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
2019-03-20 10:01:28	ga_s2bm_ard_3-2-1_55KFB_2019-03-20_final.stac-item
2019-03-20 10:01:31	ga_s2bm_ard_3-2-1_55KEB_2019-03-20_final.stac-item
2019-03-20 10:01:34	ga_s2bm_ard_3-2-1_55KDB_2019-03-20_final.stac-item
2019-03-20 10:01:37	ga_s2bm_ard_3-2-1_55KCB_2019-03-20_final.stac-item
2019-03-22 10:41:43	ga_s2bm_ard_3-2-1_54KTG_2019-03-22_final.stac-item
2019-03-22 10:41:45	ga_s2bm_ard_3-2-1_53KRB_2019-03-22_final
2019-03-22 10:41:49	ga_s2bm_ard_3-2-1_53KQB_2019-03-22_final
2019-03-22 10:41:52	ga_s2bm_ard_3-2-1_53KPB_2019-03-22_final.stac-item
2019-03-22 10:41:54	ga_s2bm_ard_3-2-1_54KTF_2019-03-22_final.stac-item
2019-03-22 10:41:55	ga_s2bm_ard_3-2-1_53KNB_2019-03-22_final.stac-item
2019-03-22 10:41:58	ga_s2bm_ard_3-2-1_53KRA_2019-03-22_final.stac-item
2019-03-22 10:42:00	ga_s2bm_ard_3-2-1_53KQA_2019-03-22_final.stac-item
2019-03-24 09:41:45	ga_s2bm_ard_3-2-1_56KKF_2019-03-24_final.stac-item
2019-03-24 11:22:01	ga_s2bm_ard_3-2-1_52KDG_2019-03-24_final.stac-item
2019-03-24 11:22:05	ga_s2bm_ard_3-2-1_52KCG_2019-03-24_final.stac-item
2019-03-24 11:22:08	ga_s2bm_ard_3-2-1_52KBG_2019-03-24_final.stac-item
2019-03-24 11:22:09	ga_s2bm_ard_3-2-1_51KZB_2019-03-24_final.stac-item
2019-03-24 11:22:12	ga_s2bm_ard_3-2-1_51KYB_2019-03-24_final.stac-item
2019-03-24 11:22:23	ga_s2bm_ard_3-2-1_52KBF_2019-03-24_final.stac-item
2019-03-24 11:22:24	ga_s2bm_ard_3-2-1_51KZA_2019-03-24_final.stac-item
2019-03-24 11:22:27	ga_s2bm_ard_3-2-1_51KYA_2019-03-24_final.stac-item
2019-03-27 11:32:12	ga_s2bm_ard_3-2-1_51KXB_2019-03-27_final.stac-item
2019-03-27 11:32:16	ga_s2bm_ard_3-2-1_51KWB_2019-03-27_final.stac-item
2019-03-27 11:32:21	ga_s2bm_ard_3-2-1_51KVB_2019-03-27_final.stac-item
2019-03-27 11:32:23	ga_s2bm_ard_3-2-1_51KYA_2019-03-27_final.stac-item
2019-03-30 11:42:11	ga_s2bm_ard_3-2-1_51KWB_2019-03-30_final.stac-item
2019-03-30 11:42:15	ga_s2bm_ard_3-2-1_51KVB_2019-03-30_final.stac-item
2019-04-03 11:22:03	ga_s2bm_ard_3-2-1_52KDG_2019-04-03_final.stac-item
2019-04-03 11:22:07	ga_s2bm_ard_3-2-1_52KCG_2019-04-03_final.stac-item
2019-04-03 11:22:11	ga_s2bm_ard_3-2-1_52KBG_2019-04-03_final.stac-item
2019-04-03 11:22:12	ga_s2bm_ard_3-2-1_51KZB_2019-04-03_final.stac-item
2019-04-03 11:22:15	ga_s2bm_ard_3-2-1_51KYB_2019-04-03_final.stac-item
2019-04-03 11:22:25	ga_s2bm_ard_3-2-1_52KBF_2019-04-03_final.stac-item
2019-04-03 11:22:26	ga_s2bm_ard_3-2-1_51KZA_2019-04-03_final.stac-item
2019-04-03 11:22:29	ga_s2bm_ard_3-2-1_51KYA_2019-04-03_final.stac-item
2019-04-06 09:51:33	ga_s2bm_ard_3-2-1_55KGB_2019-04-06_final.stac-item
2019-04-06 09:51:37	ga_s2bm_ard_3-2-1_55KFB_2019-04-06_final.stac-item
2019-04-06 09:51:43	ga_s2bm_ard_3-2-1_56KKF_2019-04-06_final.stac-item
2019-05-31 10:41:51	ga_s2bm_ard_3-2-1_54KTG_2019-05-31_final.stac-item
2019-05-31 10:41:54	ga_s2bm_ard_3-2-1_53KRB_2019-05-31_final
2019-05-31 10:41:57	ga_s2bm_ard_3-2-1_53KQB_2019-05-31_final
2019-05-31 10:42:01	ga_s2bm_ard_3-2-1_53KPB_2019-05-31_final.stac-item
2019-05-31 10:42:02	ga_s2bm_ard_3-2-1_54KTF_2019-05-31_final.stac-item
2019-05-31 10:42:04	ga_s2bm_ard_3-2-1_53KNB_2019-05-31_final.stac-item
2019-05-31 10:42:06	ga_s2bm_ard_3-2-1_53KRA_2019-05-31_final.stac-item
2019-05-31 10:42:08	ga_s2bm_ard_3-2-1_53KQA_2019-05-31_final.stac-item
2019-05-31 10:42:11	ga_s2bm_ard_3-2-1_53KNB_2019-05-31_final.stac-item
2019-06-08 11:42:17	ga_s2bm_ard_3-2-1_51KWB_2019-06-08_final.stac-item
2019-06-08 11:42:21	ga_s2bm_ard_3-2-1_51KVB_2019-06-08_final.stac-item
2019-06-12 11:22:08	ga_s2bm_ard_3-2-1_52KDG_2019-06-12_final.stac-item
2019-06-12 11:22:12	ga_s2bm_ard_3-2-1_52KCG_2019-06-12_final.stac-item
2019-06-12 11:22:15	ga_s2bm_ard_3-2-1_52KBG_2019-06-12_final.stac-item
2019-06-12 11:22:16	ga_s2bm_ard_3-2-1_51KZB_2019-06-12_final.stac-item
2019-06-12 11:22:19	ga_s2bm_ard_3-2-1_51KYB_2019-06-12_final.stac-item
2019-06-12 11:22:30	ga_s2bm_ard_3-2-1_52KBF_2019-06-12_final.stac-item
2019-06-12 11:22:31	ga_s2bm_ard_3-2-1_51KZA_2019-06-12_final.stac-item
2019-06-12 11:22:34	ga_s2bm_ard_3-2-1_51KYA_2019-06-12_final.stac-item
2019-06-18 11:42:24	ga_s2bm_ard_3-2-1_51KWB_2019-06-18_final.stac-item
2019-06-18 11:42:26	ga_s2bm_ard_3-2-1_51KVB_2019-06-18_final.stac-item
2019-06-19 11:12:07	ga_s2bm_ard_3-2-1_52KFG_2019-06-19_final.stac-item
2019-06-19 11:12:11	ga_s2bm_ard_3-2-1_52KEG_2019-06-19_final.stac-item
2019-06-19 11:12:14	ga_s2bm_ard_3-2-1_52KDG_2019-06-19_final.stac-item
2019-06-19 11:12:18	ga_s2bm_ard_3-2-1_52KCG_2019-06-19_final.stac-item
2019-06-22 11:22:08	ga_s2bm_ard_3-2-1_52KDG_2019-06-22_final.stac-item
2019-06-22 11:22:13	ga_s2bm_ard_3-2-1_52KCG_2019-06-22_final.stac-item
2019-06-22 11:22:16	ga_s2bm_ard_3-2-1_52KBG_2019-06-22_final.stac-item
2019-06-22 11:22:17	ga_s2bm_ard_3-2-1_51KZB_2019-06-22_final.stac-item
2019-06-22 11:22:20	ga_s2bm_ard_3-2-1_51KYB_2019-06-22_final.stac-item
2019-06-22 11:22:30	ga_s2bm_ard_3-2-1_52KBF_2019-06-22_final.stac-item
2019-06-22 11:22:31	ga_s2bm_ard_3-2-1_51KZA_2019-06-22_final.stac-item
2019-06-22 11:22:35	ga_s2bm_ard_3-2-1_51KYA_2019-06-22_final.stac-item
2019-06-25 11:32:16	ga_s2bm_ard_3-2-1_51KYB_2019-06-25_final.stac-item
2019-06-25 11:32:19	ga_s2bm_ard_3-2-1_51KXB_2019-06-25_final.stac-item
2019-06-25 11:32:23	ga_s2bm_ard_3-2-1_51KWB_2019-06-25_final.stac-item
2019-06-25 11:32:28	ga_s2bm_ard_3-2-1_51KVB_2019-06-25_final.stac-item
2019-06-25 11:32:30	ga_s2bm_ard_3-2-1_51KYA_2019-06-25_final.stac-item
2019-06-28 11:42:18	ga_s2bm_ard_3-2-1_51KWB_2019-06-28_final.stac-item
2019-06-28 11:42:22	ga_s2bm_ard_3-2-1_51KVB_2019-06-28_final.stac-item
2019-07-31 10:11:42	ga_s2bm_ard_3-2-1_55KCB_2019-07-31_final.stac-item
2019-07-31 10:11:45	ga_s2bm_ard_3-2-1_55KBB_2019-07-31_final.stac-item
2019-07-31 10:11:46	ga_s2bm_ard_3-2-1_54KZG_2019-07-31_final.stac-item
2019-07-31 10:11:50	ga_s2bm_ard_3-2-1_54KYG_2019-07-31_final.stac-item
2019-07-31 10:11:56	ga_s2bm_ard_3-2-1_55KBA_2019-07-31_final.stac-item
2019-07-31 10:11:56	ga_s2bm_ard_3-2-1_54KZF_2019-07-31_final.stac-item
2019-07-31 10:11:58	ga_s2bm_ard_3-2-1_54KYF_2019-07-31_final.stac-item
2019-08-19 10:41:49	ga_s2bm_ard_3-2-1_54KTG_2019-08-19_final.stac-item
2019-08-19 10:41:51	ga_s2bm_ard_3-2-1_53KRB_2019-08-19_final
2019-08-19 10:41:55	ga_s2bm_ard_3-2-1_53KQB_2019-08-19_final
2019-08-19 10:41:58	ga_s2bm_ard_3-2-1_53KPB_2019-08-19_final.stac-item
2019-08-19 10:42:00	ga_s2bm_ard_3-2-1_54KTF_2019-08-19_final.stac-item
2019-08-19 10:42:01	ga_s2bm_ard_3-2-1_53KNB_2019-08-19_final.stac-item
2019-08-19 10:42:04	ga_s2bm_ard_3-2-1_53KRA_2019-08-19_final.stac-item
2019-08-19 10:42:06	ga_s2bm_ard_3-2-1_53KQA_2019-08-19_final.stac-item
2019-08-19 10:42:08	ga_s2bm_ard_3-2-1_53KNB_2019-08-19_final.stac-item
2019-08-20 10:11:39	ga_s2bm_ard_3-2-1_55KCB_2019-08-20_final.stac-item
2019-08-20 10:11:43	ga_s2bm_ard_3-2-1_55KBB_2019-08-20_final.stac-item
2019-08-20 10:11:44	ga_s2bm_ard_3-2-1_54KZG_2019-08-20_final.stac-item
2019-08-20 10:11:47	ga_s2bm_ard_3-2-1_54KYG_2019-08-20_final.stac-item
2019-08-20 10:11:54	ga_s2bm_ard_3-2-1_55KBA_2019-08-20_final.stac-item
2019-08-20 10:11:54	ga_s2bm_ard_3-2-1_54KZF_2019-08-20_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