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
2017-07-05 11:32:58	ga_s2bm_ard_3-2-1_51JUJ_2017-07-05_final.stac-item
2017-10-27 11:11:48	ga_s2bm_ard_3-2-1_51JYN_2017-10-27_final.stac-item
2017-10-30 11:20:19	ga_s2bm_ard_3-2-1_51JYN_2017-10-30_final.stac-item
2017-10-30 11:20:19	ga_s2bm_ard_3-2-1_51KYQ_2017-10-30_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JKP_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50JLT_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KMA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KNA_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KNB_2017-11-01_final.stac-item
2017-11-01 12:02:36	ga_s2bm_ard_3-2-1_50KNC_2017-11-01_final.stac-item
2017-11-02 11:30:27	ga_s2bm_ard_3-2-1_51KUS_2017-11-02_final.stac-item
2017-11-02 11:30:27	ga_s2bm_ard_3-2-1_51KVQ_2017-11-02_final.stac-item
2017-11-02 11:30:27	ga_s2bm_ard_3-2-1_51KVR_2017-11-02_final.stac-item
2017-11-02 11:30:27	ga_s2bm_ard_3-2-1_51KXT_2017-11-02_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50JPT_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50KPU_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50KPV_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50KQV_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50KRV_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_51KTT_2017-11-05_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_51KUS_2017-11-05_final.stac-item
2017-11-08 11:44:06	ga_s2bm_ard_3-2-1_50KNC_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JKN_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JKP_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JPT_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JQT_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KMA_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KNA_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KNB_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KNC_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KPU_2017-11-08_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50KQV_2017-11-08_final.stac-item
2017-11-09 11:19:31	ga_s2bm_ard_3-2-1_51JYN_2017-11-09_final.stac-item
2017-11-09 11:19:31	ga_s2bm_ard_3-2-1_51KXT_2017-11-09_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_49JHM_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JKN_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JLT_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50KMA_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50KNA_2017-11-11_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50KNC_2017-11-11_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51KUS_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51KVR_2017-11-12_final.stac-item
2017-11-12 11:27:16	ga_s2bm_ard_3-2-1_51KXT_2017-11-12_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50JPT_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50JQT_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50KPU_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50KQU_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50KQV_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50KRV_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_51KTT_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_51KUS_2017-11-15_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_51KUT_2017-11-15_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50JKN_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50JKP_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50JPT_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KNA_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KNB_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KNC_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KPU_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KQU_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KQV_2017-11-18_final.stac-item
2017-11-19 11:16:47	ga_s2bm_ard_3-2-1_51JYM_2017-11-19_final.stac-item
2017-11-19 11:16:47	ga_s2bm_ard_3-2-1_51JYN_2017-11-19_final.stac-item
2017-11-19 11:16:47	ga_s2bm_ard_3-2-1_51KXT_2017-11-19_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_49JHM_2017-11-21_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50JKN_2017-11-21_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50JLT_2017-11-21_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50KMA_2017-11-21_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50KNA_2017-11-21_final.stac-item
2017-11-21 12:02:37	ga_s2bm_ard_3-2-1_50KNC_2017-11-21_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KUS_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KUT_2017-11-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_51KXT_2017-11-22_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50JRS_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50KPU_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50KPV_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50KQV_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50KRV_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_51KTT_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_51KUS_2017-11-25_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_51KVR_2017-11-25_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50JKP_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50JLT_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50JQT_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KMA_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KNB_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KNC_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KNU_2017-11-28_final.stac-item
2017-11-28 11:50:34	ga_s2bm_ard_3-2-1_50KPV_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
2017-11-29 11:19:33	ga_s2bm_ard_3-2-1_51KXT_2017-11-29_final.stac-item
2017-12-01 12:02:38	ga_s2bm_ard_3-2-1_50JLM_2017-12-01_final.stac-item
2017-12-06 11:11:50	ga_s2bm_ard_3-2-1_51HYE_2017-12-06_final.stac-item
2017-12-06 11:11:50	ga_s2bm_ard_3-2-1_51JYF_2017-12-06_final.stac-item
2017-12-06 11:11:50	ga_s2bm_ard_3-2-1_51JYG_2017-12-06_final.stac-item
2017-12-11 12:02:37	ga_s2bm_ard_3-2-1_50JLM_2017-12-11_final.stac-item
2017-12-16 11:07:00	ga_s2bm_ard_3-2-1_51JYF_2017-12-16_final.stac-item
2017-12-19 11:25:05	ga_s2bm_ard_3-2-1_51JYG_2017-12-19_final.stac-item
2017-12-21 12:02:37	ga_s2bm_ard_3-2-1_50JLM_2017-12-21_final.stac-item
2017-12-26 11:11:50	ga_s2bm_ard_3-2-1_51HYE_2017-12-26_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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