 10:04:36	ga_s2am_ard_3-2-1_54JXR_2019-05-04_final.stac-item
2019-05-04 10:04:37	ga_s2am_ard_3-2-1_55JCK_2019-05-04_final.stac-item
2019-05-04 10:04:40	ga_s2am_ard_3-2-1_55JBK_2019-05-04_final.stac-item
2019-05-04 10:04:43	ga_s2am_ard_3-2-1_54JYQ_2019-05-04_final.stac-item
2019-05-04 10:04:47	ga_s2am_ard_3-2-1_54JXQ_2019-05-04_final.stac-item
2019-05-04 10:04:51	ga_s2am_ard_3-2-1_55JCJ_2019-05-04_final.stac-item
2019-05-04 10:04:55	ga_s2am_ard_3-2-1_55JBJ_2019-05-04_final.stac-item
2019-05-04 10:04:58	ga_s2am_ard_3-2-1_54JYP_2019-05-04_final.stac-item
2019-05-04 10:05:01	ga_s2am_ard_3-2-1_54JXP_2019-05-04_final.stac-item
2019-05-04 10:05:06	ga_s2am_ard_3-2-1_55JCH_2019-05-04_final.stac-item
2019-05-04 10:05:09	ga_s2am_ard_3-2-1_55JBH_2019-05-04_final.stac-item
2019-05-04 10:05:12	ga_s2am_ard_3-2-1_54JYN_2019-05-04_final.stac-item
2019-05-04 10:05:16	ga_s2am_ard_3-2-1_54JXN_2019-05-04_final.stac-item
2019-05-04 10:05:20	ga_s2am_ard_3-2-1_55JCG_2019-05-04_final.stac-item
2019-05-04 10:05:24	ga_s2am_ard_3-2-1_55JBG_2019-05-04_final.stac-item
2019-05-04 10:05:27	ga_s2am_ard_3-2-1_54JYM_2019-05-04_final.stac-item
2019-05-04 10:05:30	ga_s2am_ard_3-2-1_54JXM_2019-05-04_final.stac-item
2019-05-04 10:05:33	ga_s2am_ard_3-2-1_55JCF_2019-05-04_final.stac-item
2019-05-04 10:05:37	ga_s2am_ard_3-2-1_54JWM_2019-05-04_final.stac-item
2019-05-04 10:05:38	ga_s2am_ard_3-2-1_55JBF_2019-05-04_final.stac-item
2019-05-04 10:05:41	ga_s2am_ard_3-2-1_54JYL_2019-05-04_final.stac-item
2019-05-04 10:05:43	ga_s2am_ard_3-2-1_55HCE_2019-05-04_final.stac-item
2019-05-04 10:05:45	ga_s2am_ard_3-2-1_54JXL_2019-05-04_final.stac-item
2019-05-04 10:05:49	ga_s2am_ard_3-2-1_54JWL_2019-05-04_final.stac-item
2019-05-04 10:05:53	ga_s2am_ard_3-2-1_55HBE_2019-05-04_final.stac-item
2019-05-04 10:05:56	ga_s2am_ard_3-2-1_54HYK_2019-05-04_final.stac-item
2019-05-04 10:05:59	ga_s2am_ard_3-2-1_54HXK_2019-05-04_final.stac-item
2019-05-04 10:06:03	ga_s2am_ard_3-2-1_54HWK_2019-05-04_final.stac-item
2019-05-04 10:06:08	ga_s2am_ard_3-2-1_55HBD_2019-05-04_final.stac-item
2019-05-04 10:06:10	ga_s2am_ard_3-2-1_54HYJ_2019-05-04_final.stac-item
2019-05-04 10:06:14	ga_s2am_ard_3-2-1_54HXJ_2019-05-04_final.stac-item
2019-05-04 10:06:17	ga_s2am_ard_3-2-1_54HWJ_2019-05-04_final.stac-item
2019-05-04 10:06:22	ga_s2am_ard_3-2-1_55HBC_2019-05-04_final.stac-item
2019-05-04 10:06:24	ga_s2am_ard_3-2-1_54HYH_2019-05-04_final.stac-item
2019-05-04 10:06:28	ga_s2am_ard_3-2-1_54HXH_2019-05-04_final.stac-item
2019-05-04 10:06:32	ga_s2am_ard_3-2-1_54HWH_2019-05-04_final.stac-item
2019-05-04 10:06:36	ga_s2am_ard_3-2-1_55HBB_2019-05-04_final.stac-item
2019-05-04 10:06:38	ga_s2am_ard_3-2-1_54HVH_2019-05-04_final.stac-item
2019-05-04 10:06:39	ga_s2am_ard_3-2-1_54HYG_2019-05-04_final.stac-item
2019-05-04 10:06:43	ga_s2am_ard_3-2-1_54HXG_2019-05-04_final.stac-item
2019-05-04 10:06:46	ga_s2am_ard_3-2-1_54HWG_2019-05-04_final.stac-item
2019-05-04 10:06:49	ga_s2am_ard_3-2-1_55HBA_2019-05-04_final.stac-item
2019-05-04 10:06:50	ga_s2am_ard_3-2-1_54HVG_2019-05-04_final.stac-item
2019-05-04 10:06:53	ga_s2am_ard_3-2-1_54HYF_2019-05-04_final.stac-item
2019-05-04 10:06:57	ga_s2am_ard_3-2-1_54HXF_2019-05-04_final.stac-item
2019-05-04 10:06:59	ga_s2am_ard_3-2-1_55HBV_2019-05-04_final.stac-item
2019-05-04 10:07:01	ga_s2am_ard_3-2-1_54HWF_2019-05-04_final.stac-item
2019-05-04 10:07:04	ga_s2am_ard_3-2-1_54HVF_2019-05-04_final.stac-item
2019-05-04 10:07:07	ga_s2am_ard_3-2-1_54HYE_2019-05-04_final.stac-item
2019-05-04 10:07:11	ga_s2am_ard_3-2-1_54HXE_2019-05-04_final.stac-item
2019-05-04 10:07:15	ga_s2am_ard_3-2-1_54HWE_2019-05-04_final.stac-item
2019-05-04 10:07:18	ga_s2am_ard_3-2-1_54HYD_2019-05-04_final.stac-item
2019-05-04 10:07:19	ga_s2am_ard_3-2-1_54HVE_2019-05-04_final.stac-item
2019-05-04 10:07:26	ga_s2am_ard_3-2-1_54HXD_2019-05-04_final.stac-item
2019-05-04 10:07:30	ga_s2am_ard_3-2-1_54HWD_2019-05-04_final.stac-item
2019-05-04 10:07:33	ga_s2am_ard_3-2-1_54HVD_2019-05-04_final.stac-item
2019-05-04 10:07:40	ga_s2am_ard_3-2-1_54HXC_2019-05-04_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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