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
2019-10-26 11:44:32	ga_s2bm_ard_3-2-1_51JTN_2019-10-26_final.stac-item
2019-10-26 11:44:42	ga_s2bm_ard_3-2-1_51JUM_2019-10-26_final.stac-item
2019-10-26 11:44:46	ga_s2bm_ard_3-2-1_51JTM_2019-10-26_final.stac-item
2019-10-26 11:44:52	ga_s2bm_ard_3-2-1_51JUL_2019-10-26_final.stac-item
2019-10-26 11:45:01	ga_s2bm_ard_3-2-1_51JTL_2019-10-26_final.stac-item
2019-10-26 11:45:15	ga_s2bm_ard_3-2-1_51JTK_2019-10-26_final.stac-item
2019-10-26 11:45:30	ga_s2bm_ard_3-2-1_51JTJ_2019-10-26_final.stac-item
2019-10-26 11:45:44	ga_s2bm_ard_3-2-1_51JTH_2019-10-26_final.stac-item
2019-10-26 11:45:58	ga_s2bm_ard_3-2-1_51JTG_2019-10-26_final.stac-item
2019-10-26 11:46:09	ga_s2bm_ard_3-2-1_51JTF_2019-10-26_final.stac-item
2019-10-26 11:46:14	ga_s2bm_ard_3-2-1_50JMM_2019-10-26_final.stac-item
2019-10-26 11:46:24	ga_s2bm_ard_3-2-1_50JNL_2019-10-26_final.stac-item
2019-10-26 11:46:27	ga_s2bm_ard_3-2-1_50JML_2019-10-26_final.stac-item
2019-10-26 11:46:31	ga_s2bm_ard_3-2-1_50HQK_2019-10-26_final.stac-item
2019-10-26 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2019-10-26_final.stac-item
2019-10-26 11:46:38	ga_s2bm_ard_3-2-1_50HNK_2019-10-26_final.stac-item
2019-10-26 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2019-10-26_final.stac-item
2019-10-26 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2019-10-26_final.stac-item
2019-10-26 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2019-10-26_final.stac-item
2019-10-26 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2019-10-26_final.stac-item
2019-10-26 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2019-10-26_final.stac-item
2019-10-26 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2019-10-26_final.stac-item
2019-10-26 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2019-10-26_final.stac-item
2019-10-26 11:47:07	ga_s2bm_ard_3-2-1_50HNH_2019-10-26_final.stac-item
2019-10-26 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2019-10-26_final.stac-item
2019-10-26 11:47:15	ga_s2bm_ard_3-2-1_50HLH_2019-10-26_final.stac-item
2019-10-27 09:32:49	ga_s2bm_ard_3-2-1_56KLB_2019-10-27_final.stac-item
2019-10-27 09:32:56	ga_s2bm_ard_3-2-1_56KMA_2019-10-27_final.stac-item
2019-10-27 09:33:00	ga_s2bm_ard_3-2-1_56KLA_2019-10-27_final.stac-item
2019-10-27 09:33:14	ga_s2bm_ard_3-2-1_56KLV_2019-10-27_final.stac-item
2019-10-27 09:33:25	ga_s2bm_ard_3-2-1_56KMU_2019-10-27_final.stac-item
2019-10-27 09:33:29	ga_s2bm_ard_3-2-1_56KLU_2019-10-27_final.stac-item
2019-10-27 09:33:36	ga_s2bm_ard_3-2-1_56JNT_2019-10-27_final.stac-item
2019-10-27 09:33:40	ga_s2bm_ard_3-2-1_56JMT_2019-10-27_final.stac-item
2019-10-27 09:33:43	ga_s2bm_ard_3-2-1_56JLT_2019-10-27_final.stac-item
2019-10-27 09:33:51	ga_s2bm_ard_3-2-1_56JNS_2019-10-27_final.stac-item
2019-10-27 09:33:51	ga_s2bm_ard_3-2-1_56JKT_2019-10-27_final.stac-item
2019-10-27 09:33:55	ga_s2bm_ard_3-2-1_56JMS_2019-10-27_final.stac-item
2019-10-27 09:33:58	ga_s2bm_ard_3-2-1_56JLS_2019-10-27_final.stac-item
2019-10-27 09:34:02	ga_s2bm_ard_3-2-1_55JHM_2019-10-27_final.stac-item
2019-10-27 09:34:02	ga_s2bm_ard_3-2-1_56JKS_2019-10-27_final.stac-item
2019-10-27 09:34:09	ga_s2bm_ard_3-2-1_56JMR_2019-10-27_final.stac-item
2019-10-27 09:34:12	ga_s2bm_ard_3-2-1_56JLR_2019-10-27_final.stac-item
2019-10-27 09:34:15	ga_s2bm_ard_3-2-1_56JKR_2019-10-27_final.stac-item
2019-10-27 09:34:24	ga_s2bm_ard_3-2-1_56JMQ_2019-10-27_final.stac-item
2019-10-27 09:34:27	ga_s2bm_ard_3-2-1_56JLQ_2019-10-27_final.stac-item
2019-10-27 09:34:30	ga_s2bm_ard_3-2-1_56JKQ_2019-10-27_final.stac-item
2019-10-27 09:34:38	ga_s2bm_ard_3-2-1_56JMP_2019-10-27_final.stac-item
2019-10-27 09:34:41	ga_s2bm_ard_3-2-1_56JLP_2019-10-27_final.stac-item
2019-10-27 09:34:45	ga_s2bm_ard_3-2-1_56JKP_2019-10-27_final.stac-item
2019-10-27 09:34:45	ga_s2bm_ard_3-2-1_56JNN_2019-10-27_final.stac-item
2019-10-27 09:34:51	ga_s2bm_ard_3-2-1_55JGJ_2019-10-27_final.stac-item
2019-10-27 09:34:52	ga_s2bm_ard_3-2-1_56JMN_2019-10-27_final.stac-item
2019-10-27 09:34:56	ga_s2bm_ard_3-2-1_56JLN_2019-10-27_final.stac-item
2019-10-27 09:34:59	ga_s2bm_ard_3-2-1_56JKN_2019-10-27_final.stac-item
2019-10-27 09:35:02	ga_s2bm_ard_3-2-1_55JGH_2019-10-27_final.stac-item
2019-10-27 09:35:07	ga_s2bm_ard_3-2-1_56JMM_2019-10-27_final.stac-item
2019-10-27 09:35:11	ga_s2bm_ard_3-2-1_56JLM_2019-10-27_final.stac-item
2019-10-27 09:35:14	ga_s2bm_ard_3-2-1_56JKM_2019-10-27_final.stac-item
2019-10-27 09:35:16	ga_s2bm_ard_3-2-1_55JGG_2019-10-27_final.stac-item
2019-10-27 09:35:22	ga_s2bm_ard_3-2-1_56JML_2019-10-27_final.stac-item
2019-10-27 09:35:25	ga_s2bm_ard_3-2-1_56JLL_2019-10-27_final.stac-item
2019-10-27 09:35:28	ga_s2bm_ard_3-2-1_56JKL_2019-10-27_final.stac-item
2019-10-27 09:35:31	ga_s2bm_ard_3-2-1_55JGF_2019-10-27_final.stac-item
2019-10-27 09:35:36	ga_s2bm_ard_3-2-1_56HMK_2019-10-27_final.stac-item
2019-10-27 09:35:40	ga_s2bm_ard_3-2-1_56HLK_2019-10-27_final.stac-item
2019-10-27 09:35:43	ga_s2bm_ard_3-2-1_56HKK_2019-10-27_final.stac-item
2019-10-27 09:35:45	ga_s2bm_ard_3-2-1_55HGE_2019-10-27_final.stac-item
2019-10-27 09:35:49	ga_s2bm_ard_3-2-1_56HMJ_2019-10-27_final.stac-item
2019-10-27 09:35:51	ga_s2bm_ard_3-2-1_55HFE_2019-10-27_final.stac-item
2019-10-27 09:35:54	ga_s2bm_ard_3-2-1_56HLJ_2019-10-27_final.stac-item
2019-10-27 09:35:58	ga_s2bm_ard_3-2-1_56HKJ_2019-10-27_final.stac-item
2019-10-27 09:36:00	ga_s2bm_ard_3-2-1_55HGD_2019-10-27_final.stac-item
2019-10-27 09:36:03	ga_s2bm_ard_3-2-1_55HFD_2019-10-27_final.stac-item
2019-10-27 09:36:12	ga_s2bm_ard_3-2-1_56HKH_2019-10-27_final.stac-item
2019-10-27 09:36:14	ga_s2bm_ard_3-2-1_55HGC_2019-10-27_final.stac-item
2019-10-27 09:36:18	ga_s2bm_ard_3-2-1_55HFC_2019-10-27_final.stac-item
2019-10-27 09:36:27	ga_s2bm_ard_3-2-1_56HKG_2019-10-27_final.stac-item
2019-10-27 09:36:28	ga_s2bm_ard_3-2-1_55HGB_2019-10-27_final.stac-item
2019-10-27 09:36:32	ga_s2bm_ard_3-2-1_55HFB_2019-10-27_final.stac-item
2019-10-27 09:36:41	ga_s2bm_ard_3-2-1_56HKF_2019-10-27_final.stac-item
2019-10-27 09:36:43	ga_s2bm_ard_3-2-1_55HGA_2019-10-27_final.stac-item
2019-10-27 09:36:47	ga_s2bm_ard_3-2-1_55HFA_2019-10-27_final.stac-item
2019-10-27 09:36:51	ga_s2bm_ard_3-2-1_55HEA_2019-10-27_final.stac-item
2019-10-27 09:36:57	ga_s2bm_ard_3-2-1_55HGV_2019-10-27_final.stac-item
2019-10-27 09:37:01	ga_s2bm_ard_3-2-1_55HFV_2019-10-27_final.stac-item
2019-10-27 09:37:05	ga_s2bm_ard_3-2-1_55HEV_2019-10-27_final.stac-item
2019-10-27 09:37:19	ga_s2bm_ard_3-2-1_55HEU_2019-10-27_final.stac-item
2019-10-27 09:37:34	ga_s2bm_ard_3-2-1_55HET_2019-10-27_final.stac-item
2019-10-27 09:37:41	ga_s2bm_ard_3-2-1_55HDT_2019-10-27_final.stac-item
2019-10-27 09:37:48	ga_s2bm_ard_3-2-1_55HES_2019-10-27_final.stac-item
2019-10-27 09:37:52	ga_s2bm_ard_3-2-1_55HDS_2019-10-27_final.stac-item
2019-10-27 09:37:59	ga_s2bm_ard_3-2-1_55GFR_2019-10-27_final.stac-item
2019-10-27 09:38:03	ga_s2bm_ard_3-2-1_55GER_2019-10-27_final.stac-item
2019-10-27 09:38:06	ga_s2bm_ard_3-2-1_55GDR_2019-10-27_final.stac-item
2019-10-27 09:38:13	ga_s2bm_ard_3-2-1_55GFQ_2019-10-27_final.stac-item
2019-10-27 09:38:17	ga_s2bm_ard_3-2-1_55GEQ_2019-10-27_final.stac-item
2019-10-27 09:38:20	ga_s2bm_ard_3-2-1_55GDQ_2019-10-27_final.stac-item
2019-10-27 09:38:23	ga_s2bm_ard_3-2-1_55GFP_2019-10-27_final.stac-item
2019-10-27 09:38:25	ga_s2bm_ard_3-2-1_55GEQ_2019-10-27_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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