Search ga_s2bm_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
2019-06-09 11:13:52	ga_s2bm_ard_3-2-1_52KEV_2019-06-09_final.stac-item
2019-06-09 11:13:56	ga_s2bm_ard_3-2-1_52KDV_2019-06-09_final.stac-item
2019-06-09 11:13:59	ga_s2bm_ard_3-2-1_52KCV_2019-06-09_final.stac-item
2019-06-09 11:14:02	ga_s2bm_ard_3-2-1_51KZQ_2019-06-09_final.stac-item
2019-06-09 11:14:02	ga_s2bm_ard_3-2-1_52KBV_2019-06-09_final.stac-item
2019-06-09 11:14:13	ga_s2bm_ard_3-2-1_52KCU_2019-06-09_final.stac-item
2019-06-09 11:14:17	ga_s2bm_ard_3-2-1_51KZP_2019-06-09_final.stac-item
2019-06-09 11:14:17	ga_s2bm_ard_3-2-1_52KBU_2019-06-09_final.stac-item
2019-06-19 11:13:52	ga_s2bm_ard_3-2-1_52KEV_2019-06-19_final.stac-item
2019-06-19 11:13:56	ga_s2bm_ard_3-2-1_52KDV_2019-06-19_final.stac-item
2019-06-19 11:13:59	ga_s2bm_ard_3-2-1_52KCV_2019-06-19_final.stac-item
2019-06-19 11:14:02	ga_s2bm_ard_3-2-1_51KZQ_2019-06-19_final.stac-item
2019-06-19 11:14:02	ga_s2bm_ard_3-2-1_52KBV_2019-06-19_final.stac-item
2019-06-19 11:14:13	ga_s2bm_ard_3-2-1_52KCU_2019-06-19_final.stac-item
2019-06-19 11:14:17	ga_s2bm_ard_3-2-1_51KZP_2019-06-19_final.stac-item
2019-06-19 11:14:17	ga_s2bm_ard_3-2-1_52KBU_2019-06-19_final.stac-item
2023-11-10 10:23:27	ga_s2bm_ard_3-2-1_54KWV_2023-11-10_final
2023-11-10 10:23:31	ga_s2bm_ard_3-2-1_54KVV_2023-11-10_final
2023-11-10 10:23:34	ga_s2bm_ard_3-2-1_54KUV_2023-11-10_final
2023-11-10 10:23:39	ga_s2bm_ard_3-2-1_54KTV_2023-11-10_final
2023-11-10 10:23:41	ga_s2bm_ard_3-2-1_53KRQ_2023-11-10_final
2023-11-10 10:23:48	ga_s2bm_ard_3-2-1_54KUU_2023-11-10_final
2023-11-10 10:23:52	ga_s2bm_ard_3-2-1_54KTU_2023-11-10_final
2023-11-10 10:23:52	ga_s2bm_ard_3-2-1_53KRP_2023-11-10_final
2023-11-11 09:53:13	ga_s2bm_ard_3-2-1_55KGQ_2023-11-11_final
2023-11-11 09:53:16	ga_s2bm_ard_3-2-1_55KFQ_2023-11-11_final
2023-11-11 09:53:20	ga_s2bm_ard_3-2-1_55KEQ_2023-11-11_final
2023-11-11 09:53:23	ga_s2bm_ard_3-2-1_55KDQ_2023-11-11_final
2023-11-11 09:53:27	ga_s2bm_ard_3-2-1_55KGP_2023-11-11_final
2023-11-11 09:53:31	ga_s2bm_ard_3-2-1_55KFP_2023-11-11_final
2023-11-11 11:33:54	ga_s2bm_ard_3-2-1_51KXQ_2023-11-11_final
2023-11-11 11:33:58	ga_s2bm_ard_3-2-1_51KWQ_2023-11-11_final
2023-11-11 11:34:01	ga_s2bm_ard_3-2-1_51KVQ_2023-11-11_final
2023-11-11 11:34:04	ga_s2bm_ard_3-2-1_51KUQ_2023-11-11_final
2023-11-11 11:34:19	ga_s2bm_ard_3-2-1_51KUP_2023-11-11_final
2023-11-13 10:33:28	ga_s2bm_ard_3-2-1_54KUV_2023-11-13_final
2023-11-13 10:33:32	ga_s2bm_ard_3-2-1_54KTV_2023-11-13_final
2023-11-13 10:33:32	ga_s2bm_ard_3-2-1_53KRQ_2023-11-13_final
2023-11-13 10:33:35	ga_s2bm_ard_3-2-1_53KQQ_2023-11-13_final
2023-11-13 10:33:38	ga_s2bm_ard_3-2-1_53KPQ_2023-11-13_final
2023-11-13 10:33:40	ga_s2bm_ard_3-2-1_54KUU_2023-11-13_final
2023-11-13 10:33:42	ga_s2bm_ard_3-2-1_54KTU_2023-11-13_final
2023-11-13 10:33:42	ga_s2bm_ard_3-2-1_53KRP_2023-11-13_final
2023-11-13 10:33:44	ga_s2bm_ard_3-2-1_53KQP_2023-11-13_final
2023-11-13 10:33:44	ga_s2bm_ard_3-2-1_53KQQ_2023-11-13_final
2023-11-13 10:33:45	ga_s2bm_ard_3-2-1_53KPQ_2023-11-13_final
2023-11-13 10:33:45	ga_s2bm_ard_3-2-1_53KPP_2023-11-13_final
2023-11-13 10:33:51	ga_s2bm_ard_3-2-1_53KQP_2023-11-13_final
2023-11-13 10:33:53	ga_s2bm_ard_3-2-1_53KPP_2023-11-13_final
2023-11-13 12:14:08	ga_s2bm_ard_3-2-1_50KKV_2023-11-13_final
2023-11-13 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2023-11-13_final
2023-11-13 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2023-11-13_final
2023-11-13 12:14:17	ga_s2bm_ard_3-2-1_49KFQ_2023-11-13_nrt
2023-11-13 12:14:19	ga_s2bm_ard_3-2-1_50KKU_2023-11-13_final
2023-11-13 12:14:22	ga_s2bm_ard_3-2-1_49KHP_2023-11-13_final
2023-11-13 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2023-11-13_final
2023-11-13 12:14:31	ga_s2bm_ard_3-2-1_49KFP_2023-11-13_nrt
2023-11-15 09:33:03	ga_s2bm_ard_3-2-1_56KPV_2023-11-15_nrt
2023-11-15 09:33:06	ga_s2bm_ard_3-2-1_56KNV_2023-11-15_nrt
2023-11-15 09:33:10	ga_s2bm_ard_3-2-1_56KMV_2023-11-15_nrt
2023-11-15 09:33:13	ga_s2bm_ard_3-2-1_56KLV_2023-11-15_final
2023-11-15 09:33:28	ga_s2bm_ard_3-2-1_56KLU_2023-11-15_final
2023-11-15 11:14:09	ga_s2bm_ard_3-2-1_51KZP_2023-11-15_final
2023-11-15 11:14:09	ga_s2bm_ard_3-2-1_52KBU_2023-11-15_final
2023-11-17 10:13:18	ga_s2bm_ard_3-2-1_55KBQ_2023-11-17_final
2023-11-17 10:13:18	ga_s2bm_ard_3-2-1_54KZV_2023-11-17_final
2023-11-17 10:13:22	ga_s2bm_ard_3-2-1_54KYV_2023-11-17_final
2023-11-17 10:13:25	ga_s2bm_ard_3-2-1_54KXV_2023-11-17_final
2023-11-17 10:13:28	ga_s2bm_ard_3-2-1_54KWV_2023-11-17_final
2023-11-17 10:13:31	ga_s2bm_ard_3-2-1_55KBP_2023-11-17_final
2023-11-17 10:13:32	ga_s2bm_ard_3-2-1_54KZU_2023-11-17_final
2023-11-17 10:13:36	ga_s2bm_ard_3-2-1_54KYU_2023-11-17_final
2023-11-17 10:13:40	ga_s2bm_ard_3-2-1_54KXU_2023-11-17_final
2023-12-07 11:53:57	ga_s2bm_ard_3-2-1_50KQV_2023-12-07_final
2023-12-07 11:54:01	ga_s2bm_ard_3-2-1_50KPV_2023-12-07_final
2023-12-07 11:54:05	ga_s2bm_ard_3-2-1_50KNV_2023-12-07_final
2023-12-07 11:54:08	ga_s2bm_ard_3-2-1_50KMV_2023-12-07_final
2023-12-07 11:54:10	ga_s2bm_ard_3-2-1_50KQU_2023-12-07_final
2023-12-07 11:54:16	ga_s2bm_ard_3-2-1_50KPU_2023-12-07_final
2024-01-11 11:03:39	ga_s2bm_ard_3-2-1_52KGV_2024-01-11_final
2024-01-11 11:03:43	ga_s2bm_ard_3-2-1_52KFV_2024-01-11_final
2024-01-11 11:03:47	ga_s2bm_ard_3-2-1_52KEV_2024-01-11_final
2024-01-11 11:03:51	ga_s2bm_ard_3-2-1_52KDV_2024-01-11_final
2024-01-11 11:03:54	ga_s2bm_ard_3-2-1_52KGU_2024-01-11_final
2024-01-12 10:33:43	ga_s2bm_ard_3-2-1_53KRP_2024-01-12_final
2024-01-12 10:33:47	ga_s2bm_ard_3-2-1_53KQP_2024-01-12_final
2024-01-12 10:33:50	ga_s2bm_ard_3-2-1_53KPP_2024-01-12_final
2024-01-12 12:14:05	ga_s2bm_ard_3-2-1_50KKV_2024-01-12_final
2024-01-12 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2024-01-12_final
2024-01-12 12:14:10	ga_s2bm_ard_3-2-1_49KGQ_2024-01-12_final
2024-01-12 12:14:14	ga_s2bm_ard_3-2-1_49KFQ_2024-01-12_nrt
2024-01-12 12:14:16	ga_s2bm_ard_3-2-1_50KKU_2024-01-12_final
2024-01-12 12:14:19	ga_s2bm_ard_3-2-1_49KHP_2024-01-12_final
2024-01-12 12:14:25	ga_s2bm_ard_3-2-1_49KGP_2024-01-12_final
2024-01-12 12:14:28	ga_s2bm_ard_3-2-1_49KFP_2024-01-12_nrt
2024-01-20 09:53:10	ga_s2bm_ard_3-2-1_55KGQ_2024-01-20_final
2024-01-20 09:53:14	ga_s2bm_ard_3-2-1_55KFQ_2024-01-20_final
2024-01-20 09:53:18	ga_s2bm_ard_3-2-1_55KEQ_2024-01-20_final
2024-01-20 09:53:21	ga_s2bm_ard_3-2-1_55KDQ_2024-01-20_final
2024-01-20 09:53:25	ga_s2bm_ard_3-2-1_55KGP_2024-01-20_final

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years