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
2019-06-01 11:54:09	ga_s2bm_ard_3-2-1_50KQV_2019-06-01_final.stac-item
2019-06-01 11:54:13	ga_s2bm_ard_3-2-1_50KPV_2019-06-01_final.stac-item
2019-06-01 11:54:16	ga_s2bm_ard_3-2-1_50KNV_2019-06-01_final.stac-item
2019-06-01 11:54:20	ga_s2bm_ard_3-2-1_50KMV_2019-06-01_final.stac-item
2019-06-09 09:33:21	ga_s2bm_ard_3-2-1_56KLV_2019-06-09_final.stac-item
2019-06-21 11:54:09	ga_s2bm_ard_3-2-1_50KQV_2019-06-21_final.stac-item
2019-06-21 11:54:12	ga_s2bm_ard_3-2-1_50KPV_2019-06-21_final.stac-item
2019-06-21 11:54:16	ga_s2bm_ard_3-2-1_50KNV_2019-06-21_final.stac-item
2019-06-21 11:54:19	ga_s2bm_ard_3-2-1_50KMV_2019-06-21_final.stac-item
2019-11-06 09:33:13	ga_s2bm_ard_3-2-1_56KLV_2019-11-06_final.stac-item
2019-11-08 11:54:00	ga_s2bm_ard_3-2-1_50KQV_2019-11-08_final.stac-item
2019-11-08 11:54:04	ga_s2bm_ard_3-2-1_50KPV_2019-11-08_final.stac-item
2019-11-08 11:54:08	ga_s2bm_ard_3-2-1_50KNV_2019-11-08_final.stac-item
2019-11-08 11:54:11	ga_s2bm_ard_3-2-1_50KMV_2019-11-08_final.stac-item
2019-11-09 11:23:49	ga_s2bm_ard_3-2-1_52KBV_2019-11-09_final.stac-item
2019-11-09 11:23:49	ga_s2bm_ard_3-2-1_51KZQ_2019-11-09_final.stac-item
2019-11-09 11:23:53	ga_s2bm_ard_3-2-1_51KYQ_2019-11-09_final.stac-item
2019-11-09 11:23:57	ga_s2bm_ard_3-2-1_51KXQ_2019-11-09_final.stac-item
2019-11-09 11:24:01	ga_s2bm_ard_3-2-1_51KWQ_2019-11-09_final.stac-item
2019-11-09 11:24:04	ga_s2bm_ard_3-2-1_51KZP_2019-11-09_final.stac-item
2019-11-09 11:24:08	ga_s2bm_ard_3-2-1_51KYP_2019-11-09_final.stac-item
2019-11-18 11:53:59	ga_s2bm_ard_3-2-1_50KQV_2019-11-18_final.stac-item
2019-11-18 11:54:03	ga_s2bm_ard_3-2-1_50KPV_2019-11-18_final.stac-item
2019-11-18 11:54:06	ga_s2bm_ard_3-2-1_50KNV_2019-11-18_final.stac-item
2019-11-18 11:54:09	ga_s2bm_ard_3-2-1_50KMV_2019-11-18_final.stac-item
2019-11-29 11:23:45	ga_s2bm_ard_3-2-1_52KBV_2019-11-29_final.stac-item
2019-11-29 11:23:45	ga_s2bm_ard_3-2-1_51KZQ_2019-11-29_final.stac-item
2019-11-29 11:23:49	ga_s2bm_ard_3-2-1_51KYQ_2019-11-29_final.stac-item
2019-11-29 11:23:53	ga_s2bm_ard_3-2-1_51KXQ_2019-11-29_final.stac-item
2019-11-29 11:23:57	ga_s2bm_ard_3-2-1_51KWQ_2019-11-29_final.stac-item
2019-11-29 11:24:00	ga_s2bm_ard_3-2-1_51KZP_2019-11-29_final.stac-item
2019-11-29 11:24:04	ga_s2bm_ard_3-2-1_51KYP_2019-11-29_final.stac-item
2019-12-01 12:04:01	ga_s2bm_ard_3-2-1_50KMV_2019-12-01_final.stac-item
2019-12-01 12:04:05	ga_s2bm_ard_3-2-1_50KLV_2019-12-01_final.stac-item
2019-12-01 12:04:08	ga_s2bm_ard_3-2-1_50KKV_2019-12-01_final.stac-item
2019-12-01 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2019-12-01_final.stac-item
2019-12-01 12:04:13	ga_s2bm_ard_3-2-1_49KGQ_2019-12-01_final.stac-item
2023-10-16 11:13:47	ga_s2bm_ard_3-2-1_52KEV_2023-10-16_final
2023-10-16 11:13:50	ga_s2bm_ard_3-2-1_52KDV_2023-10-16_final
2023-10-16 11:13:54	ga_s2bm_ard_3-2-1_52KCV_2023-10-16_final
2023-10-16 11:13:56	ga_s2bm_ard_3-2-1_51KZQ_2023-10-16_final
2023-10-16 11:13:57	ga_s2bm_ard_3-2-1_52KBV_2023-10-16_final
2023-10-16 11:14:11	ga_s2bm_ard_3-2-1_51KZP_2023-10-16_final
2023-10-17 10:43:36	ga_s2bm_ard_3-2-1_53KPQ_2023-10-17_final
2023-10-17 10:43:40	ga_s2bm_ard_3-2-1_53KNQ_2023-10-17_final
2023-10-17 10:43:43	ga_s2bm_ard_3-2-1_53KMQ_2023-10-17_final
2023-10-17 10:43:48	ga_s2bm_ard_3-2-1_53KLQ_2023-10-17_final
2023-10-19 11:23:52	ga_s2bm_ard_3-2-1_52KBV_2023-10-19_final
2023-10-19 11:23:52	ga_s2bm_ard_3-2-1_51KZQ_2023-10-19_final
2023-10-19 11:23:56	ga_s2bm_ard_3-2-1_51KYQ_2023-10-19_final
2023-10-19 11:23:59	ga_s2bm_ard_3-2-1_51KXQ_2023-10-19_final
2023-10-19 11:24:04	ga_s2bm_ard_3-2-1_51KWQ_2023-10-19_final
2023-10-19 11:24:06	ga_s2bm_ard_3-2-1_51KZP_2023-10-19_final
2023-10-19 11:24:10	ga_s2bm_ard_3-2-1_51KYP_2023-10-19_final
2023-10-20 10:53:59	ga_s2bm_ard_3-2-1_52KHU_2023-10-20_final
2023-10-20 10:54:03	ga_s2bm_ard_3-2-1_52KGU_2023-10-20_final
2023-10-24 12:14:09	ga_s2bm_ard_3-2-1_50KKV_2023-10-24_final
2023-10-24 12:14:10	ga_s2bm_ard_3-2-1_49KHQ_2023-10-24_final
2023-10-24 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2023-10-24_final
2023-10-24 12:14:18	ga_s2bm_ard_3-2-1_49KHQ_2023-10-24_final
2023-10-24 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2023-10-24_final
2023-11-09 10:53:38	ga_s2bm_ard_3-2-1_53KMQ_2023-11-09_final
2023-11-09 10:53:42	ga_s2bm_ard_3-2-1_53KLQ_2023-11-09_final
2023-11-09 10:53:45	ga_s2bm_ard_3-2-1_53KKQ_2023-11-09_final
2023-11-09 10:53:45	ga_s2bm_ard_3-2-1_52KHV_2023-11-09_final
2023-11-09 10:53:48	ga_s2bm_ard_3-2-1_52KGV_2023-11-09_final
2023-11-09 10:53:59	ga_s2bm_ard_3-2-1_52KHU_2023-11-09_final
2023-11-09 10:54:03	ga_s2bm_ard_3-2-1_52KGU_2023-11-09_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
2023-11-16 10:43:33	ga_s2bm_ard_3-2-1_53KPQ_2023-11-16_final
2023-11-16 10:43:37	ga_s2bm_ard_3-2-1_53KNQ_2023-11-16_final
2023-11-16 10:43:40	ga_s2bm_ard_3-2-1_53KMQ_2023-11-16_final
2023-11-16 10:43:45	ga_s2bm_ard_3-2-1_53KLQ_2023-11-16_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 10:13:32	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 11:53:59	ga_s2bm_ard_3-2-1_50KQV_2023-11-17_final
2023-11-17 11:54:03	ga_s2bm_ard_3-2-1_50KPV_2023-11-17_final
2023-11-17 11:54:10	ga_s2bm_ard_3-2-1_50KMV_2023-11-17_final
2023-11-22 09:23:04	ga_s2bm_ard_3-2-1_56KPV_2023-11-21_nrt
2023-11-23 10:33:23	ga_s2bm_ard_3-2-1_54KUV_2023-11-23_final
2023-11-23 10:33:26	ga_s2bm_ard_3-2-1_54KTV_2023-11-23_final
2023-11-23 10:33:26	ga_s2bm_ard_3-2-1_53KRQ_2023-11-23_final
2023-11-23 10:33:30	ga_s2bm_ard_3-2-1_53KQQ_2023-11-23_final
2023-11-23 10:33:33	ga_s2bm_ard_3-2-1_53KPQ_2023-11-23_final
2023-11-23 10:33:41	ga_s2bm_ard_3-2-1_53KRP_2023-11-23_final
2023-11-23 10:33:44	ga_s2bm_ard_3-2-1_53KQP_2023-11-23_final
2024-02-08 12:04:06	ga_s2bm_ard_3-2-1_50KMV_2024-02-08_final
2024-02-08 12:04:10	ga_s2bm_ard_3-2-1_50KLV_2024-02-08_final
2024-02-08 12:04:13	ga_s2bm_ard_3-2-1_50KKV_2024-02-08_final
2024-02-08 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2024-02-08_final
2024-02-08 12:04:18	ga_s2bm_ard_3-2-1_49KGQ_2024-02-08_final
2024-02-08 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2024-02-08_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