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
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_56KKA_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_56KKB_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_56KLA_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_56KLB_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_55KGR_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_55KGS_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_55KHR_2018-06-07_final.stac-item
2018-06-07 09:41:06	ga_s2bm_ard_3-2-1_55KHS_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_52KBA_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_52KBB_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_52KCA_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_52KCB_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KXR_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KXS_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KYR_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KYS_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KZR_2018-06-07_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51KZS_2018-06-07_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KEA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KEB_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KKR_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KKS_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KFA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KFB_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KGA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KGB_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KHA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_52KHB_2018-06-11_final.stac-item
2019-07-29 09:32:57	ga_s2bm_ard_3-2-1_56KLB_2019-07-29_final.stac-item
2019-08-08 09:32:56	ga_s2bm_ard_3-2-1_56KLB_2019-08-08_final.stac-item
2023-11-01 11:33:26	ga_s2bm_ard_3-2-1_51KXS_2023-11-01_final
2023-11-01 11:33:30	ga_s2bm_ard_3-2-1_51KWS_2023-11-01_final
2023-11-01 11:33:33	ga_s2bm_ard_3-2-1_51KVS_2023-11-01_final
2023-11-01 11:33:36	ga_s2bm_ard_3-2-1_51KUS_2023-11-01_final
2023-11-01 11:33:41	ga_s2bm_ard_3-2-1_51KXR_2023-11-01_final
2023-11-01 11:33:44	ga_s2bm_ard_3-2-1_51KWR_2023-11-01_final
2023-11-01 11:33:50	ga_s2bm_ard_3-2-1_51KUR_2023-11-01_final
2023-11-03 10:33:02	ga_s2bm_ard_3-2-1_54KUB_2023-11-03_final
2023-11-03 10:33:04	ga_s2bm_ard_3-2-1_54KTB_2023-11-03_final
2023-11-03 10:33:05	ga_s2bm_ard_3-2-1_53KRS_2023-11-03_final
2023-11-03 10:33:08	ga_s2bm_ard_3-2-1_53KQS_2023-11-03_final
2023-11-03 10:33:15	ga_s2bm_ard_3-2-1_53KPS_2023-11-03_final
2023-11-03 10:33:16	ga_s2bm_ard_3-2-1_54KUA_2023-11-03_final
2023-11-03 10:33:19	ga_s2bm_ard_3-2-1_54KTA_2023-11-03_final
2023-11-03 10:33:19	ga_s2bm_ard_3-2-1_53KRR_2023-11-03_final
2023-11-03 10:33:23	ga_s2bm_ard_3-2-1_53KQR_2023-11-03_final
2023-11-03 10:33:26	ga_s2bm_ard_3-2-1_53KPR_2023-11-03_final
2023-11-03 12:13:42	ga_s2bm_ard_3-2-1_50KKB_2023-11-03_final
2023-11-03 12:13:42	ga_s2bm_ard_3-2-1_49KHS_2023-11-03_final
2023-11-03 12:13:46	ga_s2bm_ard_3-2-1_49KGS_2023-11-03_nrt
2023-11-03 12:13:50	ga_s2bm_ard_3-2-1_49KFS_2023-11-03_nrt
2023-11-03 12:13:57	ga_s2bm_ard_3-2-1_50KKA_2023-11-03_final
2023-11-03 12:13:57	ga_s2bm_ard_3-2-1_49KHR_2023-11-03_final
2023-11-03 12:14:01	ga_s2bm_ard_3-2-1_49KGR_2023-11-03_final
2023-11-03 12:14:04	ga_s2bm_ard_3-2-1_49KFR_2023-11-03_nrt
2023-11-04 10:02:47	ga_s2bm_ard_3-2-1_55KES_2023-11-04_final
2023-11-04 10:02:51	ga_s2bm_ard_3-2-1_55KDS_2023-11-04_final
2023-11-04 10:02:54	ga_s2bm_ard_3-2-1_55KCS_2023-11-04_final
2023-11-04 10:02:57	ga_s2bm_ard_3-2-1_55KBS_2023-11-04_final
2023-11-04 10:02:57	ga_s2bm_ard_3-2-1_54KZB_2023-11-04_final
2023-11-04 10:03:09	ga_s2bm_ard_3-2-1_55KCR_2023-11-04_final
2023-11-04 10:03:12	ga_s2bm_ard_3-2-1_55KBR_2023-11-04_final
2023-11-04 10:03:12	ga_s2bm_ard_3-2-1_54KZA_2023-11-04_final
2023-11-04 11:43:27	ga_s2bm_ard_3-2-1_51KVS_2023-11-04_final
2023-11-04 11:43:32	ga_s2bm_ard_3-2-1_51KUS_2023-11-04_final
2023-11-04 11:43:35	ga_s2bm_ard_3-2-1_51KTS_2023-11-04_final
2023-11-04 11:43:36	ga_s2bm_ard_3-2-1_50KRB_2023-11-04_final
2023-11-04 11:43:39	ga_s2bm_ard_3-2-1_50KQB_2023-11-04_final
2023-11-04 11:43:46	ga_s2bm_ard_3-2-1_51KUR_2023-11-04_final
2023-11-04 11:43:50	ga_s2bm_ard_3-2-1_51KTR_2023-11-04_final
2023-11-04 11:43:50	ga_s2bm_ard_3-2-1_50KRA_2023-11-04_final
2023-11-04 11:43:54	ga_s2bm_ard_3-2-1_50KQA_2023-11-04_final
2024-02-04 10:42:59	ga_s2bm_ard_3-2-1_53KQS_2024-02-04_final
2024-02-04 10:43:03	ga_s2bm_ard_3-2-1_53KPS_2024-02-04_final
2024-02-04 10:43:09	ga_s2bm_ard_3-2-1_53KMS_2024-02-04_final
2024-02-04 10:43:12	ga_s2bm_ard_3-2-1_53KQR_2024-02-04_final
2024-02-04 10:43:17	ga_s2bm_ard_3-2-1_53KPR_2024-02-04_final
2024-02-04 10:43:21	ga_s2bm_ard_3-2-1_53KNR_2024-02-04_final
2024-02-05 10:12:48	ga_s2bm_ard_3-2-1_55KBS_2024-02-05_final
2024-02-05 10:12:48	ga_s2bm_ard_3-2-1_54KZB_2024-02-05_final
2024-02-05 10:12:51	ga_s2bm_ard_3-2-1_54KYB_2024-02-05_final
2024-02-05 10:12:56	ga_s2bm_ard_3-2-1_55KBS_2024-02-05_final
2024-02-05 10:12:56	ga_s2bm_ard_3-2-1_54KZA_2024-02-05_final
2024-02-05 10:12:56	ga_s2bm_ard_3-2-1_55KBR_2024-02-05_final
2024-02-05 10:12:56	ga_s2bm_ard_3-2-1_54KZB_2024-02-05_final
2024-02-05 10:12:58	ga_s2bm_ard_3-2-1_54KYB_2024-02-05_final
2024-02-05 10:12:58	ga_s2bm_ard_3-2-1_54KYA_2024-02-05_final
2024-02-05 10:13:00	ga_s2bm_ard_3-2-1_54KXB_2024-02-05_final
2024-02-05 10:13:02	ga_s2bm_ard_3-2-1_54KWB_2024-02-05_final
2024-02-05 10:13:03	ga_s2bm_ard_3-2-1_55KBR_2024-02-05_final
2024-02-05 10:13:03	ga_s2bm_ard_3-2-1_54KZA_2024-02-05_final
2024-02-05 10:13:07	ga_s2bm_ard_3-2-1_54KYA_2024-02-05_final
2024-02-05 10:13:10	ga_s2bm_ard_3-2-1_54KXA_2024-02-05_final
2024-02-05 10:13:14	ga_s2bm_ard_3-2-1_54KWA_2024-02-05_final
2024-02-09 11:33:28	ga_s2bm_ard_3-2-1_51KXS_2024-02-09_final
2024-02-09 11:33:30	ga_s2bm_ard_3-2-1_51KWS_2024-02-09_final
2024-02-09 11:33:32	ga_s2bm_ard_3-2-1_51KVS_2024-02-09_final
2024-02-09 11:33:34	ga_s2bm_ard_3-2-1_51KUS_2024-02-09_final
2024-02-09 11:33:38	ga_s2bm_ard_3-2-1_51KXR_2024-02-09_final
2024-02-09 11:33:42	ga_s2bm_ard_3-2-1_51KWR_2024-02-09_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