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
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HCB_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HCC_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HDB_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HDC_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HEB_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HEC_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HFB_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HFC_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HGB_2017-12-09_final.stac-item
2017-12-09 09:43:42	ga_s2bm_ard_3-2-1_55HGC_2017-12-09_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50HLH_2017-12-15_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50HMH_2017-12-15_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50HNH_2017-12-15_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50HPH_2017-12-15_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_51HTC_2017-12-22_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_51HUC_2017-12-22_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_50HPH_2017-12-22_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_50HQH_2017-12-22_final.stac-item
2019-08-24 09:56:21	ga_s2bm_ard_3-2-1_55HDC_2019-08-24_final.stac-item
2019-08-24 09:56:24	ga_s2bm_ard_3-2-1_55HCC_2019-08-24_final.stac-item
2019-08-24 09:56:28	ga_s2bm_ard_3-2-1_55HBC_2019-08-24_final.stac-item
2019-08-24 09:56:30	ga_s2bm_ard_3-2-1_54HYH_2019-08-24_final.stac-item
2019-08-24 09:56:36	ga_s2bm_ard_3-2-1_55HDB_2019-08-24_final.stac-item
2019-08-24 09:56:39	ga_s2bm_ard_3-2-1_55HCB_2019-08-24_final.stac-item
2019-08-24 09:56:42	ga_s2bm_ard_3-2-1_55HBB_2019-08-24_final.stac-item
2019-08-24 09:56:44	ga_s2bm_ard_3-2-1_54HYG_2019-08-24_final.stac-item
2019-09-09 10:16:25	ga_s2bm_ard_3-2-1_54HWH_2019-09-09_final.stac-item
2019-09-09 10:16:29	ga_s2bm_ard_3-2-1_54HVH_2019-09-09_final.stac-item
2019-09-09 10:16:32	ga_s2bm_ard_3-2-1_54HUH_2019-09-09_final.stac-item
2019-09-09 10:16:36	ga_s2bm_ard_3-2-1_54HTH_2019-09-09_final.stac-item
2019-09-09 10:16:40	ga_s2bm_ard_3-2-1_54HWG_2019-09-09_final.stac-item
2019-09-09 10:16:44	ga_s2bm_ard_3-2-1_54HVG_2019-09-09_final.stac-item
2019-09-09 10:16:47	ga_s2bm_ard_3-2-1_54HUG_2019-09-09_final.stac-item
2019-09-09 10:16:50	ga_s2bm_ard_3-2-1_54HTG_2019-09-09_final.stac-item
2019-09-09 10:16:53	ga_s2bm_ard_3-2-1_53HQB_2019-09-09_final.stac-item
2019-09-13 09:56:16	ga_s2bm_ard_3-2-1_55HDC_2019-09-13_final.stac-item
2019-09-13 09:56:20	ga_s2bm_ard_3-2-1_55HCC_2019-09-13_final.stac-item
2019-09-13 09:56:23	ga_s2bm_ard_3-2-1_55HBC_2019-09-13_final.stac-item
2019-09-13 09:56:25	ga_s2bm_ard_3-2-1_54HYH_2019-09-13_final.stac-item
2019-09-13 09:56:31	ga_s2bm_ard_3-2-1_55HDB_2019-09-13_final.stac-item
2019-09-13 09:56:35	ga_s2bm_ard_3-2-1_55HCB_2019-09-13_final.stac-item
2019-09-13 09:56:38	ga_s2bm_ard_3-2-1_55HBB_2019-09-13_final.stac-item
2019-09-13 09:56:40	ga_s2bm_ard_3-2-1_54HYG_2019-09-13_final.stac-item
2019-09-19 10:16:23	ga_s2bm_ard_3-2-1_54HWH_2019-09-19_final.stac-item
2019-09-19 10:16:27	ga_s2bm_ard_3-2-1_54HVH_2019-09-19_final.stac-item
2019-09-19 10:16:30	ga_s2bm_ard_3-2-1_54HUH_2019-09-19_final.stac-item
2019-09-19 10:16:33	ga_s2bm_ard_3-2-1_54HTH_2019-09-19_final.stac-item
2019-09-19 10:16:38	ga_s2bm_ard_3-2-1_54HWG_2019-09-19_final.stac-item
2019-09-19 10:16:41	ga_s2bm_ard_3-2-1_54HVG_2019-09-19_final.stac-item
2019-09-26 10:06:19	ga_s2bm_ard_3-2-1_55HBC_2019-09-26_final.stac-item
2019-09-26 10:06:20	ga_s2bm_ard_3-2-1_54HYH_2019-09-26_final.stac-item
2019-09-26 10:06:24	ga_s2bm_ard_3-2-1_54HXH_2019-09-26_final.stac-item
2019-09-26 10:06:28	ga_s2bm_ard_3-2-1_54HWH_2019-09-26_final.stac-item
2019-09-26 10:06:33	ga_s2bm_ard_3-2-1_55HBB_2019-09-26_final.stac-item
2019-09-26 10:06:34	ga_s2bm_ard_3-2-1_54HVH_2019-09-26_final.stac-item
2019-09-26 10:06:35	ga_s2bm_ard_3-2-1_54HYG_2019-09-26_final.stac-item
2019-09-26 10:06:39	ga_s2bm_ard_3-2-1_54HXG_2019-09-26_final.stac-item
2019-09-26 10:06:42	ga_s2bm_ard_3-2-1_54HWG_2019-09-26_final.stac-item
2019-09-26 10:06:46	ga_s2bm_ard_3-2-1_54HVG_2019-09-26_final.stac-item
2019-09-29 10:16:24	ga_s2bm_ard_3-2-1_54HWH_2019-09-29_final.stac-item
2019-09-29 10:16:28	ga_s2bm_ard_3-2-1_54HVH_2019-09-29_final.stac-item
2019-09-29 10:16:31	ga_s2bm_ard_3-2-1_54HUH_2019-09-29_final.stac-item
2019-09-29 10:16:34	ga_s2bm_ard_3-2-1_54HTH_2019-09-29_final.stac-item
2019-09-29 10:16:39	ga_s2bm_ard_3-2-1_54HWG_2019-09-29_final.stac-item
2019-09-29 10:16:43	ga_s2bm_ard_3-2-1_54HVG_2019-09-29_final.stac-item
2019-09-29 10:16:46	ga_s2bm_ard_3-2-1_54HUG_2019-09-29_final.stac-item
2019-09-29 10:16:49	ga_s2bm_ard_3-2-1_54HTG_2019-09-29_final.stac-item
2019-09-29 10:16:52	ga_s2bm_ard_3-2-1_53HQB_2019-09-29_final.stac-item
2019-10-03 09:56:16	ga_s2bm_ard_3-2-1_55HDC_2019-10-03_final.stac-item
2019-10-03 09:56:20	ga_s2bm_ard_3-2-1_55HCC_2019-10-03_final.stac-item
2019-10-03 09:56:23	ga_s2bm_ard_3-2-1_55HBC_2019-10-03_final.stac-item
2019-10-03 09:56:25	ga_s2bm_ard_3-2-1_54HYH_2019-10-03_final.stac-item
2019-10-03 09:56:31	ga_s2bm_ard_3-2-1_55HDB_2019-10-03_final.stac-item
2019-10-03 09:56:35	ga_s2bm_ard_3-2-1_55HCB_2019-10-03_final.stac-item
2019-10-03 09:56:38	ga_s2bm_ard_3-2-1_55HBB_2019-10-03_final.stac-item
2019-10-03 09:56:40	ga_s2bm_ard_3-2-1_54HYG_2019-10-03_final.stac-item
2019-10-05 10:36:33	ga_s2bm_ard_3-2-1_53HPC_2019-10-05_final.stac-item
2019-10-05 10:36:36	ga_s2bm_ard_3-2-1_53HNC_2019-10-05_final.stac-item
2019-10-05 10:36:47	ga_s2bm_ard_3-2-1_53HPB_2019-10-05_final.stac-item
2019-10-05 10:36:51	ga_s2bm_ard_3-2-1_53HNB_2019-10-05_final.stac-item
2019-10-22 10:26:28	ga_s2bm_ard_3-2-1_54HUH_2019-10-22_final.stac-item
2019-10-22 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2019-10-22_final.stac-item
2019-10-22 10:26:33	ga_s2bm_ard_3-2-1_53HQC_2019-10-22_final.stac-item
2019-10-22 10:26:37	ga_s2bm_ard_3-2-1_53HPC_2019-10-22_final.stac-item
2019-10-22 10:26:41	ga_s2bm_ard_3-2-1_54HUG_2019-10-22_final.stac-item
2019-10-22 10:26:42	ga_s2bm_ard_3-2-1_53HNC_2019-10-22_final.stac-item
2019-10-22 10:26:46	ga_s2bm_ard_3-2-1_54HTG_2019-10-22_final.stac-item
2019-10-22 10:26:48	ga_s2bm_ard_3-2-1_53HQB_2019-10-22_final.stac-item
2019-10-22 10:26:51	ga_s2bm_ard_3-2-1_53HPB_2019-10-22_final.stac-item
2019-10-22 10:26:55	ga_s2bm_ard_3-2-1_53HNB_2019-10-22_final.stac-item
2019-10-26 10:06:40	ga_s2bm_ard_3-2-1_54HXG_2019-10-26_final.stac-item
2019-10-26 10:06:43	ga_s2bm_ard_3-2-1_54HWG_2019-10-26_final.stac-item
2019-10-26 10:06:47	ga_s2bm_ard_3-2-1_54HVG_2019-10-26_final.stac-item
2019-10-29 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2019-10-29_final.stac-item
2019-10-29 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-29_final.stac-item
2019-10-30 11:26:59	ga_s2bm_ard_3-2-1_51HVC_2019-10-30_final.stac-item
2019-11-01 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2019-11-01_final.stac-item
2019-11-01 10:26:41	ga_s2bm_ard_3-2-1_53HNC_2019-11-01_final.stac-item
2019-11-01 10:26:45	ga_s2bm_ard_3-2-1_54HTG_2019-11-01_final.stac-item
2019-11-01 10:26:51	ga_s2bm_ard_3-2-1_53HPB_2019-11-01_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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