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
2017-07-04 10:22:06	ga_s2bm_ard_3-2-1_53HNB_2017-07-04_final.stac-item
2017-07-04 10:22:06	ga_s2bm_ard_3-2-1_53HNC_2017-07-04_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53LPC_2018-06-05_final
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53LPD_2018-06-05_final
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53KNP_2018-06-05_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53KNQ_2018-06-05_final.stac-item
2019-01-15 10:26:40	ga_s2bm_ard_3-2-1_53HNC_2019-01-15_final.stac-item
2019-01-15 10:26:47	ga_s2bm_ard_3-2-1_53HNB_2019-01-15_final.stac-item
2019-01-15 10:26:54	ga_s2bm_ard_3-2-1_53HNB_2019-01-15_final.stac-item
2019-01-24 10:50:35	ga_s2bm_ard_3-2-1_53LPG_2019-01-24_final.stac-item
2019-01-24 10:50:49	ga_s2bm_ard_3-2-1_53LPF_2019-01-24_final.stac-item
2019-01-24 10:51:04	ga_s2bm_ard_3-2-1_53LPE_2019-01-24_final.stac-item
2019-01-24 10:51:18	ga_s2bm_ard_3-2-1_53LPD_2019-01-24_final
2019-01-24 10:51:31	ga_s2bm_ard_3-2-1_53LPC_2019-01-24_final
2019-01-25 10:26:41	ga_s2bm_ard_3-2-1_53HNC_2019-01-25_final.stac-item
2019-01-25 10:26:54	ga_s2bm_ard_3-2-1_53HNB_2019-01-25_final.stac-item
2019-01-28 10:34:06	ga_s2bm_ard_3-2-1_53JPN_2019-01-28_final.stac-item
2019-01-28 10:34:11	ga_s2bm_ard_3-2-1_53JNN_2019-01-28_final.stac-item
2019-01-28 10:34:13	ga_s2bm_ard_3-2-1_53JPN_2019-01-28_final.stac-item
2019-01-28 10:34:15	ga_s2bm_ard_3-2-1_53JNN_2019-01-28_final.stac-item
2019-01-28 10:34:22	ga_s2bm_ard_3-2-1_53JPM_2019-01-28_final.stac-item
2019-01-28 10:34:25	ga_s2bm_ard_3-2-1_53JNM_2019-01-28_final.stac-item
2019-01-28 10:34:36	ga_s2bm_ard_3-2-1_53JPL_2019-01-28_final.stac-item
2019-01-28 10:34:40	ga_s2bm_ard_3-2-1_53JNL_2019-01-28_final.stac-item
2019-01-28 10:34:51	ga_s2bm_ard_3-2-1_53JPK_2019-01-28_final.stac-item
2019-01-28 10:34:54	ga_s2bm_ard_3-2-1_53JNK_2019-01-28_final.stac-item
2019-01-28 10:35:05	ga_s2bm_ard_3-2-1_53JPJ_2019-01-28_final.stac-item
2019-01-28 10:35:09	ga_s2bm_ard_3-2-1_53JNJ_2019-01-28_final.stac-item
2019-01-28 10:35:20	ga_s2bm_ard_3-2-1_53JPH_2019-01-28_final.stac-item
2019-01-28 10:35:23	ga_s2bm_ard_3-2-1_53JNH_2019-01-28_final.stac-item
2019-01-28 10:35:34	ga_s2bm_ard_3-2-1_53JPG_2019-01-28_final.stac-item
2019-01-28 10:35:38	ga_s2bm_ard_3-2-1_53JNG_2019-01-28_final.stac-item
2019-01-28 10:35:49	ga_s2bm_ard_3-2-1_53JPF_2019-01-28_final.stac-item
2019-01-28 10:35:52	ga_s2bm_ard_3-2-1_53JNF_2019-01-28_final.stac-item
2019-01-28 10:36:07	ga_s2bm_ard_3-2-1_53HNE_2019-01-28_final.stac-item
2019-02-03 10:50:35	ga_s2bm_ard_3-2-1_53LPG_2019-02-03_final.stac-item
2019-02-03 10:50:49	ga_s2bm_ard_3-2-1_53LPF_2019-02-03_final.stac-item
2019-02-03 10:51:04	ga_s2bm_ard_3-2-1_53LPE_2019-02-03_final.stac-item
2019-02-03 10:51:18	ga_s2bm_ard_3-2-1_53LPD_2019-02-03_final
2019-02-03 10:51:31	ga_s2bm_ard_3-2-1_53LPC_2019-02-03_final
2019-02-07 10:34:07	ga_s2bm_ard_3-2-1_53JPN_2019-02-07_final.stac-item
2019-02-07 10:34:14	ga_s2bm_ard_3-2-1_53JNN_2019-02-07_final.stac-item
2019-02-07 10:34:22	ga_s2bm_ard_3-2-1_53JPM_2019-02-07_final.stac-item
2019-02-07 10:34:25	ga_s2bm_ard_3-2-1_53JNM_2019-02-07_final.stac-item
2019-02-07 10:34:36	ga_s2bm_ard_3-2-1_53JPL_2019-02-07_final.stac-item
2019-02-07 10:34:40	ga_s2bm_ard_3-2-1_53JNL_2019-02-07_final.stac-item
2019-02-07 10:34:51	ga_s2bm_ard_3-2-1_53JPK_2019-02-07_final.stac-item
2019-02-07 10:34:54	ga_s2bm_ard_3-2-1_53JNK_2019-02-07_final.stac-item
2019-02-07 10:35:05	ga_s2bm_ard_3-2-1_53JPJ_2019-02-07_final.stac-item
2019-02-07 10:35:09	ga_s2bm_ard_3-2-1_53JNJ_2019-02-07_final.stac-item
2019-02-07 10:35:20	ga_s2bm_ard_3-2-1_53JPH_2019-02-07_final.stac-item
2019-02-07 10:35:23	ga_s2bm_ard_3-2-1_53JNH_2019-02-07_final.stac-item
2019-02-07 10:35:34	ga_s2bm_ard_3-2-1_53JPG_2019-02-07_final.stac-item
2019-02-07 10:35:38	ga_s2bm_ard_3-2-1_53JNG_2019-02-07_final.stac-item
2019-02-07 10:35:49	ga_s2bm_ard_3-2-1_53JPF_2019-02-07_final.stac-item
2019-02-07 10:35:52	ga_s2bm_ard_3-2-1_53JNF_2019-02-07_final.stac-item
2019-02-07 10:36:07	ga_s2bm_ard_3-2-1_53HNE_2019-02-07_final.stac-item
2019-02-07 10:36:21	ga_s2bm_ard_3-2-1_53HND_2019-02-07_final.stac-item
2019-02-07 10:36:36	ga_s2bm_ard_3-2-1_53HNC_2019-02-07_final.stac-item
2019-02-07 10:36:50	ga_s2bm_ard_3-2-1_53HNB_2019-02-07_final.stac-item
2019-07-07 10:34:16	ga_s2bm_ard_3-2-1_53JPN_2019-07-07_final.stac-item
2019-07-07 10:34:22	ga_s2bm_ard_3-2-1_53JNN_2019-07-07_final.stac-item
2019-07-07 10:34:30	ga_s2bm_ard_3-2-1_53JPM_2019-07-07_final.stac-item
2019-07-07 10:34:34	ga_s2bm_ard_3-2-1_53JNM_2019-07-07_final.stac-item
2019-07-07 10:34:45	ga_s2bm_ard_3-2-1_53JPL_2019-07-07_final.stac-item
2019-07-07 10:34:48	ga_s2bm_ard_3-2-1_53JNL_2019-07-07_final.stac-item
2019-07-07 10:34:59	ga_s2bm_ard_3-2-1_53JPK_2019-07-07_final.stac-item
2019-07-07 10:35:03	ga_s2bm_ard_3-2-1_53JNK_2019-07-07_final.stac-item
2019-09-21 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2019-09-21_final.stac-item
2019-09-21 10:50:48	ga_s2bm_ard_3-2-1_53LPF_2019-09-21_final.stac-item
2019-09-21 10:51:03	ga_s2bm_ard_3-2-1_53LPE_2019-09-21_final.stac-item
2019-09-21 10:51:18	ga_s2bm_ard_3-2-1_53LPD_2019-09-21_final
2019-09-21 10:51:31	ga_s2bm_ard_3-2-1_53LPC_2019-09-21_final
2019-10-08 10:41:24	ga_s2bm_ard_3-2-1_53LPD_2019-10-08_final
2019-10-08 10:41:39	ga_s2bm_ard_3-2-1_53LPC_2019-10-08_final
2019-10-08 10:41:53	ga_s2bm_ard_3-2-1_53KPB_2019-10-08_final.stac-item
2019-10-08 10:42:03	ga_s2bm_ard_3-2-1_53KPA_2019-10-08_final.stac-item
2019-10-08 10:42:09	ga_s2bm_ard_3-2-1_53KPA_2019-10-08_final.stac-item
2019-10-08 10:42:22	ga_s2bm_ard_3-2-1_53KPV_2019-10-08_final.stac-item
2019-10-08 10:42:37	ga_s2bm_ard_3-2-1_53KPU_2019-10-08_final.stac-item
2019-10-08 10:42:40	ga_s2bm_ard_3-2-1_53KNU_2019-10-08_final.stac-item
2019-10-08 10:42:51	ga_s2bm_ard_3-2-1_53KPT_2019-10-08_final.stac-item
2019-10-08 10:42:54	ga_s2bm_ard_3-2-1_53KNT_2019-10-08_final.stac-item
2019-10-08 10:43:06	ga_s2bm_ard_3-2-1_53KPS_2019-10-08_final.stac-item
2019-10-08 10:43:09	ga_s2bm_ard_3-2-1_53KNS_2019-10-08_final.stac-item
2019-10-08 10:43:20	ga_s2bm_ard_3-2-1_53KPR_2019-10-08_final.stac-item
2019-10-08 10:43:24	ga_s2bm_ard_3-2-1_53KNR_2019-10-08_final.stac-item
2019-10-08 10:43:34	ga_s2bm_ard_3-2-1_53KPQ_2019-10-08_final.stac-item
2019-10-08 10:43:38	ga_s2bm_ard_3-2-1_53KNQ_2019-10-08_final.stac-item
2019-10-08 10:43:49	ga_s2bm_ard_3-2-1_53KPP_2019-10-08_final.stac-item
2019-10-08 10:43:53	ga_s2bm_ard_3-2-1_53KNP_2019-10-08_final.stac-item
2019-10-08 10:44:04	ga_s2bm_ard_3-2-1_53JPN_2019-10-08_final.stac-item
2019-10-08 10:44:07	ga_s2bm_ard_3-2-1_53JNN_2019-10-08_final.stac-item
2019-10-08 10:44:17	ga_s2bm_ard_3-2-1_53JPM_2019-10-08_final.stac-item
2019-10-08 10:44:22	ga_s2bm_ard_3-2-1_53JNM_2019-10-08_final.stac-item
2019-10-08 10:44:29	ga_s2bm_ard_3-2-1_53JPL_2019-10-08_final.stac-item
2019-10-08 10:44:36	ga_s2bm_ard_3-2-1_53JNL_2019-10-08_final.stac-item
2019-11-21 10:26:51	ga_s2bm_ard_3-2-1_53HNB_2019-11-21_final.stac-item
2019-12-01 10:26:36	ga_s2bm_ard_3-2-1_53HNC_2019-12-01_final.stac-item
2019-12-01 10:26:45	ga_s2bm_ard_3-2-1_53HNB_2019-12-01_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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