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
2017-09-10 11:16:51	ga_s2bm_ard_3-2-1_52KBG_2017-09-10_final.stac-item
2017-09-10 11:16:51	ga_s2bm_ard_3-2-1_52KCG_2017-09-10_final.stac-item
2017-09-10 11:16:51	ga_s2bm_ard_3-2-1_52KDG_2017-09-10_final.stac-item
2017-09-10 11:16:51	ga_s2bm_ard_3-2-1_51KYB_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_51KYB_2017-09-10_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KVB_2017-09-23_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KWB_2017-09-23_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KXB_2017-09-23_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KYB_2017-09-23_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KZB_2017-09-23_final.stac-item
2017-09-30 11:16:43	ga_s2bm_ard_3-2-1_52KBG_2017-09-30_final.stac-item
2017-09-30 11:16:43	ga_s2bm_ard_3-2-1_52KCG_2017-09-30_final.stac-item
2017-09-30 11:16:43	ga_s2bm_ard_3-2-1_52KDG_2017-09-30_final.stac-item
2017-09-30 11:16:43	ga_s2bm_ard_3-2-1_51KZB_2017-09-30_final.stac-item
2017-09-30 11:21:42	ga_s2bm_ard_3-2-1_52KBG_2017-09-30_final.stac-item
2017-09-30 11:21:42	ga_s2bm_ard_3-2-1_51KYB_2017-09-30_final.stac-item
2017-09-30 11:21:42	ga_s2bm_ard_3-2-1_51KZB_2017-09-30_final.stac-item
2017-10-03 09:50:38	ga_s2bm_ard_3-2-1_55KFB_2017-10-03_final.stac-item
2017-10-03 09:50:38	ga_s2bm_ard_3-2-1_55KGB_2017-10-03_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KCG_2017-10-07_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KDG_2017-10-07_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KEG_2017-10-07_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KFG_2017-10-07_final.stac-item
2017-10-07 11:06:57	ga_s2bm_ard_3-2-1_52KGG_2017-10-07_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KVB_2017-10-13_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KWB_2017-10-13_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KXB_2017-10-13_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KYB_2017-10-13_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KZB_2017-10-13_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KVB_2018-05-11_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KWB_2018-05-11_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KXB_2018-05-11_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KYB_2018-05-11_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KZB_2018-05-11_final.stac-item
2018-05-15 11:07:36	ga_s2bm_ard_3-2-1_52KCG_2018-05-15_final.stac-item
2018-05-15 11:07:36	ga_s2bm_ard_3-2-1_52KDG_2018-05-15_final.stac-item
2018-05-15 11:07:36	ga_s2bm_ard_3-2-1_52KEG_2018-05-15_final.stac-item
2018-05-15 11:07:36	ga_s2bm_ard_3-2-1_52KFG_2018-05-15_final.stac-item
2018-05-15 11:07:36	ga_s2bm_ard_3-2-1_52KGG_2018-05-15_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_53KKB_2018-05-22_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_53KLB_2018-05-22_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_52KFG_2018-05-22_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_52KGG_2018-05-22_final.stac-item
2018-05-22 10:57:13	ga_s2bm_ard_3-2-1_52KHG_2018-05-22_final.stac-item
2019-06-16 11:01:59	ga_s2bm_ard_3-2-1_53KLB_2019-06-16_final.stac-item
2019-06-16 11:02:03	ga_s2bm_ard_3-2-1_53KKB_2019-06-16_final.stac-item
2019-06-16 11:02:04	ga_s2bm_ard_3-2-1_52KHG_2019-06-16_final.stac-item
2019-06-16 11:02:08	ga_s2bm_ard_3-2-1_52KGG_2019-06-16_final.stac-item
2019-06-16 11:02:11	ga_s2bm_ard_3-2-1_52KFG_2019-06-16_final.stac-item
2019-12-02 11:31:54	ga_s2bm_ard_3-2-1_51KZB_2019-12-02_final.stac-item
2019-12-02 11:32:02	ga_s2bm_ard_3-2-1_51KYB_2019-12-02_final.stac-item
2019-12-02 11:32:06	ga_s2bm_ard_3-2-1_51KXB_2019-12-02_final.stac-item
2019-12-02 11:32:09	ga_s2bm_ard_3-2-1_51KWB_2019-12-02_final.stac-item
2019-12-02 11:32:14	ga_s2bm_ard_3-2-1_51KVB_2019-12-02_final.stac-item
2019-12-05 10:01:23	ga_s2bm_ard_3-2-1_55KFB_2019-12-05_final.stac-item
2019-12-05 10:01:26	ga_s2bm_ard_3-2-1_55KEB_2019-12-05_final.stac-item
2019-12-05 10:01:29	ga_s2bm_ard_3-2-1_55KDB_2019-12-05_final.stac-item
2019-12-05 10:01:32	ga_s2bm_ard_3-2-1_55KCB_2019-12-05_final.stac-item
2019-12-06 11:11:45	ga_s2bm_ard_3-2-1_52KGG_2019-12-06_final.stac-item
2019-12-06 11:11:53	ga_s2bm_ard_3-2-1_52KFG_2019-12-06_final.stac-item
2019-12-06 11:11:57	ga_s2bm_ard_3-2-1_52KEG_2019-12-06_final.stac-item
2019-12-06 11:12:00	ga_s2bm_ard_3-2-1_52KDG_2019-12-06_final.stac-item
2019-12-06 11:12:05	ga_s2bm_ard_3-2-1_52KCG_2019-12-06_final.stac-item
2019-12-09 11:21:50	ga_s2bm_ard_3-2-1_52KDG_2019-12-09_final.stac-item
2019-12-09 11:21:51	ga_s2bm_ard_3-2-1_52KCG_2019-12-09_final.stac-item
2019-12-09 11:21:55	ga_s2bm_ard_3-2-1_52KDG_2019-12-09_final.stac-item
2019-12-09 11:21:59	ga_s2bm_ard_3-2-1_52KCG_2019-12-09_final.stac-item
2019-12-09 11:22:02	ga_s2bm_ard_3-2-1_52KBG_2019-12-09_final.stac-item
2019-12-09 11:22:03	ga_s2bm_ard_3-2-1_51KZB_2019-12-09_final.stac-item
2019-12-09 11:22:06	ga_s2bm_ard_3-2-1_51KYB_2019-12-09_final.stac-item
2019-12-15 11:42:04	ga_s2bm_ard_3-2-1_51KWB_2019-12-15_final.stac-item
2019-12-15 11:42:08	ga_s2bm_ard_3-2-1_51KVB_2019-12-15_final.stac-item
2019-12-19 11:21:55	ga_s2bm_ard_3-2-1_52KDG_2019-12-19_final.stac-item
2019-12-19 11:21:59	ga_s2bm_ard_3-2-1_52KCG_2019-12-19_final.stac-item
2019-12-19 11:22:01	ga_s2bm_ard_3-2-1_52KBG_2019-12-19_final.stac-item
2019-12-19 11:22:01	ga_s2bm_ard_3-2-1_51KZB_2019-12-19_final.stac-item
2019-12-19 11:22:03	ga_s2bm_ard_3-2-1_51KYB_2019-12-19_final.stac-item
2019-12-23 11:01:47	ga_s2bm_ard_3-2-1_53KLB_2019-12-23_final.stac-item
2019-12-23 11:01:51	ga_s2bm_ard_3-2-1_53KKB_2019-12-23_final.stac-item
2019-12-23 11:01:52	ga_s2bm_ard_3-2-1_52KHG_2019-12-23_final.stac-item
2019-12-23 11:01:55	ga_s2bm_ard_3-2-1_52KGG_2019-12-23_final.stac-item
2019-12-23 11:01:59	ga_s2bm_ard_3-2-1_52KFG_2019-12-23_final.stac-item
2019-12-24 10:31:27	ga_s2bm_ard_3-2-1_54KWG_2019-12-24_final.stac-item
2019-12-24 10:31:37	ga_s2bm_ard_3-2-1_54KVG_2019-12-24_final.stac-item
2019-12-24 10:31:41	ga_s2bm_ard_3-2-1_54KUG_2019-12-24_final.stac-item
2019-12-24 10:31:44	ga_s2bm_ard_3-2-1_54KTG_2019-12-24_final.stac-item
2019-12-24 10:31:45	ga_s2bm_ard_3-2-1_53KRB_2019-12-24_final
2019-12-25 10:01:24	ga_s2bm_ard_3-2-1_55KFB_2019-12-25_final.stac-item
2019-12-25 10:01:27	ga_s2bm_ard_3-2-1_55KEB_2019-12-25_final.stac-item
2019-12-25 10:01:30	ga_s2bm_ard_3-2-1_55KDB_2019-12-25_final.stac-item
2019-12-25 10:01:33	ga_s2bm_ard_3-2-1_55KCB_2019-12-25_final.stac-item
2020-04-26 11:52:15	ga_s2bm_ard_3-2-1_50KQG_2020-04-26_final
2020-04-28 10:51:37	ga_s2bm_ard_3-2-1_53KPB_2020-04-28_final.stac-item
2020-04-28 10:51:46	ga_s2bm_ard_3-2-1_53KNB_2020-04-28_final.stac-item
2020-04-28 10:51:50	ga_s2bm_ard_3-2-1_53KMB_2020-04-28_final.stac-item
2020-04-28 10:51:53	ga_s2bm_ard_3-2-1_53KLB_2020-04-28_final.stac-item
2020-04-28 10:51:57	ga_s2bm_ard_3-2-1_53KKB_2020-04-28_final.stac-item
2020-05-13 11:42:08	ga_s2bm_ard_3-2-1_51KWB_2020-05-13_final.stac-item
2020-05-13 11:42:12	ga_s2bm_ard_3-2-1_51KVB_2020-05-13_final.stac-item
2020-05-13 11:42:15	ga_s2bm_ard_3-2-1_51KUB_2020-05-13_final

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