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
2017-09-14 10:57:06	ga_s2bm_ard_3-2-1_52KGG_2017-09-14_final.stac-item
2017-09-14 11:02:49	ga_s2bm_ard_3-2-1_52KFB_2017-09-14_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFL_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFM_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFN_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFP_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFQ_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFR_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFS_2017-10-21_final.stac-item
2017-10-21 10:53:01	ga_s2bm_ard_3-2-1_52JFT_2017-10-21_final.stac-item
2018-05-29 10:47:21	ga_s2bm_ard_3-2-1_52JFQ_2018-05-29_final.stac-item
2018-05-29 10:47:21	ga_s2bm_ard_3-2-1_52JFR_2018-05-29_final.stac-item
2018-05-29 10:47:21	ga_s2bm_ard_3-2-1_52JFS_2018-05-29_final.stac-item
2018-05-29 10:47:21	ga_s2bm_ard_3-2-1_52JFT_2018-05-29_final.stac-item
2018-05-29 10:54:52	ga_s2bm_ard_3-2-1_52JFP_2018-05-29_final.stac-item
2018-05-29 10:54:52	ga_s2bm_ard_3-2-1_52JFQ_2018-05-29_final.stac-item
2019-10-14 11:04:59	ga_s2bm_ard_3-2-1_52JFQ_2019-10-14_final.stac-item
2019-10-24 11:01:33	ga_s2bm_ard_3-2-1_52LGJ_2019-10-24_final.stac-item
2019-10-24 11:01:40	ga_s2bm_ard_3-2-1_52LFJ_2019-10-24_final.stac-item
2019-10-24 11:01:47	ga_s2bm_ard_3-2-1_52LGH_2019-10-24_final.stac-item
2019-10-24 11:01:51	ga_s2bm_ard_3-2-1_52LFH_2019-10-24_final.stac-item
2019-10-24 11:02:02	ga_s2bm_ard_3-2-1_52KGG_2019-10-24_final.stac-item
2019-10-24 11:02:05	ga_s2bm_ard_3-2-1_52KFG_2019-10-24_final.stac-item
2019-10-24 11:02:16	ga_s2bm_ard_3-2-1_52KGF_2019-10-24_final.stac-item
2019-10-24 11:02:19	ga_s2bm_ard_3-2-1_52KFF_2019-10-24_final.stac-item
2019-10-24 11:02:31	ga_s2bm_ard_3-2-1_52KGE_2019-10-24_final.stac-item
2019-10-24 11:02:34	ga_s2bm_ard_3-2-1_52KFE_2019-10-24_final.stac-item
2019-10-24 11:02:45	ga_s2bm_ard_3-2-1_52KGD_2019-10-24_final.stac-item
2019-10-24 11:02:48	ga_s2bm_ard_3-2-1_52KFD_2019-10-24_final.stac-item
2019-10-24 11:02:59	ga_s2bm_ard_3-2-1_52KGC_2019-10-24_final.stac-item
2019-10-24 11:03:03	ga_s2bm_ard_3-2-1_52KFC_2019-10-24_final.stac-item
2019-10-24 11:03:14	ga_s2bm_ard_3-2-1_52KGB_2019-10-24_final.stac-item
2019-10-24 11:03:18	ga_s2bm_ard_3-2-1_52KFB_2019-10-24_final.stac-item
2019-10-24 11:03:28	ga_s2bm_ard_3-2-1_52KGA_2019-10-24_final.stac-item
2019-10-24 11:03:32	ga_s2bm_ard_3-2-1_52KFA_2019-10-24_final.stac-item
2019-10-24 11:03:47	ga_s2bm_ard_3-2-1_52KFV_2019-10-24_final.stac-item
2019-10-24 11:04:01	ga_s2bm_ard_3-2-1_52KFU_2019-10-24_final.stac-item
2019-10-24 11:04:16	ga_s2bm_ard_3-2-1_52JFT_2019-10-24_final.stac-item
2019-10-24 11:04:30	ga_s2bm_ard_3-2-1_52JFS_2019-10-24_final.stac-item
2019-10-24 11:04:44	ga_s2bm_ard_3-2-1_52JFR_2019-10-24_final.stac-item
2019-10-24 11:04:59	ga_s2bm_ard_3-2-1_52JFQ_2019-10-24_final.stac-item
2019-12-03 11:04:37	ga_s2bm_ard_3-2-1_52JFR_2019-12-03_final.stac-item
2019-12-03 11:04:52	ga_s2bm_ard_3-2-1_52JFQ_2019-12-03_final.stac-item
2019-12-06 11:10:23	ga_s2bm_ard_3-2-1_52LGN_2019-12-06_final.stac-item
2019-12-06 11:10:37	ga_s2bm_ard_3-2-1_52LGM_2019-12-06_final.stac-item
2019-12-06 11:10:52	ga_s2bm_ard_3-2-1_52LGL_2019-12-06_final.stac-item
2019-12-06 11:10:55	ga_s2bm_ard_3-2-1_52LFL_2019-12-06_final.stac-item
2019-12-06 11:11:01	ga_s2bm_ard_3-2-1_52LGK_2019-12-06_final.stac-item
2019-12-06 11:11:02	ga_s2bm_ard_3-2-1_52LFL_2019-12-06_final.stac-item
2019-12-06 11:11:02	ga_s2bm_ard_3-2-1_52LFK_2019-12-06_final.stac-item
2019-12-06 11:11:07	ga_s2bm_ard_3-2-1_52LGK_2019-12-06_final.stac-item
2019-12-06 11:11:10	ga_s2bm_ard_3-2-1_52LFK_2019-12-06_final.stac-item
2019-12-06 11:11:21	ga_s2bm_ard_3-2-1_52LGJ_2019-12-06_final.stac-item
2019-12-06 11:11:24	ga_s2bm_ard_3-2-1_52LFJ_2019-12-06_final.stac-item
2019-12-06 11:11:34	ga_s2bm_ard_3-2-1_52LGH_2019-12-06_final.stac-item
2019-12-06 11:11:39	ga_s2bm_ard_3-2-1_52LFH_2019-12-06_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
2019-12-10 10:54:16	ga_s2bm_ard_3-2-1_52JFT_2019-12-10_final.stac-item
2019-12-10 10:54:28	ga_s2bm_ard_3-2-1_52JFS_2019-12-10_final.stac-item
2019-12-10 10:54:42	ga_s2bm_ard_3-2-1_52JFR_2019-12-10_final.stac-item
2019-12-10 10:54:56	ga_s2bm_ard_3-2-1_52JFQ_2019-12-10_final.stac-item
2019-12-10 10:55:11	ga_s2bm_ard_3-2-1_52JFP_2019-12-10_final.stac-item
2019-12-10 10:55:21	ga_s2bm_ard_3-2-1_52JFN_2019-12-10_final.stac-item
2019-12-10 10:55:28	ga_s2bm_ard_3-2-1_52JFN_2019-12-10_final.stac-item
2019-12-10 10:55:40	ga_s2bm_ard_3-2-1_52JFM_2019-12-10_final.stac-item
2019-12-10 10:55:54	ga_s2bm_ard_3-2-1_52JFL_2019-12-10_final.stac-item
2019-12-20 10:54:16	ga_s2bm_ard_3-2-1_52JFT_2019-12-20_final.stac-item
2019-12-20 10:54:28	ga_s2bm_ard_3-2-1_52JFS_2019-12-20_final.stac-item
2019-12-20 10:54:42	ga_s2bm_ard_3-2-1_52JFR_2019-12-20_final.stac-item
2019-12-20 10:54:57	ga_s2bm_ard_3-2-1_52JFQ_2019-12-20_final.stac-item
2019-12-20 10:55:12	ga_s2bm_ard_3-2-1_52JFP_2019-12-20_final.stac-item
2019-12-20 10:55:26	ga_s2bm_ard_3-2-1_52JFN_2019-12-20_final.stac-item
2019-12-20 10:55:35	ga_s2bm_ard_3-2-1_52JFM_2019-12-20_final.stac-item
2019-12-20 10:55:42	ga_s2bm_ard_3-2-1_52JFM_2019-12-20_final.stac-item
2019-12-20 10:55:55	ga_s2bm_ard_3-2-1_52JFL_2019-12-20_final.stac-item
2020-05-11 11:02:43	ga_s2bm_ard_3-2-1_52KGD_2020-05-11_final.stac-item
2020-05-11 11:02:46	ga_s2bm_ard_3-2-1_52KFD_2020-05-11_final.stac-item
2020-05-11 11:02:57	ga_s2bm_ard_3-2-1_52KGC_2020-05-11_final.stac-item
2020-05-11 11:03:00	ga_s2bm_ard_3-2-1_52KFC_2020-05-11_final.stac-item
2020-05-11 11:03:11	ga_s2bm_ard_3-2-1_52KGB_2020-05-11_final.stac-item
2020-05-11 11:03:15	ga_s2bm_ard_3-2-1_52KFB_2020-05-11_final.stac-item
2020-05-11 11:03:26	ga_s2bm_ard_3-2-1_52KGA_2020-05-11_final.stac-item
2020-05-11 11:03:29	ga_s2bm_ard_3-2-1_52KFA_2020-05-11_final.stac-item
2020-05-11 11:03:44	ga_s2bm_ard_3-2-1_52KFV_2020-05-11_final.stac-item
2020-05-11 11:03:58	ga_s2bm_ard_3-2-1_52KFU_2020-05-11_final.stac-item
2020-05-11 11:04:13	ga_s2bm_ard_3-2-1_52JFT_2020-05-11_final.stac-item
2020-05-11 11:04:27	ga_s2bm_ard_3-2-1_52JFS_2020-05-11_final.stac-item
2020-05-11 11:04:42	ga_s2bm_ard_3-2-1_52JFR_2020-05-11_final.stac-item
2020-05-11 11:04:56	ga_s2bm_ard_3-2-1_52JFQ_2020-05-11_final.stac-item
2020-05-14 11:10:42	ga_s2bm_ard_3-2-1_52LGM_2020-05-14_final.stac-item
2020-05-14 11:10:57	ga_s2bm_ard_3-2-1_52LGL_2020-05-14_final.stac-item
2020-05-14 11:11:00	ga_s2bm_ard_3-2-1_52LFL_2020-05-14_final.stac-item
2020-05-14 11:11:11	ga_s2bm_ard_3-2-1_52LGK_2020-05-14_final.stac-item
2020-05-14 11:11:15	ga_s2bm_ard_3-2-1_52LFK_2020-05-14_final.stac-item
2020-05-14 11:11:26	ga_s2bm_ard_3-2-1_52LGJ_2020-05-14_final.stac-item
2020-05-14 11:11:29	ga_s2bm_ard_3-2-1_52LFJ_2020-05-14_final.stac-item
2020-05-14 11:11:39	ga_s2bm_ard_3-2-1_52LGH_2020-05-14_final.stac-item
2020-05-14 11:11:44	ga_s2bm_ard_3-2-1_52LFH_2020-05-14_final.stac-item
2020-05-14 11:11:49	ga_s2bm_ard_3-2-1_52KGG_2020-05-14_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