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
2019-01-09 10:03:51	ga_s2bm_ard_3-2-1_54JZT_2019-01-09_final.stac-item
2019-01-09 10:03:55	ga_s2bm_ard_3-2-1_54JYT_2019-01-09_final.stac-item
2019-01-11 10:43:47	ga_s2bm_ard_3-2-1_53KPP_2019-01-11_final.stac-item
2019-01-11 10:43:51	ga_s2bm_ard_3-2-1_53KNP_2019-01-11_final.stac-item
2019-01-11 10:43:54	ga_s2bm_ard_3-2-1_53KMP_2019-01-11_final.stac-item
2019-01-11 10:43:57	ga_s2bm_ard_3-2-1_53KLP_2019-01-11_final.stac-item
2019-01-12 10:13:32	ga_s2bm_ard_3-2-1_55KBP_2019-01-12_final.stac-item
2019-01-12 10:13:32	ga_s2bm_ard_3-2-1_54KZU_2019-01-12_final.stac-item
2019-01-12 10:13:37	ga_s2bm_ard_3-2-1_54KYU_2019-01-12_final.stac-item
2019-01-12 10:13:40	ga_s2bm_ard_3-2-1_54KXU_2019-01-12_final.stac-item
2019-01-12 10:13:44	ga_s2bm_ard_3-2-1_54KWU_2019-01-12_final.stac-item
2019-01-12 10:13:44	ga_s2bm_ard_3-2-1_54JZT_2019-01-12_final.stac-item
2019-01-12 10:13:51	ga_s2bm_ard_3-2-1_54JYT_2019-01-12_final.stac-item
2019-01-15 10:23:39	ga_s2bm_ard_3-2-1_54KWU_2019-01-15_final.stac-item
2019-01-15 10:23:43	ga_s2bm_ard_3-2-1_54KVU_2019-01-15_final.stac-item
2019-01-15 10:23:46	ga_s2bm_ard_3-2-1_54KUU_2019-01-15_final.stac-item
2019-01-15 10:23:49	ga_s2bm_ard_3-2-1_54KTU_2019-01-15_final.stac-item
2019-01-15 10:23:50	ga_s2bm_ard_3-2-1_53KRP_2019-01-15_final.stac-item
2019-01-15 10:24:03	ga_s2bm_ard_3-2-1_53JRN_2019-01-15_final.stac-item
2019-01-25 12:04:21	ga_s2bm_ard_3-2-1_50KMU_2019-01-25_final.stac-item
2019-01-25 12:04:25	ga_s2bm_ard_3-2-1_50KLU_2019-01-25_final.stac-item
2019-01-25 12:04:28	ga_s2bm_ard_3-2-1_49KHP_2019-01-25_final.stac-item
2019-01-25 12:04:28	ga_s2bm_ard_3-2-1_50KKU_2019-01-25_final.stac-item
2019-01-25 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2019-01-25_final.stac-item
2019-01-25 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2019-01-25_final.stac-item
2019-01-25 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2019-01-25_final.stac-item
2019-01-26 11:34:05	ga_s2bm_ard_3-2-1_51KXP_2019-01-26_final.stac-item
2019-01-26 11:34:11	ga_s2bm_ard_3-2-1_51KWP_2019-01-26_final.stac-item
2019-01-26 11:34:14	ga_s2bm_ard_3-2-1_51KVP_2019-01-26_final.stac-item
2019-01-26 11:34:18	ga_s2bm_ard_3-2-1_51KUP_2019-01-26_final.stac-item
2019-01-29 11:44:13	ga_s2bm_ard_3-2-1_51KUP_2019-01-29_final.stac-item
2019-01-29 11:44:16	ga_s2bm_ard_3-2-1_50KRU_2019-01-29_final.stac-item
2019-01-29 11:44:16	ga_s2bm_ard_3-2-1_51KTP_2019-01-29_final.stac-item
2019-01-29 11:44:20	ga_s2bm_ard_3-2-1_50KQU_2019-01-29_final.stac-item
2019-01-29 11:44:23	ga_s2bm_ard_3-2-1_50KPU_2019-01-29_final.stac-item
2019-01-29 11:44:31	ga_s2bm_ard_3-2-1_50JRT_2019-01-29_final.stac-item
2019-01-29 11:44:35	ga_s2bm_ard_3-2-1_50JQT_2019-01-29_final.stac-item
2019-02-01 10:13:33	ga_s2bm_ard_3-2-1_55KBP_2019-02-01_final.stac-item
2019-02-01 10:13:34	ga_s2bm_ard_3-2-1_54KZU_2019-02-01_final.stac-item
2019-02-01 10:13:38	ga_s2bm_ard_3-2-1_54KYU_2019-02-01_final.stac-item
2019-02-01 10:13:41	ga_s2bm_ard_3-2-1_54KXU_2019-02-01_final.stac-item
2019-02-01 10:13:45	ga_s2bm_ard_3-2-1_54KWU_2019-02-01_final.stac-item
2019-02-01 10:13:46	ga_s2bm_ard_3-2-1_54JZT_2019-02-01_final.stac-item
2019-02-01 10:13:52	ga_s2bm_ard_3-2-1_54JYT_2019-02-01_final.stac-item
2019-02-01 11:54:14	ga_s2bm_ard_3-2-1_50KQU_2019-02-01_final.stac-item
2019-02-01 11:54:19	ga_s2bm_ard_3-2-1_50KPU_2019-02-01_final.stac-item
2019-02-01 11:54:23	ga_s2bm_ard_3-2-1_50KNU_2019-02-01_final.stac-item
2019-02-01 11:54:26	ga_s2bm_ard_3-2-1_50KMU_2019-02-01_final.stac-item
2019-02-01 11:54:34	ga_s2bm_ard_3-2-1_50KLU_2019-02-01_final.stac-item
2019-02-07 10:33:41	ga_s2bm_ard_3-2-1_54KUU_2019-02-07_final.stac-item
2019-02-07 10:33:46	ga_s2bm_ard_3-2-1_54KTU_2019-02-07_final.stac-item
2019-02-07 10:33:46	ga_s2bm_ard_3-2-1_53KRP_2019-02-07_final.stac-item
2019-02-07 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2019-02-07_final.stac-item
2019-02-07 10:33:53	ga_s2bm_ard_3-2-1_53KPP_2019-02-07_final.stac-item
2019-02-07 10:34:00	ga_s2bm_ard_3-2-1_53JRN_2019-02-07_final.stac-item
2019-02-07 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2019-02-07_final.stac-item
2019-02-07 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-02-07_final.stac-item
2019-02-07 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2019-02-07_final.stac-item
2019-02-07 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-02-07_final.stac-item
2019-02-08 10:03:32	ga_s2bm_ard_3-2-1_55KDP_2019-02-08_final.stac-item
2019-02-08 10:03:35	ga_s2bm_ard_3-2-1_55KCP_2019-02-08_final.stac-item
2019-02-08 10:03:38	ga_s2bm_ard_3-2-1_55KBP_2019-02-08_final.stac-item
2019-02-08 10:03:38	ga_s2bm_ard_3-2-1_54KZU_2019-02-08_final.stac-item
2019-02-08 10:03:42	ga_s2bm_ard_3-2-1_54KYU_2019-02-08_final.stac-item
2019-02-08 10:03:45	ga_s2bm_ard_3-2-1_54KZU_2019-02-08_final.stac-item
2019-02-08 10:03:45	ga_s2bm_ard_3-2-1_55KBP_2019-02-08_final.stac-item
2019-02-08 10:03:46	ga_s2bm_ard_3-2-1_54JZT_2019-02-08_final.stac-item
2019-02-08 10:03:47	ga_s2bm_ard_3-2-1_54JYT_2019-02-08_final.stac-item
2019-02-08 10:03:47	ga_s2bm_ard_3-2-1_54KYU_2019-02-08_final.stac-item
2019-02-08 10:03:53	ga_s2bm_ard_3-2-1_54JZT_2019-02-08_final.stac-item
2019-02-08 10:03:56	ga_s2bm_ard_3-2-1_54JYT_2019-02-08_final.stac-item
2019-02-08 11:44:13	ga_s2bm_ard_3-2-1_51KUP_2019-02-08_final.stac-item
2019-02-08 11:44:16	ga_s2bm_ard_3-2-1_50KRU_2019-02-08_final.stac-item
2019-02-08 11:44:16	ga_s2bm_ard_3-2-1_51KTP_2019-02-08_final.stac-item
2019-02-08 11:44:20	ga_s2bm_ard_3-2-1_50KQU_2019-02-08_final.stac-item
2019-02-08 11:44:23	ga_s2bm_ard_3-2-1_50KPU_2019-02-08_final.stac-item
2019-02-08 11:44:31	ga_s2bm_ard_3-2-1_50JRT_2019-02-08_final.stac-item
2019-02-08 11:44:35	ga_s2bm_ard_3-2-1_50JQT_2019-02-08_final.stac-item
2019-02-09 11:13:57	ga_s2bm_ard_3-2-1_52KEU_2019-02-09_final.stac-item
2019-02-09 11:14:02	ga_s2bm_ard_3-2-1_52KDU_2019-02-09_final.stac-item
2019-02-09 11:14:06	ga_s2bm_ard_3-2-1_52KCU_2019-02-09_final.stac-item
2019-02-09 11:14:09	ga_s2bm_ard_3-2-1_51KZP_2019-02-09_final.stac-item
2019-02-09 11:14:09	ga_s2bm_ard_3-2-1_52KBU_2019-02-09_final.stac-item
2019-02-09 11:14:23	ga_s2bm_ard_3-2-1_51JZN_2019-02-09_final.stac-item
2019-07-26 11:04:04	ga_s2bm_ard_3-2-1_52KGU_2019-07-26_final.stac-item
2019-07-26 11:04:08	ga_s2bm_ard_3-2-1_52KFU_2019-07-26_final.stac-item
2019-07-26 11:04:12	ga_s2bm_ard_3-2-1_52KEU_2019-07-26_final.stac-item
2019-07-26 11:04:15	ga_s2bm_ard_3-2-1_52KDU_2019-07-26_final.stac-item
2019-08-18 11:14:03	ga_s2bm_ard_3-2-1_52KEU_2019-08-18_final.stac-item
2019-08-18 11:14:08	ga_s2bm_ard_3-2-1_52KDU_2019-08-18_final.stac-item
2019-08-18 11:14:12	ga_s2bm_ard_3-2-1_52KCU_2019-08-18_final.stac-item
2019-08-18 11:14:15	ga_s2bm_ard_3-2-1_51KZP_2019-08-18_final.stac-item
2019-08-18 11:14:15	ga_s2bm_ard_3-2-1_52KBU_2019-08-18_final.stac-item
2019-08-18 11:14:29	ga_s2bm_ard_3-2-1_51JZN_2019-08-18_final.stac-item
2019-08-21 11:24:10	ga_s2bm_ard_3-2-1_51KZP_2019-08-21_final.stac-item
2019-08-21 11:24:10	ga_s2bm_ard_3-2-1_52KBU_2019-08-21_final.stac-item
2019-08-21 11:24:13	ga_s2bm_ard_3-2-1_51KYP_2019-08-21_final.stac-item
2019-08-21 11:24:17	ga_s2bm_ard_3-2-1_51KXP_2019-08-21_final.stac-item
2019-08-21 11:24:20	ga_s2bm_ard_3-2-1_51KWP_2019-08-21_final.stac-item
2019-08-21 11:24:24	ga_s2bm_ard_3-2-1_51JZN_2019-08-21_final.stac-item

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