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
2017-11-15 11:46:01	ga_s2bm_ard_3-2-1_50HPH_2017-11-15_final.stac-item
2017-11-15 11:46:01	ga_s2bm_ard_3-2-1_50HPJ_2017-11-15_final.stac-item
2017-11-15 11:46:01	ga_s2bm_ard_3-2-1_50HPK_2017-11-15_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HPH_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HPJ_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HPK_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HQH_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HQJ_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50HQK_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50JPL_2017-11-22_final.stac-item
2017-11-22 11:35:56	ga_s2bm_ard_3-2-1_50JQL_2017-11-22_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KQA_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KQB_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KQC_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KQU_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KQV_2017-11-28_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HPH_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HPJ_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HPK_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HQH_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HQJ_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50HQK_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50JPL_2017-12-02_final.stac-item
2017-12-02 11:34:20	ga_s2bm_ard_3-2-1_50JQL_2017-12-02_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50KQA_2018-08-05_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50KQB_2018-08-05_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50KQC_2018-08-05_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50KQU_2018-08-05_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50KQV_2018-08-05_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HPH_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HPJ_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HPK_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HQH_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HQJ_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50HQK_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50JPL_2018-08-09_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_50JQL_2018-08-09_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HPH_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HPJ_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HPK_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HQH_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HQJ_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50HQK_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JPL_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQL_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQM_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQN_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQP_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQQ_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQR_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQS_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50JQT_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50KQA_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50KQU_2018-08-12_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_50KQV_2018-08-12_final.stac-item
2018-08-15 11:43:38	ga_s2bm_ard_3-2-1_50KQA_2018-08-15_final.stac-item
2018-08-15 11:43:38	ga_s2bm_ard_3-2-1_50KQB_2018-08-15_final.stac-item
2018-08-15 11:43:38	ga_s2bm_ard_3-2-1_50KQC_2018-08-15_final.stac-item
2018-08-15 11:43:38	ga_s2bm_ard_3-2-1_50KQU_2018-08-15_final.stac-item
2018-08-15 11:43:38	ga_s2bm_ard_3-2-1_50KQV_2018-08-15_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HPH_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HPJ_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HPK_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HQH_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HQJ_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50HQK_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50JPL_2018-08-19_final.stac-item
2018-08-19 11:35:15	ga_s2bm_ard_3-2-1_50JQL_2018-08-19_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50JQR_2018-08-22_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50JQS_2018-08-22_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50JQT_2018-08-22_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50KQA_2018-08-22_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50KQU_2018-08-22_final.stac-item
2018-08-22 11:38:17	ga_s2bm_ard_3-2-1_50KQV_2018-08-22_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50KQA_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50KQB_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50KQC_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50KQU_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50KQV_2018-10-04_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQA_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQB_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQC_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQU_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQV_2018-10-14_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HPH_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HPJ_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HPK_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HQH_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HQJ_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50HQK_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50JPL_2018-10-18_final.stac-item
2018-10-18 11:35:22	ga_s2bm_ard_3-2-1_50JQL_2018-10-18_final.stac-item
2019-01-02 11:53:15	ga_s2bm_ard_3-2-1_50KQC_2019-01-02_final.stac-item
2019-01-02 11:53:29	ga_s2bm_ard_3-2-1_50KQB_2019-01-02_final.stac-item
2019-01-02 11:53:44	ga_s2bm_ard_3-2-1_50KQA_2019-01-02_final.stac-item
2019-01-02 11:53:58	ga_s2bm_ard_3-2-1_50KQV_2019-01-02_final.stac-item
2019-01-02 11:54:11	ga_s2bm_ard_3-2-1_50KQU_2019-01-02_final.stac-item
2020-01-21 11:36:13	ga_s2bm_ard_3-2-1_50JQL_2020-01-21_final.stac-item
2020-01-21 11:36:20	ga_s2bm_ard_3-2-1_50JPL_2020-01-21_final.stac-item
2020-01-21 11:36:27	ga_s2bm_ard_3-2-1_50HQK_2020-01-21_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