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

52 results

Time (local)	Label
2017-07-02 09:44:54	ga_s2bm_ard_3-2-1_55JFF_2017-07-02_final.stac-item
2017-07-13 10:53:15	ga_s2bm_ard_3-2-1_52JHT_2017-07-13_final.stac-item
2017-07-14 10:17:06	ga_s2bm_ard_3-2-1_54KVD_2017-07-14_final.stac-item
2018-03-12 09:50:45	ga_s2bm_ard_3-2-1_55HBV_2018-03-12_final.stac-item
2018-04-04 11:45:38	ga_s2bm_ard_3-2-1_50JPL_2018-04-04_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_52KED_2018-06-24_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_51JTN_2018-09-01_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JQK_2018-10-20_final.stac-item
2018-11-23 11:53:50	ga_s2bm_ard_3-2-1_50KNA_2018-11-23_final.stac-item
2019-01-12 11:53:38	ga_s2bm_ard_3-2-1_50KNB_2019-01-12_final.stac-item
2019-05-04 10:52:46	ga_s2bm_ard_3-2-1_53KMU_2019-05-04_final.stac-item
2019-05-08 10:33:10	ga_s2bm_ard_3-2-1_54KTB_2019-05-08_final.stac-item
2019-06-04 10:24:09	ga_s2bm_ard_3-2-1_54JUT_2019-06-04_final.stac-item
2019-08-02 10:54:37	ga_s2bm_ard_3-2-1_52JGS_2019-08-02_final.stac-item
2019-09-12 10:26:33	ga_s2bm_ard_3-2-1_53HQC_2019-09-12_final.stac-item
2019-09-25 10:33:02	ga_s2bm_ard_3-2-1_53KRS_2019-09-25_final.stac-item
2019-10-03 11:31:39	ga_s2bm_ard_3-2-1_51LYD_2019-10-03_final.stac-item
2019-10-19 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-19_final.stac-item
2019-10-20 09:43:42	ga_s2bm_ard_3-2-1_55JHN_2019-10-20_final.stac-item
2019-10-20 09:43:46	ga_s2bm_ard_3-2-1_55JGN_2019-10-20_final.stac-item
2019-10-25 10:33:03	ga_s2bm_ard_3-2-1_53KRS_2019-10-25_final.stac-item
2019-11-18 10:12:23	ga_s2bm_ard_3-2-1_54KYD_2019-11-18_final.stac-item
2019-12-18 11:53:30	ga_s2bm_ard_3-2-1_50KPB_2019-12-18_final.stac-item
2020-01-27 11:57:02	ga_s2bm_ard_3-2-1_50HLH_2020-01-27_final.stac-item
2020-03-17 11:53:34	ga_s2bm_ard_3-2-1_50KPB_2020-03-17_final.stac-item
2020-05-11 11:01:25	ga_s2bm_ard_3-2-1_53LKD_2020-05-11_final.stac-item
2020-05-24 09:33:54	ga_s2bm_ard_3-2-1_56JMS_2020-05-24_final.stac-item
2020-06-18 10:26:18	ga_s2bm_ard_3-2-1_54HTJ_2020-06-18_final.stac-item
2020-07-08 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2020-07-08_final.stac-item
2020-09-23 10:11:41	ga_s2bm_ard_3-2-1_54KZG_2020-09-23_final.stac-item
2020-11-14 10:54:27	ga_s2bm_ard_3-2-1_53JKM_2020-11-14_final.stac-item
2021-01-12 09:44:56	ga_s2bm_ard_3-2-1_55JGH_2021-01-12_final.stac-item
2021-01-12 09:45:00	ga_s2bm_ard_3-2-1_55JFH_2021-01-12_final.stac-item
2021-01-20 10:45:26	ga_s2bm_ard_3-2-1_53JLH_2021-01-20_final.stac-item
2021-02-07 10:05:36	ga_s2bm_ard_3-2-1_54JYL_2021-02-07_final.stac-item
2021-03-05 10:26:00	ga_s2bm_ard_3-2-1_54HTK_2021-03-05_final.stac-item
2021-05-27 10:33:31	ga_s2bm_ard_3-2-1_54KTV_2021-05-27_final.stac-item
2021-07-08 11:11:21	ga_s2bm_ard_3-2-1_52LEK_2021-07-08_final
2021-09-06 09:34:52	ga_s2bm_ard_3-2-1_56JLN_2021-09-06_final.stac-item
2021-09-10 10:54:08	ga_s2bm_ard_3-2-1_52JHT_2021-09-10_final.stac-item
2021-09-10 10:54:22	ga_s2bm_ard_3-2-1_52JHS_2021-09-10_final.stac-item
2021-10-08 10:16:28	ga_s2bm_ard_3-2-1_54HVH_2021-10-08_final.stac-item
2021-12-11 11:35:42	ga_s2bm_ard_3-2-1_51JTH_2021-12-11_final.stac-item
2022-03-11 11:33:11	ga_s2bm_ard_3-2-1_51KWT_2022-03-11_final.stac-item
2022-03-14 11:43:13	ga_s2bm_ard_3-2-1_51KUT_2022-03-14_final.stac-item
2022-08-21 11:43:48	ga_s2bm_ard_3-2-1_51KTR_2022-08-21_final.stac-item
2022-09-20 11:43:34	ga_s2bm_ard_3-2-1_51KTS_2022-09-20_final.stac-item
2023-03-26 09:54:05	ga_s2bm_ard_3-2-1_55JEM_2023-03-26_final
2023-05-22 09:44:04	ga_s2bm_ard_3-2-1_55JGM_2023-05-22_final
2023-06-14 09:55:38	ga_s2bm_ard_3-2-1_55JDF_2023-06-14_final
2023-11-24 11:43:10	ga_s2bm_ard_3-2-1_51KUT_2023-11-24_final
2023-12-25 11:14:07	ga_s2bm_ard_3-2-1_52KCU_2023-12-25_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