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
2018-02-09 10:16:59	ga_s2bm_ard_3-2-1_54KUA_2018-02-09_final.stac-item
2018-02-09 10:16:59	ga_s2bm_ard_3-2-1_54KVA_2018-02-09_final.stac-item
2018-02-09 10:16:59	ga_s2bm_ard_3-2-1_54KWA_2018-02-09_final.stac-item
2018-02-09 10:16:59	ga_s2bm_ard_3-2-1_54KXA_2018-02-09_final.stac-item
2018-02-10 11:30:33	ga_s2bm_ard_3-2-1_51KUR_2018-02-10_final.stac-item
2018-02-10 11:30:33	ga_s2bm_ard_3-2-1_51KVR_2018-02-10_final.stac-item
2018-02-10 11:30:33	ga_s2bm_ard_3-2-1_51KWR_2018-02-10_final.stac-item
2018-02-10 11:30:33	ga_s2bm_ard_3-2-1_51KXR_2018-02-10_final.stac-item
2018-02-13 11:37:45	ga_s2bm_ard_3-2-1_51KTR_2018-02-13_final.stac-item
2018-02-13 11:37:45	ga_s2bm_ard_3-2-1_51KUR_2018-02-13_final.stac-item
2018-02-13 11:37:45	ga_s2bm_ard_3-2-1_50KRA_2018-02-13_final.stac-item
2018-02-13 11:37:45	ga_s2bm_ard_3-2-1_50KRV_2018-02-13_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_51KTR_2018-02-13_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50KQA_2018-02-13_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50KQV_2018-02-13_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50KRA_2018-02-13_final.stac-item
2018-02-13 11:43:42	ga_s2bm_ard_3-2-1_50KRV_2018-02-13_final.stac-item
2018-02-14 09:32:33	ga_s2bm_ard_3-2-1_56KLA_2018-02-14_final.stac-item
2018-02-14 09:32:33	ga_s2bm_ard_3-2-1_56KMA_2018-02-14_final.stac-item
2018-02-16 11:50:39	ga_s2bm_ard_3-2-1_50KMA_2018-02-16_final.stac-item
2018-02-16 11:50:39	ga_s2bm_ard_3-2-1_50KNA_2018-02-16_final.stac-item
2018-02-16 11:50:39	ga_s2bm_ard_3-2-1_50KPA_2018-02-16_final.stac-item
2018-02-16 11:50:39	ga_s2bm_ard_3-2-1_50KQA_2018-02-16_final.stac-item
2018-02-24 09:32:32	ga_s2bm_ard_3-2-1_56KLA_2018-02-24_final.stac-item
2018-02-24 09:32:32	ga_s2bm_ard_3-2-1_56KMA_2018-02-24_final.stac-item
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50KMA_2018-02-26_final.stac-item
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50KNA_2018-02-26_final.stac-item
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50KPA_2018-02-26_final.stac-item
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50KQA_2018-02-26_final.stac-item
2018-03-01 10:16:57	ga_s2bm_ard_3-2-1_54KUA_2018-03-01_final.stac-item
2018-03-01 10:16:57	ga_s2bm_ard_3-2-1_54KVA_2018-03-01_final.stac-item
2018-03-01 10:16:57	ga_s2bm_ard_3-2-1_54KWA_2018-03-01_final.stac-item
2018-03-01 10:16:57	ga_s2bm_ard_3-2-1_54KXA_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_49KGQ_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_49KHQ_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_49KHR_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50KKA_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50KLA_2018-03-01_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50KMA_2018-03-01_final.stac-item
2019-08-24 09:53:06	ga_s2bm_ard_3-2-1_55KGR_2019-08-24_final.stac-item
2019-08-24 09:53:08	ga_s2bm_ard_3-2-1_55KFR_2019-08-24_final.stac-item
2019-08-24 09:53:09	ga_s2bm_ard_3-2-1_55KER_2019-08-24_final.stac-item
2019-08-24 09:53:12	ga_s2bm_ard_3-2-1_55KDR_2019-08-24_final.stac-item
2019-09-02 10:23:11	ga_s2bm_ard_3-2-1_54KXA_2019-09-02_final.stac-item
2019-09-02 10:23:14	ga_s2bm_ard_3-2-1_54KWA_2019-09-02_final.stac-item
2019-09-02 10:23:18	ga_s2bm_ard_3-2-1_54KVA_2019-09-02_final.stac-item
2019-09-02 10:23:21	ga_s2bm_ard_3-2-1_54KUA_2019-09-02_final.stac-item
2019-09-05 10:33:16	ga_s2bm_ard_3-2-1_54KUA_2019-09-05_final.stac-item
2019-09-05 10:33:19	ga_s2bm_ard_3-2-1_54KTA_2019-09-05_final.stac-item
2019-09-05 10:33:19	ga_s2bm_ard_3-2-1_53KRR_2019-09-05_final.stac-item
2019-09-05 10:33:23	ga_s2bm_ard_3-2-1_53KQR_2019-09-05_final.stac-item
2019-09-05 10:33:26	ga_s2bm_ard_3-2-1_53KPR_2019-09-05_final.stac-item
2019-09-05 10:33:34	ga_s2bm_ard_3-2-1_53KRQ_2019-09-05_final.stac-item
2019-09-05 10:33:37	ga_s2bm_ard_3-2-1_53KQQ_2019-09-05_final.stac-item
2019-09-12 10:23:09	ga_s2bm_ard_3-2-1_54KXA_2019-09-12_final.stac-item
2019-09-12 10:23:12	ga_s2bm_ard_3-2-1_54KWA_2019-09-12_final.stac-item
2019-09-12 10:23:15	ga_s2bm_ard_3-2-1_54KVA_2019-09-12_final.stac-item
2019-09-12 10:23:18	ga_s2bm_ard_3-2-1_54KUA_2019-09-12_final.stac-item
2019-12-28 10:13:00	ga_s2bm_ard_3-2-1_55KBR_2019-12-28_final.stac-item
2019-12-28 10:13:04	ga_s2bm_ard_3-2-1_54KYA_2019-12-28_final.stac-item
2019-12-28 10:13:07	ga_s2bm_ard_3-2-1_54KXA_2019-12-28_final.stac-item
2019-12-28 10:13:11	ga_s2bm_ard_3-2-1_54KWA_2019-12-28_final.stac-item
2019-12-28 10:13:18	ga_s2bm_ard_3-2-1_54KYV_2019-12-28_final.stac-item
2019-12-31 10:23:01	ga_s2bm_ard_3-2-1_54KXA_2019-12-31_final.stac-item
2019-12-31 10:23:06	ga_s2bm_ard_3-2-1_54KWA_2019-12-31_final.stac-item
2019-12-31 10:23:09	ga_s2bm_ard_3-2-1_54KVA_2019-12-31_final.stac-item
2019-12-31 10:23:13	ga_s2bm_ard_3-2-1_54KUA_2019-12-31_final.stac-item
2020-01-01 09:52:52	ga_s2bm_ard_3-2-1_55KGR_2020-01-01_final.stac-item
2020-01-01 09:52:55	ga_s2bm_ard_3-2-1_55KFR_2020-01-01_final.stac-item
2020-01-01 09:52:59	ga_s2bm_ard_3-2-1_55KER_2020-01-01_final.stac-item
2020-01-01 09:53:02	ga_s2bm_ard_3-2-1_55KDR_2020-01-01_final.stac-item
2020-01-07 10:12:59	ga_s2bm_ard_3-2-1_55KBR_2020-01-07_final.stac-item
2020-01-07 10:12:59	ga_s2bm_ard_3-2-1_54KZA_2020-01-07_final.stac-item
2020-01-07 10:13:03	ga_s2bm_ard_3-2-1_54KYA_2020-01-07_final.stac-item
2020-01-07 10:13:07	ga_s2bm_ard_3-2-1_54KXA_2020-01-07_final.stac-item
2020-01-07 10:13:10	ga_s2bm_ard_3-2-1_54KWA_2020-01-07_final.stac-item
2020-01-07 10:13:14	ga_s2bm_ard_3-2-1_54KZV_2020-01-07_final.stac-item
2020-01-07 10:13:18	ga_s2bm_ard_3-2-1_54KYV_2020-01-07_final.stac-item
2020-01-10 10:23:01	ga_s2bm_ard_3-2-1_54KXA_2020-01-10_final.stac-item
2020-01-10 10:23:05	ga_s2bm_ard_3-2-1_54KWA_2020-01-10_final.stac-item
2020-01-10 10:23:09	ga_s2bm_ard_3-2-1_54KVA_2020-01-10_final.stac-item
2020-01-10 10:23:12	ga_s2bm_ard_3-2-1_54KUA_2020-01-10_final.stac-item
2020-01-11 09:52:51	ga_s2bm_ard_3-2-1_55KGR_2020-01-11_final.stac-item
2020-01-11 09:52:55	ga_s2bm_ard_3-2-1_55KFR_2020-01-11_final.stac-item
2020-01-11 09:52:58	ga_s2bm_ard_3-2-1_55KER_2020-01-11_final.stac-item
2020-01-11 09:53:02	ga_s2bm_ard_3-2-1_55KDR_2020-01-11_final.stac-item
2020-01-12 11:03:17	ga_s2bm_ard_3-2-1_52KHA_2020-01-12_final.stac-item
2020-01-12 11:03:22	ga_s2bm_ard_3-2-1_52KGA_2020-01-12_final.stac-item
2020-01-12 11:03:25	ga_s2bm_ard_3-2-1_52KFA_2020-01-12_final.stac-item
2020-01-12 11:03:28	ga_s2bm_ard_3-2-1_52KHV_2020-01-12_final.stac-item
2020-01-12 11:03:29	ga_s2bm_ard_3-2-1_52KEA_2020-01-12_final.stac-item
2020-01-12 11:03:36	ga_s2bm_ard_3-2-1_52KGV_2020-01-12_final.stac-item
2020-01-14 10:02:52	ga_s2bm_ard_3-2-1_55KER_2020-01-14_final.stac-item
2020-01-14 10:02:57	ga_s2bm_ard_3-2-1_55KDR_2020-01-14_final.stac-item
2020-01-14 10:03:00	ga_s2bm_ard_3-2-1_55KCR_2020-01-14_final.stac-item
2020-01-14 10:03:03	ga_s2bm_ard_3-2-1_55KBR_2020-01-14_final.stac-item
2020-01-14 10:03:04	ga_s2bm_ard_3-2-1_54KZA_2020-01-14_final.stac-item
2020-01-14 10:03:18	ga_s2bm_ard_3-2-1_54KZV_2020-01-14_final.stac-item
2020-01-15 09:32:46	ga_s2bm_ard_3-2-1_56KNA_2020-01-15_final
2020-01-15 09:32:50	ga_s2bm_ard_3-2-1_56KMA_2020-01-15_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

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