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
2019-01-11 10:41:19	ga_s2bm_ard_3-2-1_53LQD_2019-01-11_final.stac-item
2019-01-11 10:41:33	ga_s2bm_ard_3-2-1_53LQC_2019-01-11_final
2019-01-11 10:41:48	ga_s2bm_ard_3-2-1_53KQB_2019-01-11_final
2019-01-11 10:42:02	ga_s2bm_ard_3-2-1_53KQA_2019-01-11_final.stac-item
2019-01-11 10:42:17	ga_s2bm_ard_3-2-1_53KQV_2019-01-11_final.stac-item
2019-01-11 10:42:31	ga_s2bm_ard_3-2-1_53KQU_2019-01-11_final.stac-item
2019-01-11 10:42:46	ga_s2bm_ard_3-2-1_53KQT_2019-01-11_final.stac-item
2019-01-11 10:43:00	ga_s2bm_ard_3-2-1_53KQS_2019-01-11_final.stac-item
2019-01-11 10:43:13	ga_s2bm_ard_3-2-1_53KQR_2019-01-11_final.stac-item
2019-01-15 10:25:34	ga_s2bm_ard_3-2-1_53JQG_2019-01-15_final.stac-item
2019-01-15 10:25:39	ga_s2bm_ard_3-2-1_53JPG_2019-01-15_final.stac-item
2019-01-15 10:25:48	ga_s2bm_ard_3-2-1_53JQF_2019-01-15_final.stac-item
2019-01-15 10:25:52	ga_s2bm_ard_3-2-1_53JPF_2019-01-15_final.stac-item
2019-01-15 10:26:03	ga_s2bm_ard_3-2-1_53HQE_2019-01-15_final.stac-item
2019-01-18 10:32:51	ga_s2bm_ard_3-2-1_53KQT_2019-01-18_final.stac-item
2019-01-18 10:33:05	ga_s2bm_ard_3-2-1_53KQS_2019-01-18_final.stac-item
2019-01-18 10:33:20	ga_s2bm_ard_3-2-1_53KQR_2019-01-18_final.stac-item
2019-01-18 10:33:34	ga_s2bm_ard_3-2-1_53KQQ_2019-01-18_final.stac-item
2019-01-18 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2019-01-18_final.stac-item
2019-01-18 10:34:03	ga_s2bm_ard_3-2-1_53JQN_2019-01-18_final.stac-item
2019-01-18 10:35:00	ga_s2bm_ard_3-2-1_53JPJ_2019-01-18_final.stac-item
2019-01-18 10:35:06	ga_s2bm_ard_3-2-1_53JPJ_2019-01-18_final.stac-item
2019-01-18 10:35:19	ga_s2bm_ard_3-2-1_53JPH_2019-01-18_final.stac-item
2019-01-18 10:35:34	ga_s2bm_ard_3-2-1_53JPG_2019-01-18_final.stac-item
2019-01-18 10:35:48	ga_s2bm_ard_3-2-1_53JPF_2019-01-18_final.stac-item
2019-01-18 10:35:56	ga_s2bm_ard_3-2-1_53HQE_2019-01-18_final.stac-item
2019-01-18 10:36:02	ga_s2bm_ard_3-2-1_53HPE_2019-01-18_final.stac-item
2019-02-10 10:41:20	ga_s2bm_ard_3-2-1_53LQD_2019-02-10_final.stac-item
2019-02-10 10:41:35	ga_s2bm_ard_3-2-1_53LQC_2019-02-10_final
2019-02-10 10:41:49	ga_s2bm_ard_3-2-1_53KQB_2019-02-10_final
2019-02-10 10:42:03	ga_s2bm_ard_3-2-1_53KQA_2019-02-10_final.stac-item
2019-02-10 10:42:18	ga_s2bm_ard_3-2-1_53KQV_2019-02-10_final.stac-item
2019-02-10 10:42:32	ga_s2bm_ard_3-2-1_53KQU_2019-02-10_final.stac-item
2019-02-10 10:42:47	ga_s2bm_ard_3-2-1_53KQT_2019-02-10_final.stac-item
2019-02-10 10:43:01	ga_s2bm_ard_3-2-1_53KQS_2019-02-10_final.stac-item
2019-02-10 10:43:10	ga_s2bm_ard_3-2-1_53KQR_2019-02-10_final.stac-item
2019-02-10 10:43:15	ga_s2bm_ard_3-2-1_53KQR_2019-02-10_final.stac-item
2019-02-14 10:25:34	ga_s2bm_ard_3-2-1_53JQG_2019-02-14_final.stac-item
2019-02-14 10:25:40	ga_s2bm_ard_3-2-1_53JPG_2019-02-14_final.stac-item
2019-02-14 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2019-02-14_final.stac-item
2019-02-14 10:25:52	ga_s2bm_ard_3-2-1_53JPF_2019-02-14_final.stac-item
2019-02-14 10:26:03	ga_s2bm_ard_3-2-1_53HQE_2019-02-14_final.stac-item
2019-02-14 10:26:07	ga_s2bm_ard_3-2-1_53HPE_2019-02-14_final.stac-item
2019-02-14 10:26:18	ga_s2bm_ard_3-2-1_53HQD_2019-02-14_final.stac-item
2019-02-14 10:26:21	ga_s2bm_ard_3-2-1_53HPD_2019-02-14_final.stac-item
2019-02-14 10:26:36	ga_s2bm_ard_3-2-1_53HPC_2019-02-14_final.stac-item
2019-02-14 10:26:50	ga_s2bm_ard_3-2-1_53HPB_2019-02-14_final.stac-item
2019-02-14 10:27:05	ga_s2bm_ard_3-2-1_53HPA_2019-02-14_final.stac-item
2019-02-17 10:32:51	ga_s2bm_ard_3-2-1_53KQT_2019-02-17_final.stac-item
2019-02-17 10:33:05	ga_s2bm_ard_3-2-1_53KQS_2019-02-17_final.stac-item
2019-02-17 10:33:20	ga_s2bm_ard_3-2-1_53KQR_2019-02-17_final.stac-item
2019-02-17 10:33:34	ga_s2bm_ard_3-2-1_53KQQ_2019-02-17_final.stac-item
2019-02-17 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2019-02-17_final.stac-item
2019-02-17 10:34:03	ga_s2bm_ard_3-2-1_53JQN_2019-02-17_final.stac-item
2019-02-20 10:41:19	ga_s2bm_ard_3-2-1_53LQD_2019-02-20_final.stac-item
2019-02-20 10:41:34	ga_s2bm_ard_3-2-1_53LQC_2019-02-20_final
2019-02-20 10:41:48	ga_s2bm_ard_3-2-1_53KQB_2019-02-20_final
2019-02-20 10:42:03	ga_s2bm_ard_3-2-1_53KQA_2019-02-20_final.stac-item
2019-02-20 10:42:10	ga_s2bm_ard_3-2-1_53KQA_2019-02-20_final.stac-item
2019-02-20 10:42:10	ga_s2bm_ard_3-2-1_53KQV_2019-02-20_final.stac-item
2019-02-20 10:42:17	ga_s2bm_ard_3-2-1_53KQV_2019-02-20_final.stac-item
2019-02-20 10:42:31	ga_s2bm_ard_3-2-1_53KQU_2019-02-20_final.stac-item
2019-02-20 10:42:46	ga_s2bm_ard_3-2-1_53KQT_2019-02-20_final.stac-item
2019-02-20 10:43:01	ga_s2bm_ard_3-2-1_53KQS_2019-02-20_final.stac-item
2019-02-20 10:43:14	ga_s2bm_ard_3-2-1_53KQR_2019-02-20_final.stac-item
2019-02-24 10:25:33	ga_s2bm_ard_3-2-1_53JQG_2019-02-24_final.stac-item
2019-02-24 10:25:39	ga_s2bm_ard_3-2-1_53JPG_2019-02-24_final.stac-item
2019-02-24 10:25:48	ga_s2bm_ard_3-2-1_53JQF_2019-02-24_final.stac-item
2019-02-24 10:25:51	ga_s2bm_ard_3-2-1_53JPF_2019-02-24_final.stac-item
2019-02-24 10:26:02	ga_s2bm_ard_3-2-1_53HQE_2019-02-24_final.stac-item
2019-02-24 10:26:06	ga_s2bm_ard_3-2-1_53HPE_2019-02-24_final.stac-item
2019-02-24 10:26:17	ga_s2bm_ard_3-2-1_53HQD_2019-02-24_final.stac-item
2019-02-24 10:26:21	ga_s2bm_ard_3-2-1_53HPD_2019-02-24_final.stac-item
2019-02-24 10:26:35	ga_s2bm_ard_3-2-1_53HPC_2019-02-24_final.stac-item
2019-02-24 10:26:49	ga_s2bm_ard_3-2-1_53HPB_2019-02-24_final.stac-item
2019-02-24 10:27:04	ga_s2bm_ard_3-2-1_53HPA_2019-02-24_final.stac-item
2019-02-27 10:32:50	ga_s2bm_ard_3-2-1_53KQT_2019-02-27_final.stac-item
2019-02-27 10:33:04	ga_s2bm_ard_3-2-1_53KQS_2019-02-27_final.stac-item
2019-02-27 10:33:19	ga_s2bm_ard_3-2-1_53KQR_2019-02-27_final.stac-item
2019-02-27 10:33:33	ga_s2bm_ard_3-2-1_53KQQ_2019-02-27_final.stac-item
2019-02-27 10:33:48	ga_s2bm_ard_3-2-1_53KQP_2019-02-27_final.stac-item
2019-02-27 10:34:02	ga_s2bm_ard_3-2-1_53JQN_2019-02-27_final.stac-item
2019-02-27 10:34:17	ga_s2bm_ard_3-2-1_53JQM_2019-02-27_final.stac-item
2019-02-27 10:34:31	ga_s2bm_ard_3-2-1_53JQL_2019-02-27_final.stac-item
2019-02-27 10:34:46	ga_s2bm_ard_3-2-1_53JQK_2019-02-27_final.stac-item
2019-02-27 10:34:49	ga_s2bm_ard_3-2-1_53JPK_2019-02-27_final.stac-item
2019-02-27 10:35:00	ga_s2bm_ard_3-2-1_53JQJ_2019-02-27_final.stac-item
2019-02-27 10:35:04	ga_s2bm_ard_3-2-1_53JPJ_2019-02-27_final.stac-item
2019-06-10 10:41:27	ga_s2bm_ard_3-2-1_53LQD_2019-06-10_final.stac-item
2019-06-14 10:25:42	ga_s2bm_ard_3-2-1_53JQG_2019-06-14_final.stac-item
2019-06-14 10:25:47	ga_s2bm_ard_3-2-1_53JPG_2019-06-14_final.stac-item
2019-06-14 10:25:56	ga_s2bm_ard_3-2-1_53JQF_2019-06-14_final.stac-item
2019-06-14 10:26:00	ga_s2bm_ard_3-2-1_53JPF_2019-06-14_final.stac-item
2019-06-14 10:26:11	ga_s2bm_ard_3-2-1_53HQE_2019-06-14_final.stac-item
2019-06-14 10:26:14	ga_s2bm_ard_3-2-1_53HPE_2019-06-14_final.stac-item
2019-06-14 10:26:25	ga_s2bm_ard_3-2-1_53HQD_2019-06-14_final.stac-item
2019-06-14 10:26:29	ga_s2bm_ard_3-2-1_53HPD_2019-06-14_final.stac-item
2019-06-14 10:26:43	ga_s2bm_ard_3-2-1_53HPC_2019-06-14_final.stac-item
2019-06-14 10:26:58	ga_s2bm_ard_3-2-1_53HPB_2019-06-14_final.stac-item
2019-06-14 10:27:12	ga_s2bm_ard_3-2-1_53HPA_2019-06-14_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

All years