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
2019-09-20 11:22:00	ga_s2bm_ard_3-2-1_52KDG_2019-09-20_final.stac-item
2019-09-20 11:22:04	ga_s2bm_ard_3-2-1_52KCG_2019-09-20_final.stac-item
2019-09-20 11:22:07	ga_s2bm_ard_3-2-1_52KBG_2019-09-20_final.stac-item
2019-09-20 11:22:08	ga_s2bm_ard_3-2-1_51KZB_2019-09-20_final.stac-item
2019-09-20 11:22:11	ga_s2bm_ard_3-2-1_51KYB_2019-09-20_final.stac-item
2019-09-24 11:02:00	ga_s2bm_ard_3-2-1_52KGG_2019-09-24_final.stac-item
2019-09-24 11:02:03	ga_s2bm_ard_3-2-1_52KFG_2019-09-24_final.stac-item
2019-09-24 11:02:11	ga_s2bm_ard_3-2-1_52KHF_2019-09-24_final.stac-item
2019-09-24 11:02:15	ga_s2bm_ard_3-2-1_52KGF_2019-09-24_final.stac-item
2019-09-26 11:42:09	ga_s2bm_ard_3-2-1_51KWB_2019-09-26_final.stac-item
2019-09-26 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2019-09-26_final.stac-item
2023-11-06 10:41:46	ga_s2bm_ard_3-2-1_54KTG_2023-11-06_final
2023-11-06 10:41:48	ga_s2bm_ard_3-2-1_53KRB_2023-11-06_final
2023-11-06 10:41:52	ga_s2bm_ard_3-2-1_53KQB_2023-11-06_final
2023-11-06 10:41:55	ga_s2bm_ard_3-2-1_53KPB_2023-11-06_final
2023-11-06 10:41:58	ga_s2bm_ard_3-2-1_53KNB_2023-11-06_final
2023-11-06 10:42:02	ga_s2bm_ard_3-2-1_53KRA_2023-11-06_final
2023-11-06 10:42:06	ga_s2bm_ard_3-2-1_53KQA_2023-11-06_final
2023-11-07 10:11:36	ga_s2bm_ard_3-2-1_55KCB_2023-11-07_final
2023-11-07 10:11:40	ga_s2bm_ard_3-2-1_55KBB_2023-11-07_final
2023-11-07 10:11:41	ga_s2bm_ard_3-2-1_54KZG_2023-11-07_final
2023-11-07 10:11:44	ga_s2bm_ard_3-2-1_54KYG_2023-11-07_final
2023-11-07 10:11:55	ga_s2bm_ard_3-2-1_54KZF_2023-11-07_final
2023-11-07 10:11:59	ga_s2bm_ard_3-2-1_54KYF_2023-11-07_final
2023-11-10 10:21:39	ga_s2bm_ard_3-2-1_54KYG_2023-11-10_final
2023-11-10 10:21:42	ga_s2bm_ard_3-2-1_54KXG_2023-11-10_final
2023-11-10 10:21:46	ga_s2bm_ard_3-2-1_54KWG_2023-11-10_final
2023-11-10 10:21:49	ga_s2bm_ard_3-2-1_54KVG_2023-11-10_final
2023-11-14 11:42:09	ga_s2bm_ard_3-2-1_51KWB_2023-11-14_final
2023-11-14 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2023-11-14_final
2023-11-14 11:42:17	ga_s2bm_ard_3-2-1_51KUB_2023-11-14_final
2023-11-14 11:42:20	ga_s2bm_ard_3-2-1_51KTB_2023-11-14_nrt
2023-11-14 11:42:21	ga_s2bm_ard_3-2-1_50KRG_2023-11-14_nrt
2023-11-14 11:42:35	ga_s2bm_ard_3-2-1_50KRF_2023-11-14_nrt
2023-11-15 11:11:59	ga_s2bm_ard_3-2-1_52KFG_2023-11-15_final
2023-11-15 11:12:03	ga_s2bm_ard_3-2-1_52KEG_2023-11-15_final
2023-11-15 11:12:06	ga_s2bm_ard_3-2-1_52KDG_2023-11-15_final
2023-11-15 11:12:10	ga_s2bm_ard_3-2-1_52KCG_2023-11-15_final
2023-11-22 11:01:48	ga_s2bm_ard_3-2-1_53KLB_2023-11-22_final
2023-11-22 11:01:52	ga_s2bm_ard_3-2-1_53KKB_2023-11-22_final
2023-11-22 11:01:53	ga_s2bm_ard_3-2-1_52KHG_2023-11-22_final
2023-11-22 11:01:56	ga_s2bm_ard_3-2-1_52KGG_2023-11-22_final
2023-11-22 11:01:59	ga_s2bm_ard_3-2-1_52KFG_2023-11-22_final
2023-11-22 11:02:06	ga_s2bm_ard_3-2-1_52KHF_2023-11-22_final
2023-11-22 11:02:07	ga_s2bm_ard_3-2-1_52KGF_2023-11-22_final
2023-11-23 10:31:44	ga_s2bm_ard_3-2-1_54KTG_2023-11-23_final
2023-11-23 10:31:45	ga_s2bm_ard_3-2-1_53KRB_2023-11-23_final
2023-11-23 10:32:00	ga_s2bm_ard_3-2-1_53KRA_2023-11-23_final
2023-11-24 10:01:24	ga_s2bm_ard_3-2-1_55KFB_2023-11-24_final
2023-11-24 10:01:27	ga_s2bm_ard_3-2-1_55KEB_2023-11-24_final
2023-11-24 10:01:30	ga_s2bm_ard_3-2-1_55KDB_2023-11-24_final
2023-11-24 10:01:33	ga_s2bm_ard_3-2-1_55KCB_2023-11-24_final
2023-11-24 11:42:04	ga_s2bm_ard_3-2-1_51KWB_2023-11-24_final
2023-11-24 11:42:08	ga_s2bm_ard_3-2-1_51KVB_2023-11-24_final
2023-11-24 11:42:11	ga_s2bm_ard_3-2-1_51KUB_2023-11-24_final
2023-11-24 11:42:15	ga_s2bm_ard_3-2-1_51KTB_2023-11-24_nrt
2023-11-24 11:42:15	ga_s2bm_ard_3-2-1_50KRG_2023-11-24_nrt
2023-11-24 11:42:30	ga_s2bm_ard_3-2-1_50KRF_2023-11-24_nrt
2023-11-30 10:21:37	ga_s2bm_ard_3-2-1_54KXG_2023-11-30_final
2023-11-30 10:21:41	ga_s2bm_ard_3-2-1_54KWG_2023-11-30_final
2023-12-01 11:32:04	ga_s2bm_ard_3-2-1_51KYB_2023-12-01_final
2023-12-01 11:32:08	ga_s2bm_ard_3-2-1_51KXB_2023-12-01_final
2023-12-01 11:32:12	ga_s2bm_ard_3-2-1_51KWB_2023-12-01_final
2023-12-01 11:32:17	ga_s2bm_ard_3-2-1_51KVB_2023-12-01_final
2023-12-21 09:51:26	ga_s2bm_ard_3-2-1_56KKG_2023-12-21_final
2023-12-21 09:51:27	ga_s2bm_ard_3-2-1_55KHB_2023-12-21_final
2023-12-21 09:51:31	ga_s2bm_ard_3-2-1_55KGB_2023-12-21_final
2023-12-21 09:51:34	ga_s2bm_ard_3-2-1_55KFB_2023-12-21_final
2023-12-21 09:51:41	ga_s2bm_ard_3-2-1_55KHA_2023-12-21_nrt
2023-12-21 09:51:45	ga_s2bm_ard_3-2-1_55KGA_2023-12-21_nrt
2023-12-24 10:01:30	ga_s2bm_ard_3-2-1_55KFB_2023-12-24_final
2023-12-24 10:01:33	ga_s2bm_ard_3-2-1_55KEB_2023-12-24_final
2023-12-24 10:01:37	ga_s2bm_ard_3-2-1_55KDB_2023-12-24_final
2023-12-24 10:01:39	ga_s2bm_ard_3-2-1_55KCB_2023-12-24_final
2023-12-25 09:31:27	ga_s2bm_ard_3-2-1_56KPG_2023-12-25_nrt
2023-12-25 09:31:29	ga_s2bm_ard_3-2-1_56KNG_2023-12-25_nrt
2023-12-26 10:41:44	ga_s2bm_ard_3-2-1_54KTG_2023-12-26_final
2023-12-26 10:41:47	ga_s2bm_ard_3-2-1_53KRB_2023-12-26_final
2023-12-26 10:41:50	ga_s2bm_ard_3-2-1_53KQB_2023-12-26_final
2023-12-26 10:41:54	ga_s2bm_ard_3-2-1_53KPB_2023-12-26_final
2023-12-26 10:41:57	ga_s2bm_ard_3-2-1_53KNB_2023-12-26_final
2023-12-26 10:42:01	ga_s2bm_ard_3-2-1_53KRA_2023-12-26_final
2023-12-26 10:42:05	ga_s2bm_ard_3-2-1_53KQA_2023-12-26_final
2024-01-01 11:01:53	ga_s2bm_ard_3-2-1_53KLB_2024-01-01_final
2024-01-01 11:01:57	ga_s2bm_ard_3-2-1_53KKB_2024-01-01_final
2024-01-01 11:01:58	ga_s2bm_ard_3-2-1_52KHG_2024-01-01_final
2024-01-01 11:02:01	ga_s2bm_ard_3-2-1_52KGG_2024-01-01_final
2024-01-01 11:02:04	ga_s2bm_ard_3-2-1_52KFG_2024-01-01_final
2024-01-01 11:02:12	ga_s2bm_ard_3-2-1_52KHF_2024-01-01_final
2024-01-01 11:02:16	ga_s2bm_ard_3-2-1_52KGF_2024-01-01_final
2024-01-02 10:31:43	ga_s2bm_ard_3-2-1_54KVG_2024-01-02_final
2024-01-02 10:31:47	ga_s2bm_ard_3-2-1_54KUG_2024-01-02_final
2024-01-02 10:31:50	ga_s2bm_ard_3-2-1_54KTG_2024-01-02_final
2024-01-02 10:31:51	ga_s2bm_ard_3-2-1_53KRB_2024-01-02_final
2024-01-02 10:32:05	ga_s2bm_ard_3-2-1_53KRA_2024-01-02_final
2024-01-03 10:01:29	ga_s2bm_ard_3-2-1_55KFB_2024-01-03_final
2024-01-03 10:01:33	ga_s2bm_ard_3-2-1_55KEB_2024-01-03_final
2024-01-03 10:01:36	ga_s2bm_ard_3-2-1_55KDB_2024-01-03_final
2024-01-03 10:01:39	ga_s2bm_ard_3-2-1_55KCB_2024-01-03_final
2024-01-03 11:42:10	ga_s2bm_ard_3-2-1_51KWB_2024-01-03_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