Search ga_s2bm_ard_3 across December 2019

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
2019-12-01 10:25:24	ga_s2bm_ard_3-2-1_54JUM_2019-12-01_final.stac-item
2019-12-01 10:25:27	ga_s2bm_ard_3-2-1_54JTM_2019-12-01_final.stac-item
2019-12-01 10:25:29	ga_s2bm_ard_3-2-1_53JQG_2019-12-01_final.stac-item
2019-12-01 10:25:31	ga_s2bm_ard_3-2-1_54JVL_2019-12-01_final.stac-item
2019-12-01 10:25:35	ga_s2bm_ard_3-2-1_53JPG_2019-12-01_final.stac-item
2019-12-01 10:25:38	ga_s2bm_ard_3-2-1_54JUL_2019-12-01_final.stac-item
2019-12-01 10:25:41	ga_s2bm_ard_3-2-1_54JTL_2019-12-01_final.stac-item
2019-12-01 10:25:44	ga_s2bm_ard_3-2-1_53JQF_2019-12-01_final.stac-item
2019-12-01 10:25:47	ga_s2bm_ard_3-2-1_53JPF_2019-12-01_final.stac-item
2019-12-01 10:25:52	ga_s2bm_ard_3-2-1_54HUK_2019-12-01_final.stac-item
2019-12-01 10:25:56	ga_s2bm_ard_3-2-1_54HTK_2019-12-01_final.stac-item
2019-12-01 10:25:58	ga_s2bm_ard_3-2-1_53HQE_2019-12-01_final.stac-item
2019-12-01 10:26:02	ga_s2bm_ard_3-2-1_53HPE_2019-12-01_final.stac-item
2019-12-01 10:26:07	ga_s2bm_ard_3-2-1_54HUJ_2019-12-01_final.stac-item
2019-12-01 10:26:11	ga_s2bm_ard_3-2-1_54HTJ_2019-12-01_final.stac-item
2019-12-01 10:26:13	ga_s2bm_ard_3-2-1_53HQD_2019-12-01_final.stac-item
2019-12-01 10:26:17	ga_s2bm_ard_3-2-1_53HPD_2019-12-01_final.stac-item
2019-12-01 10:26:22	ga_s2bm_ard_3-2-1_54HUH_2019-12-01_final.stac-item
2019-12-01 10:26:25	ga_s2bm_ard_3-2-1_54HTH_2019-12-01_final.stac-item
2019-12-01 10:26:27	ga_s2bm_ard_3-2-1_53HQC_2019-12-01_final.stac-item
2019-12-01 10:26:31	ga_s2bm_ard_3-2-1_53HPC_2019-12-01_final.stac-item
2019-12-01 10:26:35	ga_s2bm_ard_3-2-1_54HUG_2019-12-01_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 10:26:40	ga_s2bm_ard_3-2-1_54HTG_2019-12-01_final.stac-item
2019-12-01 10:26:41	ga_s2bm_ard_3-2-1_53HQB_2019-12-01_final.stac-item
2019-12-01 10:26:43	ga_s2bm_ard_3-2-1_53HPB_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
2019-12-01 10:26:45	ga_s2bm_ard_3-2-1_54HUF_2019-12-01_final.stac-item
2019-12-01 10:26:47	ga_s2bm_ard_3-2-1_54HUF_2019-12-01_final.stac-item
2019-12-01 10:26:47	ga_s2bm_ard_3-2-1_54HTF_2019-12-01_final.stac-item
2019-12-01 10:26:47	ga_s2bm_ard_3-2-1_54HTG_2019-12-01_final.stac-item
2019-12-01 10:26:48	ga_s2bm_ard_3-2-1_53HQA_2019-12-01_final.stac-item
2019-12-01 10:26:48	ga_s2bm_ard_3-2-1_53HQB_2019-12-01_final.stac-item
2019-12-01 10:26:50	ga_s2bm_ard_3-2-1_53HPB_2019-12-01_final.stac-item
2019-12-01 10:26:51	ga_s2bm_ard_3-2-1_53HNB_2019-12-01_final.stac-item
2019-12-01 10:26:54	ga_s2bm_ard_3-2-1_54HTF_2019-12-01_final.stac-item
2019-12-01 10:26:56	ga_s2bm_ard_3-2-1_53HQA_2019-12-01_final.stac-item
2019-12-01 10:27:00	ga_s2bm_ard_3-2-1_53HPA_2019-12-01_final.stac-item
2019-12-01 12:03:11	ga_s2bm_ard_3-2-1_50KNC_2019-12-01_final.stac-item
2019-12-01 12:03:13	ga_s2bm_ard_3-2-1_50KMC_2019-12-01_final.stac-item
2019-12-01 12:03:15	ga_s2bm_ard_3-2-1_50KLC_2019-12-01_final.stac-item
2019-12-01 12:03:18	ga_s2bm_ard_3-2-1_50KNC_2019-12-01_final.stac-item
2019-12-01 12:03:20	ga_s2bm_ard_3-2-1_50KMC_2019-12-01_final.stac-item
2019-12-01 12:03:22	ga_s2bm_ard_3-2-1_50KLC_2019-12-01_final.stac-item
2019-12-01 12:03:28	ga_s2bm_ard_3-2-1_50KNB_2019-12-01_final.stac-item
2019-12-01 12:03:33	ga_s2bm_ard_3-2-1_50KMB_2019-12-01_final.stac-item
2019-12-01 12:03:36	ga_s2bm_ard_3-2-1_50KLB_2019-12-01_final.stac-item
2019-12-01 12:03:39	ga_s2bm_ard_3-2-1_50KKB_2019-12-01_final.stac-item
2019-12-01 12:03:39	ga_s2bm_ard_3-2-1_50KNA_2019-12-01_final.stac-item
2019-12-01 12:03:47	ga_s2bm_ard_3-2-1_50KMA_2019-12-01_final.stac-item
2019-12-01 12:03:51	ga_s2bm_ard_3-2-1_50KLA_2019-12-01_final.stac-item
2019-12-01 12:03:54	ga_s2bm_ard_3-2-1_50KKA_2019-12-01_final.stac-item
2019-12-01 12:03:54	ga_s2bm_ard_3-2-1_49KHR_2019-12-01_final.stac-item
2019-12-01 12:04:01	ga_s2bm_ard_3-2-1_50KMV_2019-12-01_final.stac-item
2019-12-01 12:04:05	ga_s2bm_ard_3-2-1_50KLV_2019-12-01_final.stac-item
2019-12-01 12:04:08	ga_s2bm_ard_3-2-1_50KKV_2019-12-01_final.stac-item
2019-12-01 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2019-12-01_final.stac-item
2019-12-01 12:04:13	ga_s2bm_ard_3-2-1_49KGQ_2019-12-01_final.stac-item
2019-12-01 12:04:16	ga_s2bm_ard_3-2-1_50KMU_2019-12-01_final.stac-item
2019-12-02 09:55:42	ga_s2bm_ard_3-2-1_55HDE_2019-12-02_final.stac-item
2019-12-02 09:55:45	ga_s2bm_ard_3-2-1_55HCE_2019-12-02_final.stac-item
2019-12-02 09:55:48	ga_s2bm_ard_3-2-1_55HBE_2019-12-02_final.stac-item
2019-12-02 09:55:49	ga_s2bm_ard_3-2-1_55HED_2019-12-02_final.stac-item
2019-12-02 09:55:52	ga_s2bm_ard_3-2-1_54HYK_2019-12-02_final.stac-item
2019-12-02 09:55:56	ga_s2bm_ard_3-2-1_55HDD_2019-12-02_final.stac-item
2019-12-02 09:56:00	ga_s2bm_ard_3-2-1_55HCD_2019-12-02_final.stac-item
2019-12-02 09:56:03	ga_s2bm_ard_3-2-1_55HBD_2019-12-02_final.stac-item
2019-12-02 09:56:05	ga_s2bm_ard_3-2-1_54HYJ_2019-12-02_final.stac-item
2019-12-02 09:56:10	ga_s2bm_ard_3-2-1_55HDC_2019-12-02_final.stac-item
2019-12-02 09:56:14	ga_s2bm_ard_3-2-1_55HCC_2019-12-02_final.stac-item
2019-12-02 09:56:17	ga_s2bm_ard_3-2-1_55HBC_2019-12-02_final.stac-item
2019-12-02 09:56:19	ga_s2bm_ard_3-2-1_54HYH_2019-12-02_final.stac-item
2019-12-02 09:56:25	ga_s2bm_ard_3-2-1_55HDB_2019-12-02_final.stac-item
2019-12-02 09:56:29	ga_s2bm_ard_3-2-1_55HCB_2019-12-02_final.stac-item
2019-12-02 09:56:32	ga_s2bm_ard_3-2-1_55HBB_2019-12-02_final.stac-item
2019-12-02 09:56:34	ga_s2bm_ard_3-2-1_54HYG_2019-12-02_final.stac-item
2019-12-02 09:56:40	ga_s2bm_ard_3-2-1_55HDA_2019-12-02_final.stac-item
2019-12-02 09:56:41	ga_s2bm_ard_3-2-1_54HXG_2019-12-02_final.stac-item
2019-12-02 09:56:43	ga_s2bm_ard_3-2-1_55HCA_2019-12-02_final.stac-item
2019-12-02 09:56:47	ga_s2bm_ard_3-2-1_55HBA_2019-12-02_final.stac-item
2019-12-02 09:56:48	ga_s2bm_ard_3-2-1_54HYF_2019-12-02_final.stac-item
2019-12-02 09:56:52	ga_s2bm_ard_3-2-1_54HXF_2019-12-02_final.stac-item
2019-12-02 09:56:53	ga_s2bm_ard_3-2-1_55HDV_2019-12-02_final.stac-item
2019-12-02 09:56:58	ga_s2bm_ard_3-2-1_55HCV_2019-12-02_final.stac-item
2019-12-02 09:57:01	ga_s2bm_ard_3-2-1_55HBV_2019-12-02_final.stac-item
2019-12-02 09:57:02	ga_s2bm_ard_3-2-1_54HYE_2019-12-02_final.stac-item
2019-12-02 09:57:03	ga_s2bm_ard_3-2-1_55HDU_2019-12-02_final.stac-item
2019-12-02 09:57:06	ga_s2bm_ard_3-2-1_54HXE_2019-12-02_final.stac-item
2019-12-02 09:57:12	ga_s2bm_ard_3-2-1_55HCU_2019-12-02_final.stac-item
2019-12-02 09:57:16	ga_s2bm_ard_3-2-1_55HBU_2019-12-02_final.stac-item
2019-12-02 09:57:17	ga_s2bm_ard_3-2-1_54HYD_2019-12-02_final.stac-item
2019-12-02 09:57:21	ga_s2bm_ard_3-2-1_54HXD_2019-12-02_final.stac-item
2019-12-02 09:57:27	ga_s2bm_ard_3-2-1_55HCT_2019-12-02_final.stac-item
2019-12-02 09:57:30	ga_s2bm_ard_3-2-1_55HBT_2019-12-02_final.stac-item
2019-12-02 09:57:31	ga_s2bm_ard_3-2-1_54HYC_2019-12-02_final.stac-item
2019-12-02 09:57:35	ga_s2bm_ard_3-2-1_54HXC_2019-12-02_final.stac-item
2019-12-02 09:57:40	ga_s2bm_ard_3-2-1_54HWC_2019-12-02_final.stac-item
2019-12-02 09:57:42	ga_s2bm_ard_3-2-1_55HCS_2019-12-02_final.stac-item
2019-12-02 09:57:45	ga_s2bm_ard_3-2-1_55HBS_2019-12-02_final.stac-item
2019-12-02 09:57:45	ga_s2bm_ard_3-2-1_54HYB_2019-12-02_final.stac-item

Return to ga_s2bm_ard_3 across December 2019 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

2019

December

All days