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
2017-08-07 11:38:33	ga_s2bm_ard_3-2-1_50JNR_2017-08-07_final.stac-item
2017-08-07 11:38:33	ga_s2bm_ard_3-2-1_50JPR_2017-08-07_final.stac-item
2017-08-07 11:38:33	ga_s2bm_ard_3-2-1_50JPS_2017-08-07_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNP_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNQ_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNR_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNS_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNT_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JPP_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JPQ_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JPR_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JPS_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JPT_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KNU_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KNV_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KPA_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KPB_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KPC_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KPU_2017-12-28_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50KPV_2017-12-28_final.stac-item
2019-08-17 11:44:58	ga_s2bm_ard_3-2-1_50JPS_2019-08-17_final.stac-item
2019-08-17 11:45:13	ga_s2bm_ard_3-2-1_50JPR_2019-08-17_final.stac-item
2019-08-17 11:45:17	ga_s2bm_ard_3-2-1_50JNR_2019-08-17_final.stac-item
2019-08-17 11:45:27	ga_s2bm_ard_3-2-1_50JPQ_2019-08-17_final.stac-item
2019-08-17 11:45:31	ga_s2bm_ard_3-2-1_50JNQ_2019-08-17_final.stac-item
2019-08-17 11:45:42	ga_s2bm_ard_3-2-1_50JPP_2019-08-17_final.stac-item
2019-08-17 11:45:45	ga_s2bm_ard_3-2-1_50JNP_2019-08-17_final.stac-item
2019-08-17 11:45:56	ga_s2bm_ard_3-2-1_50JPN_2019-08-17_final.stac-item
2019-08-17 11:46:00	ga_s2bm_ard_3-2-1_50JNN_2019-08-17_final.stac-item
2019-08-17 11:46:11	ga_s2bm_ard_3-2-1_50JPM_2019-08-17_final.stac-item
2019-08-17 11:46:14	ga_s2bm_ard_3-2-1_50JNM_2019-08-17_final.stac-item
2019-08-17 11:46:25	ga_s2bm_ard_3-2-1_50JPL_2019-08-17_final.stac-item
2019-08-17 11:46:29	ga_s2bm_ard_3-2-1_50JNL_2019-08-17_final.stac-item
2019-08-17 11:46:40	ga_s2bm_ard_3-2-1_50HPK_2019-08-17_final.stac-item
2019-08-17 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2019-08-17_final.stac-item
2019-09-06 11:46:11	ga_s2bm_ard_3-2-1_50JNM_2019-09-06_final.stac-item
2019-09-06 11:46:21	ga_s2bm_ard_3-2-1_50JPL_2019-09-06_final.stac-item
2019-09-06 11:46:25	ga_s2bm_ard_3-2-1_50JNL_2019-09-06_final.stac-item
2019-09-06 11:46:36	ga_s2bm_ard_3-2-1_50HPK_2019-09-06_final.stac-item
2019-09-06 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2019-09-06_final.stac-item
2019-09-06 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2019-09-06_final.stac-item
2019-09-06 11:46:54	ga_s2bm_ard_3-2-1_50HNJ_2019-09-06_final.stac-item
2019-09-06 11:47:04	ga_s2bm_ard_3-2-1_50HPH_2019-09-06_final.stac-item
2019-09-06 11:47:09	ga_s2bm_ard_3-2-1_50HNH_2019-09-06_final.stac-item
2019-09-09 11:55:17	ga_s2bm_ard_3-2-1_50JPQ_2019-09-09_final.stac-item
2019-09-09 11:55:22	ga_s2bm_ard_3-2-1_50JNQ_2019-09-09_final.stac-item
2019-09-09 11:55:28	ga_s2bm_ard_3-2-1_50JPP_2019-09-09_final.stac-item
2019-09-09 11:55:36	ga_s2bm_ard_3-2-1_50JNP_2019-09-09_final.stac-item
2019-09-16 11:44:52	ga_s2bm_ard_3-2-1_50JPS_2019-09-16_final.stac-item
2019-09-16 11:45:06	ga_s2bm_ard_3-2-1_50JPR_2019-09-16_final.stac-item
2019-09-16 11:45:11	ga_s2bm_ard_3-2-1_50JNR_2019-09-16_final.stac-item
2019-09-16 11:45:21	ga_s2bm_ard_3-2-1_50JPQ_2019-09-16_final.stac-item
2019-09-16 11:45:24	ga_s2bm_ard_3-2-1_50JNQ_2019-09-16_final.stac-item
2019-09-16 11:45:36	ga_s2bm_ard_3-2-1_50JPP_2019-09-16_final.stac-item
2019-09-16 11:45:39	ga_s2bm_ard_3-2-1_50JNP_2019-09-16_final.stac-item
2019-09-16 11:45:50	ga_s2bm_ard_3-2-1_50JPN_2019-09-16_final.stac-item
2019-09-16 11:45:54	ga_s2bm_ard_3-2-1_50JNN_2019-09-16_final.stac-item
2019-09-16 11:46:05	ga_s2bm_ard_3-2-1_50JPM_2019-09-16_final.stac-item
2019-09-16 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2019-09-16_final.stac-item
2019-09-16 11:46:19	ga_s2bm_ard_3-2-1_50JPL_2019-09-16_final.stac-item
2019-09-16 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2019-09-16_final.stac-item
2019-09-16 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2019-09-16_final.stac-item
2019-09-16 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2019-09-16_final.stac-item
2019-09-16 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2019-09-16_final.stac-item
2019-09-16 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2019-09-16_final.stac-item
2019-09-16 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-09-16_final.stac-item
2019-09-16 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2019-09-16_final.stac-item
2023-01-11 11:52:04	ga_s2bm_ard_3-2-1_50LPH_2023-01-11_nrt.stac-item
2023-01-11 11:52:19	ga_s2bm_ard_3-2-1_50KPG_2023-01-11_nrt.stac-item
2023-01-11 11:52:48	ga_s2bm_ard_3-2-1_50KPE_2023-01-11_nrt.stac-item
2023-01-11 11:53:17	ga_s2bm_ard_3-2-1_50KPC_2023-01-11_final.stac-item
2023-01-11 11:53:32	ga_s2bm_ard_3-2-1_50KPB_2023-01-11_final.stac-item
2023-01-11 11:53:46	ga_s2bm_ard_3-2-1_50KPA_2023-01-11_final.stac-item
2023-01-11 11:54:01	ga_s2bm_ard_3-2-1_50KPV_2023-01-11_final.stac-item
2023-01-11 11:54:04	ga_s2bm_ard_3-2-1_50KNV_2023-01-11_final.stac-item
2023-01-11 11:54:15	ga_s2bm_ard_3-2-1_50KPU_2023-01-11_final.stac-item
2023-01-11 11:54:18	ga_s2bm_ard_3-2-1_50KNU_2023-01-11_final.stac-item
2023-01-11 11:54:29	ga_s2bm_ard_3-2-1_50JPT_2023-01-11_final.stac-item
2023-01-11 11:54:33	ga_s2bm_ard_3-2-1_50JNT_2023-01-11_final.stac-item
2023-01-11 11:54:44	ga_s2bm_ard_3-2-1_50JPS_2023-01-11_final.stac-item
2023-01-11 11:54:47	ga_s2bm_ard_3-2-1_50JNS_2023-01-11_final.stac-item
2023-01-11 11:54:58	ga_s2bm_ard_3-2-1_50JPR_2023-01-11_final.stac-item
2023-01-11 11:55:02	ga_s2bm_ard_3-2-1_50JNR_2023-01-11_final.stac-item
2023-01-11 11:55:12	ga_s2bm_ard_3-2-1_50JPQ_2023-01-11_final.stac-item
2023-01-11 11:55:16	ga_s2bm_ard_3-2-1_50JNQ_2023-01-11_final.stac-item
2023-01-11 11:55:22	ga_s2bm_ard_3-2-1_50JPP_2023-01-11_final.stac-item
2023-01-14 12:00:33	ga_s2bm_ard_3-2-1_50LPP_2023-01-14_nrt.stac-item
2023-01-14 12:00:47	ga_s2bm_ard_3-2-1_50LPN_2023-01-14_nrt.stac-item
2023-01-14 12:01:02	ga_s2bm_ard_3-2-1_50LPM_2023-01-14_nrt.stac-item
2023-01-14 12:01:16	ga_s2bm_ard_3-2-1_50LPL_2023-01-14_nrt.stac-item
2023-01-14 12:01:30	ga_s2bm_ard_3-2-1_50LPK_2023-01-14_nrt.stac-item
2023-01-14 12:01:37	ga_s2bm_ard_3-2-1_50LPJ_2023-01-14_nrt.stac-item
2023-01-15 11:37:23	ga_s2bm_ard_3-2-1_50HNG_2023-01-15_final
2023-01-15 11:37:29	ga_s2bm_ard_3-2-1_50HNF_2023-01-15_nrt.stac-item
2023-01-21 11:52:06	ga_s2bm_ard_3-2-1_50LPH_2023-01-21_nrt.stac-item
2023-01-21 11:52:21	ga_s2bm_ard_3-2-1_50KPG_2023-01-21_nrt.stac-item
2023-01-21 11:53:19	ga_s2bm_ard_3-2-1_50KPC_2023-01-21_final.stac-item
2023-01-21 11:53:33	ga_s2bm_ard_3-2-1_50KPB_2023-01-21_final.stac-item
2023-01-21 11:53:48	ga_s2bm_ard_3-2-1_50KPA_2023-01-21_final.stac-item
2023-01-21 11:54:06	ga_s2bm_ard_3-2-1_50KNV_2023-01-21_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

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