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
2019-08-30 10:13:23	ga_s2bm_ard_3-2-1_55KBQ_2019-08-30_final.stac-item
2019-08-30 10:13:23	ga_s2bm_ard_3-2-1_54KZV_2019-08-30_final.stac-item
2019-08-30 10:13:27	ga_s2bm_ard_3-2-1_54KYV_2019-08-30_final.stac-item
2019-08-30 10:13:30	ga_s2bm_ard_3-2-1_54KXV_2019-08-30_final.stac-item
2019-08-30 10:13:33	ga_s2bm_ard_3-2-1_54KWV_2019-08-30_final.stac-item
2019-08-30 10:13:37	ga_s2bm_ard_3-2-1_54KZU_2019-08-30_final.stac-item
2019-09-03 09:53:14	ga_s2bm_ard_3-2-1_55KGQ_2019-09-03_final.stac-item
2019-09-03 09:53:18	ga_s2bm_ard_3-2-1_55KFQ_2019-09-03_final.stac-item
2019-09-03 09:53:21	ga_s2bm_ard_3-2-1_55KEQ_2019-09-03_final.stac-item
2019-09-03 09:53:24	ga_s2bm_ard_3-2-1_55KDQ_2019-09-03_final.stac-item
2019-09-03 11:33:55	ga_s2bm_ard_3-2-1_51KXQ_2019-09-03_final.stac-item
2019-09-03 11:33:59	ga_s2bm_ard_3-2-1_51KWQ_2019-09-03_final.stac-item
2019-09-03 11:34:03	ga_s2bm_ard_3-2-1_51KVQ_2019-09-03_final.stac-item
2019-09-03 11:34:06	ga_s2bm_ard_3-2-1_51KUQ_2019-09-03_final.stac-item
2019-09-07 11:13:46	ga_s2bm_ard_3-2-1_52KEV_2019-09-07_final.stac-item
2019-09-07 11:13:50	ga_s2bm_ard_3-2-1_52KDV_2019-09-07_final.stac-item
2019-09-07 11:13:53	ga_s2bm_ard_3-2-1_52KCV_2019-09-07_final.stac-item
2019-09-07 11:13:56	ga_s2bm_ard_3-2-1_51KZQ_2019-09-07_final.stac-item
2019-09-07 11:13:56	ga_s2bm_ard_3-2-1_52KBV_2019-09-07_final.stac-item
2019-09-14 11:03:42	ga_s2bm_ard_3-2-1_52KGV_2019-09-14_final.stac-item
2019-09-14 11:03:46	ga_s2bm_ard_3-2-1_52KFV_2019-09-14_final.stac-item
2019-09-14 11:03:49	ga_s2bm_ard_3-2-1_52KEV_2019-09-14_final.stac-item
2019-09-14 11:03:54	ga_s2bm_ard_3-2-1_52KDV_2019-09-14_final.stac-item
2019-09-15 10:33:28	ga_s2bm_ard_3-2-1_54KUV_2019-09-15_final.stac-item
2019-09-15 10:33:31	ga_s2bm_ard_3-2-1_54KTV_2019-09-15_final.stac-item
2019-09-15 10:33:31	ga_s2bm_ard_3-2-1_53KRQ_2019-09-15_final.stac-item
2019-09-15 10:33:35	ga_s2bm_ard_3-2-1_53KQQ_2019-09-15_final.stac-item
2019-09-15 10:33:38	ga_s2bm_ard_3-2-1_53KPQ_2019-09-15_final.stac-item
2019-09-15 10:33:45	ga_s2bm_ard_3-2-1_53KRP_2019-09-15_final.stac-item
2023-06-18 11:13:49	ga_s2bm_ard_3-2-1_52KEV_2023-06-18_final
2023-06-18 11:13:53	ga_s2bm_ard_3-2-1_52KDV_2023-06-18_final
2023-06-18 11:13:56	ga_s2bm_ard_3-2-1_52KCV_2023-06-18_final
2023-06-18 11:13:59	ga_s2bm_ard_3-2-1_51KZQ_2023-06-18_final
2023-06-18 11:13:59	ga_s2bm_ard_3-2-1_52KBV_2023-06-18_final
2023-06-18 11:14:14	ga_s2bm_ard_3-2-1_51KZP_2023-06-18_final
2023-06-20 10:13:23	ga_s2bm_ard_3-2-1_55KBQ_2023-06-20_final
2023-06-20 10:13:24	ga_s2bm_ard_3-2-1_54KZV_2023-06-20_final
2023-06-20 10:13:27	ga_s2bm_ard_3-2-1_54KYV_2023-06-20_final
2023-06-20 10:13:31	ga_s2bm_ard_3-2-1_54KXV_2023-06-20_final
2023-06-20 10:13:34	ga_s2bm_ard_3-2-1_54KWV_2023-06-20_final
2023-06-20 10:13:38	ga_s2bm_ard_3-2-1_54KZU_2023-06-20_final
2023-06-22 10:53:40	ga_s2bm_ard_3-2-1_53KMQ_2023-06-22_final
2023-06-22 10:53:43	ga_s2bm_ard_3-2-1_53KLQ_2023-06-22_final
2023-06-22 10:53:47	ga_s2bm_ard_3-2-1_53KKQ_2023-06-22_final
2023-06-22 10:53:47	ga_s2bm_ard_3-2-1_52KHV_2023-06-22_final
2023-06-22 10:53:50	ga_s2bm_ard_3-2-1_52KGV_2023-06-22_final
2023-06-22 10:54:01	ga_s2bm_ard_3-2-1_52KHU_2023-06-22_final
2023-06-23 10:23:29	ga_s2bm_ard_3-2-1_54KWV_2023-06-23_final
2023-06-23 10:23:33	ga_s2bm_ard_3-2-1_54KVV_2023-06-23_final
2023-06-23 10:23:36	ga_s2bm_ard_3-2-1_54KUV_2023-06-23_final
2023-06-23 10:23:41	ga_s2bm_ard_3-2-1_54KTV_2023-06-23_final
2023-06-23 10:23:44	ga_s2bm_ard_3-2-1_53KRQ_2023-06-23_final
2023-06-23 10:23:54	ga_s2bm_ard_3-2-1_53KRP_2023-06-23_final
2023-06-23 12:04:10	ga_s2bm_ard_3-2-1_50KMV_2023-06-23_final
2023-06-23 12:04:14	ga_s2bm_ard_3-2-1_50KLV_2023-06-23_final
2023-06-23 12:04:17	ga_s2bm_ard_3-2-1_50KKV_2023-06-23_final
2023-06-23 12:04:17	ga_s2bm_ard_3-2-1_49KHQ_2023-06-23_final
2023-06-23 12:04:22	ga_s2bm_ard_3-2-1_49KGQ_2023-06-23_final
2023-06-23 12:04:32	ga_s2bm_ard_3-2-1_49KHP_2023-06-23_final
2023-06-24 09:53:15	ga_s2bm_ard_3-2-1_55KGQ_2023-06-24_final
2023-06-24 09:53:19	ga_s2bm_ard_3-2-1_55KFQ_2023-06-24_final
2023-06-24 09:53:22	ga_s2bm_ard_3-2-1_55KEQ_2023-06-24_final
2023-06-24 09:53:25	ga_s2bm_ard_3-2-1_55KDQ_2023-06-24_final
2023-06-24 11:33:57	ga_s2bm_ard_3-2-1_51KXQ_2023-06-24_final
2023-06-24 11:34:00	ga_s2bm_ard_3-2-1_51KWQ_2023-06-24_final
2023-06-24 11:34:04	ga_s2bm_ard_3-2-1_51KVQ_2023-06-24_final
2023-06-24 11:34:07	ga_s2bm_ard_3-2-1_51KUQ_2023-06-24_final
2023-06-25 09:23:12	ga_s2bm_ard_3-2-1_56KPV_2023-06-24_nrt
2023-06-25 11:03:46	ga_s2bm_ard_3-2-1_52KGV_2023-06-25_final
2023-06-25 11:03:50	ga_s2bm_ard_3-2-1_52KFV_2023-06-25_final
2023-06-25 11:03:53	ga_s2bm_ard_3-2-1_52KEV_2023-06-25_final
2023-06-25 11:03:58	ga_s2bm_ard_3-2-1_52KDV_2023-06-25_final
2023-06-26 10:33:32	ga_s2bm_ard_3-2-1_54KUV_2023-06-26_final
2023-06-26 10:33:35	ga_s2bm_ard_3-2-1_54KTV_2023-06-26_final
2023-06-26 10:33:36	ga_s2bm_ard_3-2-1_53KRQ_2023-06-26_final
2023-06-26 10:33:39	ga_s2bm_ard_3-2-1_53KQQ_2023-06-26_final
2023-06-26 10:33:42	ga_s2bm_ard_3-2-1_53KPQ_2023-06-26_final
2023-06-26 10:33:50	ga_s2bm_ard_3-2-1_53KRP_2023-06-26_final
2023-07-05 11:03:47	ga_s2bm_ard_3-2-1_52KGV_2023-07-05_final
2023-07-05 11:03:51	ga_s2bm_ard_3-2-1_52KFV_2023-07-05_final
2023-07-05 11:03:54	ga_s2bm_ard_3-2-1_52KEV_2023-07-05_final
2023-07-05 11:03:59	ga_s2bm_ard_3-2-1_52KDV_2023-07-05_final
2023-07-06 12:14:13	ga_s2bm_ard_3-2-1_50KKV_2023-07-06_final
2023-07-06 12:14:14	ga_s2bm_ard_3-2-1_49KHQ_2023-07-06_final
2023-07-06 12:14:18	ga_s2bm_ard_3-2-1_49KGQ_2023-07-06_final
2023-07-06 12:14:22	ga_s2bm_ard_3-2-1_49KFQ_2023-07-06_nrt
2023-07-07 10:03:22	ga_s2bm_ard_3-2-1_55KDQ_2023-07-07_final
2023-07-07 10:03:26	ga_s2bm_ard_3-2-1_55KCQ_2023-07-07_final
2023-07-07 10:03:29	ga_s2bm_ard_3-2-1_55KBQ_2023-07-07_final
2023-07-07 10:03:29	ga_s2bm_ard_3-2-1_54KZV_2023-07-07_final
2023-07-07 10:03:37	ga_s2bm_ard_3-2-1_54KYV_2023-07-07_final
2023-07-07 10:03:44	ga_s2bm_ard_3-2-1_54KZU_2023-07-07_final
2023-07-07 11:44:03	ga_s2bm_ard_3-2-1_51KUQ_2023-07-07_final
2023-07-07 11:44:07	ga_s2bm_ard_3-2-1_50KRV_2023-07-07_final
2023-07-07 11:44:21	ga_s2bm_ard_3-2-1_50KRU_2023-07-07_final
2023-07-10 10:13:24	ga_s2bm_ard_3-2-1_55KBQ_2023-07-10_final
2023-07-10 10:13:24	ga_s2bm_ard_3-2-1_54KZV_2023-07-10_final
2023-07-10 10:13:28	ga_s2bm_ard_3-2-1_54KYV_2023-07-10_final
2023-07-10 10:13:32	ga_s2bm_ard_3-2-1_54KXV_2023-07-10_final
2023-07-10 10:13:35	ga_s2bm_ard_3-2-1_54KWV_2023-07-10_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