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
2019-09-21 10:54:55	ga_s2bm_ard_3-2-1_53JKK_2019-09-21_final.stac-item
2019-09-21 10:55:09	ga_s2bm_ard_3-2-1_53JKJ_2019-09-21_final.stac-item
2019-09-21 10:55:15	ga_s2bm_ard_3-2-1_53JLH_2019-09-21_final.stac-item
2019-09-21 10:55:22	ga_s2bm_ard_3-2-1_52JEP_2019-09-21_final.stac-item
2019-09-21 10:55:24	ga_s2bm_ard_3-2-1_53JKH_2019-09-21_final.stac-item
2019-09-21 10:55:34	ga_s2bm_ard_3-2-1_52JEN_2019-09-21_final.stac-item
2019-09-21 10:55:38	ga_s2bm_ard_3-2-1_53JKG_2019-09-21_final.stac-item
2019-09-21 10:55:45	ga_s2bm_ard_3-2-1_52JFM_2019-09-21_final.stac-item
2019-09-21 10:55:48	ga_s2bm_ard_3-2-1_52JEM_2019-09-21_final.stac-item
2019-09-21 10:55:53	ga_s2bm_ard_3-2-1_53JKF_2019-09-21_final.stac-item
2019-09-21 10:55:59	ga_s2bm_ard_3-2-1_52JFL_2019-09-21_final.stac-item
2019-09-21 10:56:03	ga_s2bm_ard_3-2-1_52JEL_2019-09-21_final.stac-item
2019-09-22 10:22:34	ga_s2bm_ard_3-2-1_54KUD_2019-09-22_final.stac-item
2019-09-22 10:22:38	ga_s2bm_ard_3-2-1_54KXC_2019-09-22_final.stac-item
2019-09-22 10:22:41	ga_s2bm_ard_3-2-1_54KWC_2019-09-22_final.stac-item
2019-09-22 10:22:45	ga_s2bm_ard_3-2-1_54KVC_2019-09-22_final.stac-item
2019-09-22 10:22:48	ga_s2bm_ard_3-2-1_54KUC_2019-09-22_final.stac-item
2019-09-22 10:22:52	ga_s2bm_ard_3-2-1_54KXB_2019-09-22_final.stac-item
2019-09-22 10:22:56	ga_s2bm_ard_3-2-1_54KWB_2019-09-22_final.stac-item
2019-09-22 10:22:58	ga_s2bm_ard_3-2-1_54KVB_2019-09-22_final.stac-item
2019-09-22 10:23:00	ga_s2bm_ard_3-2-1_54KUB_2019-09-22_final.stac-item
2019-09-22 10:23:02	ga_s2bm_ard_3-2-1_54KXA_2019-09-22_final.stac-item
2019-09-22 10:23:04	ga_s2bm_ard_3-2-1_54KWB_2019-09-22_final.stac-item
2019-09-22 10:23:04	ga_s2bm_ard_3-2-1_54KWA_2019-09-22_final.stac-item
2019-09-22 10:23:05	ga_s2bm_ard_3-2-1_54KVB_2019-09-22_final.stac-item
2019-09-22 10:23:05	ga_s2bm_ard_3-2-1_54KVA_2019-09-22_final.stac-item
2019-09-22 10:23:07	ga_s2bm_ard_3-2-1_54KUB_2019-09-22_final.stac-item
2019-09-22 10:23:07	ga_s2bm_ard_3-2-1_54KXA_2019-09-22_final.stac-item
2019-09-22 10:23:11	ga_s2bm_ard_3-2-1_54KWA_2019-09-22_final.stac-item
2019-09-22 10:23:14	ga_s2bm_ard_3-2-1_54KVA_2019-09-22_final.stac-item
2019-09-22 10:23:17	ga_s2bm_ard_3-2-1_54KXV_2019-09-22_final.stac-item
2019-09-22 10:23:17	ga_s2bm_ard_3-2-1_54KUA_2019-09-22_final.stac-item
2019-09-22 10:23:25	ga_s2bm_ard_3-2-1_54KWV_2019-09-22_final.stac-item
2019-09-22 10:23:28	ga_s2bm_ard_3-2-1_54KVV_2019-09-22_final.stac-item
2019-09-22 10:23:32	ga_s2bm_ard_3-2-1_54KUV_2019-09-22_final.stac-item
2019-09-22 10:23:36	ga_s2bm_ard_3-2-1_54KTV_2019-09-22_final.stac-item
2019-09-22 10:23:39	ga_s2bm_ard_3-2-1_54KWU_2019-09-22_final.stac-item
2019-09-22 10:23:43	ga_s2bm_ard_3-2-1_54KVU_2019-09-22_final.stac-item
2019-09-22 10:23:46	ga_s2bm_ard_3-2-1_54KUU_2019-09-22_final.stac-item
2019-09-22 10:23:49	ga_s2bm_ard_3-2-1_54KTU_2019-09-22_final.stac-item
2019-09-22 10:23:50	ga_s2bm_ard_3-2-1_53KRP_2019-09-22_final.stac-item
2019-09-22 10:23:54	ga_s2bm_ard_3-2-1_54JWT_2019-09-22_final.stac-item
2019-09-22 10:23:57	ga_s2bm_ard_3-2-1_54JVT_2019-09-22_final.stac-item
2019-09-22 10:24:01	ga_s2bm_ard_3-2-1_54JUT_2019-09-22_final.stac-item
2019-09-22 10:24:03	ga_s2bm_ard_3-2-1_53JRN_2019-09-22_final.stac-item
2019-09-22 10:24:04	ga_s2bm_ard_3-2-1_54JTT_2019-09-22_final.stac-item
2019-09-22 10:24:08	ga_s2bm_ard_3-2-1_54JWS_2019-09-22_final.stac-item
2019-09-22 10:24:12	ga_s2bm_ard_3-2-1_54JVS_2019-09-22_final.stac-item
2019-09-22 10:24:15	ga_s2bm_ard_3-2-1_54JUS_2019-09-22_final.stac-item
2019-09-22 10:24:18	ga_s2bm_ard_3-2-1_53JRM_2019-09-22_final.stac-item
2019-09-22 10:24:18	ga_s2bm_ard_3-2-1_54JTS_2019-09-22_final.stac-item
2019-09-22 10:24:20	ga_s2bm_ard_3-2-1_54JWR_2019-09-22_final.stac-item
2019-09-22 10:24:26	ga_s2bm_ard_3-2-1_54JVR_2019-09-22_final.stac-item
2019-09-22 10:24:30	ga_s2bm_ard_3-2-1_54JUR_2019-09-22_final.stac-item
2019-09-22 10:24:30	ga_s2bm_ard_3-2-1_54JWQ_2019-09-22_final.stac-item
2019-09-22 10:24:33	ga_s2bm_ard_3-2-1_54JTR_2019-09-22_final.stac-item
2019-09-22 10:24:39	ga_s2bm_ard_3-2-1_53JQL_2019-09-22_final.stac-item
2019-09-22 10:24:41	ga_s2bm_ard_3-2-1_54JVQ_2019-09-22_final.stac-item
2019-09-22 10:24:45	ga_s2bm_ard_3-2-1_54JUQ_2019-09-22_final.stac-item
2019-09-22 10:24:48	ga_s2bm_ard_3-2-1_54JTQ_2019-09-22_final.stac-item
2019-09-22 10:24:51	ga_s2bm_ard_3-2-1_53JQK_2019-09-22_final.stac-item
2019-09-22 10:24:56	ga_s2bm_ard_3-2-1_54JVP_2019-09-22_final.stac-item
2019-09-22 10:24:59	ga_s2bm_ard_3-2-1_54JUP_2019-09-22_final.stac-item
2019-09-22 10:25:02	ga_s2bm_ard_3-2-1_54JTP_2019-09-22_final.stac-item
2019-09-22 10:25:05	ga_s2bm_ard_3-2-1_53JQJ_2019-09-22_final.stac-item
2019-09-22 10:25:10	ga_s2bm_ard_3-2-1_54JVN_2019-09-22_final.stac-item
2019-09-22 10:25:14	ga_s2bm_ard_3-2-1_54JUN_2019-09-22_final.stac-item
2019-09-22 10:25:17	ga_s2bm_ard_3-2-1_54JTN_2019-09-22_final.stac-item
2019-09-22 10:25:20	ga_s2bm_ard_3-2-1_53JQH_2019-09-22_final.stac-item
2019-09-22 10:25:24	ga_s2bm_ard_3-2-1_54JVM_2019-09-22_final.stac-item
2019-09-22 10:25:28	ga_s2bm_ard_3-2-1_54JUM_2019-09-22_final.stac-item
2019-09-22 10:25:31	ga_s2bm_ard_3-2-1_54JTM_2019-09-22_final.stac-item
2019-09-22 10:25:34	ga_s2bm_ard_3-2-1_53JQG_2019-09-22_final.stac-item
2019-09-22 10:25:35	ga_s2bm_ard_3-2-1_54JVL_2019-09-22_final.stac-item
2019-09-22 10:25:39	ga_s2bm_ard_3-2-1_53JPG_2019-09-22_final.stac-item
2019-09-22 10:25:42	ga_s2bm_ard_3-2-1_54JUL_2019-09-22_final.stac-item
2019-09-22 10:25:46	ga_s2bm_ard_3-2-1_54JTL_2019-09-22_final.stac-item
2019-09-22 10:25:48	ga_s2bm_ard_3-2-1_53JQF_2019-09-22_final.stac-item
2019-09-22 10:25:52	ga_s2bm_ard_3-2-1_53JPF_2019-09-22_final.stac-item
2019-09-22 10:25:57	ga_s2bm_ard_3-2-1_54HUK_2019-09-22_final.stac-item
2019-09-22 10:26:01	ga_s2bm_ard_3-2-1_54HTK_2019-09-22_final.stac-item
2019-09-22 10:26:03	ga_s2bm_ard_3-2-1_53HQE_2019-09-22_final.stac-item
2019-09-22 10:26:06	ga_s2bm_ard_3-2-1_53HPE_2019-09-22_final.stac-item
2019-09-22 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2019-09-22_final.stac-item
2019-09-22 10:26:15	ga_s2bm_ard_3-2-1_54HTJ_2019-09-22_final.stac-item
2019-09-22 10:26:17	ga_s2bm_ard_3-2-1_53HQD_2019-09-22_final.stac-item
2019-09-22 10:26:21	ga_s2bm_ard_3-2-1_53HPD_2019-09-22_final.stac-item
2019-09-22 10:26:26	ga_s2bm_ard_3-2-1_54HUH_2019-09-22_final.stac-item
2019-09-22 10:26:30	ga_s2bm_ard_3-2-1_54HTH_2019-09-22_final.stac-item
2019-09-22 10:26:32	ga_s2bm_ard_3-2-1_53HQC_2019-09-22_final.stac-item
2019-09-22 10:26:35	ga_s2bm_ard_3-2-1_53HPC_2019-09-22_final.stac-item
2019-09-22 10:26:40	ga_s2bm_ard_3-2-1_54HUG_2019-09-22_final.stac-item
2019-09-22 10:26:40	ga_s2bm_ard_3-2-1_53HNC_2019-09-22_final.stac-item
2019-09-22 10:26:44	ga_s2bm_ard_3-2-1_54HTG_2019-09-22_final.stac-item
2019-09-22 10:26:46	ga_s2bm_ard_3-2-1_53HQB_2019-09-22_final.stac-item
2019-09-22 10:26:50	ga_s2bm_ard_3-2-1_53HPB_2019-09-22_final.stac-item
2019-09-22 10:26:50	ga_s2bm_ard_3-2-1_54HUF_2019-09-22_final.stac-item
2019-09-22 10:26:53	ga_s2bm_ard_3-2-1_53HNB_2019-09-22_final.stac-item
2019-09-22 10:26:59	ga_s2bm_ard_3-2-1_54HTF_2019-09-22_final.stac-item
2019-09-22 10:27:00	ga_s2bm_ard_3-2-1_53HQA_2019-09-22_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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