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

68 results

Time (local)	Label
2017-07-10 10:43:08	ga_s2bm_ard_3-2-1_53JNM_2017-07-10_final.stac-item
2018-01-21 11:30:33	ga_s2bm_ard_3-2-1_51KVR_2018-01-21_final.stac-item
2018-06-20 09:56:14	ga_s2bm_ard_3-2-1_55HDU_2018-06-20_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_51KXU_2018-07-10_final.stac-item
2018-11-17 11:33:10	ga_s2bm_ard_3-2-1_51KWT_2018-11-17_final.stac-item
2018-11-22 10:42:21	ga_s2bm_ard_3-2-1_53KNV_2018-11-22_final.stac-item
2019-01-06 11:33:11	ga_s2bm_ard_3-2-1_51KWT_2019-01-06_final.stac-item
2019-01-08 10:30:39	ga_s2bm_ard_3-2-1_54LWL_2019-01-08_final.stac-item
2019-02-25 11:33:00	ga_s2bm_ard_3-2-1_51KVU_2019-02-25_final.stac-item
2019-03-04 11:23:31	ga_s2bm_ard_3-2-1_51KYR_2019-03-04_final.stac-item
2019-05-15 10:21:09	ga_s2bm_ard_3-2-1_54LWK_2019-05-15_final.stac-item
2019-05-28 10:34:12	ga_s2bm_ard_3-2-1_53JQN_2019-05-28_final.stac-item
2019-06-08 11:41:40	ga_s2bm_ard_3-2-1_51LUE_2019-06-08_final.stac-item
2019-06-18 10:06:42	ga_s2bm_ard_3-2-1_54HYG_2019-06-18_final.stac-item
2019-08-04 11:33:30	ga_s2bm_ard_3-2-1_51KUT_2019-08-04_final.stac-item
2019-09-23 09:57:36	ga_s2bm_ard_3-2-1_54HYC_2019-09-23_final.stac-item
2019-11-05 11:43:25	ga_s2bm_ard_3-2-1_51KVS_2019-11-05_final.stac-item
2019-11-28 10:15:28	ga_s2bm_ard_3-2-1_54JUM_2019-11-28_final.stac-item
2020-02-05 10:44:10	ga_s2bm_ard_3-2-1_53JPM_2020-02-05_final.stac-item
2020-02-13 11:41:22	ga_s2bm_ard_3-2-1_51LUE_2020-02-13_final.stac-item
2020-04-02 10:34:33	ga_s2bm_ard_3-2-1_53JPL_2020-04-02_final.stac-item
2020-06-26 09:47:43	ga_s2bm_ard_3-2-1_55HBT_2020-06-26_final.stac-item
2020-06-28 10:25:38	ga_s2bm_ard_3-2-1_54JVL_2020-06-28_final.stac-item
2020-11-23 11:23:01	ga_s2bm_ard_3-2-1_51KXU_2020-11-23_final.stac-item
2020-12-16 11:33:30	ga_s2bm_ard_3-2-1_51KUS_2020-12-16_final.stac-item
2020-12-18 10:34:57	ga_s2bm_ard_3-2-1_53JQJ_2020-12-18_final.stac-item
2020-12-28 10:30:53	ga_s2bm_ard_3-2-1_54LWK_2020-12-28_final.stac-item
2020-12-29 11:43:09	ga_s2bm_ard_3-2-1_51KVT_2020-12-29_final.stac-item
2021-01-20 10:44:16	ga_s2bm_ard_3-2-1_53JPM_2021-01-20_final.stac-item
2021-02-15 09:25:05	ga_s2bm_ard_3-2-1_56JNM_2021-02-14_final.stac-item
2021-03-30 11:11:03	ga_s2bm_ard_3-2-1_52LEL_2021-03-30_final
2021-05-15 09:57:50	ga_s2bm_ard_3-2-1_54HYB_2021-05-15_final.stac-item
2021-07-21 11:23:15	ga_s2bm_ard_3-2-1_51KXT_2021-07-21_final.stac-item
2021-08-05 10:34:19	ga_s2bm_ard_3-2-1_53JQM_2021-08-05_final.stac-item
2021-11-26 10:44:02	ga_s2bm_ard_3-2-1_53JNN_2021-11-26_final.stac-item
2022-01-07 09:44:21	ga_s2bm_ard_3-2-1_56JKQ_2022-01-07_final.stac-item
2022-01-12 10:30:37	ga_s2bm_ard_3-2-1_54LWL_2022-01-12_final.stac-item
2022-01-30 11:33:10	ga_s2bm_ard_3-2-1_51KVT_2022-01-30_final.stac-item
2022-02-19 11:32:48	ga_s2bm_ard_3-2-1_51KXU_2022-02-19_final.stac-item
2022-03-18 11:21:30	ga_s2bm_ard_3-2-1_52LDJ_2022-03-18_final.stac-item
2022-04-27 09:44:39	ga_s2bm_ard_3-2-1_55JFJ_2022-04-27_final.stac-item
2022-05-13 10:07:24	ga_s2bm_ard_3-2-1_54HWD_2022-05-13_final.stac-item
2022-05-15 10:43:47	ga_s2bm_ard_3-2-1_53KPP_2022-05-15_final.stac-item
2022-05-23 11:43:25	ga_s2bm_ard_3-2-1_51KVS_2022-05-23_final.stac-item
2022-05-27 11:23:21	ga_s2bm_ard_3-2-1_52KBB_2022-05-27_final.stac-item
2022-06-02 11:41:32	ga_s2bm_ard_3-2-1_51LUE_2022-06-02_final.stac-item
2022-06-19 09:52:21	ga_s2bm_ard_3-2-1_55KFU_2022-06-19_final.stac-item
2022-06-23 11:13:59	ga_s2bm_ard_3-2-1_52KBV_2022-06-23_final.stac-item
2022-09-19 10:33:54	ga_s2bm_ard_3-2-1_53KPP_2022-09-19_final.stac-item
2022-11-20 11:13:15	ga_s2bm_ard_3-2-1_52KEB_2022-11-20_final.stac-item
2022-11-24 10:54:15	ga_s2bm_ard_3-2-1_52JGT_2022-11-24_final.stac-item
2023-01-26 11:01:30	ga_s2bm_ard_3-2-1_52LGJ_2023-01-26_final.stac-item
2023-04-15 09:55:51	ga_s2bm_ard_3-2-1_55HCE_2023-04-15_final
2023-05-15 09:54:01	ga_s2bm_ard_3-2-1_55JCN_2023-05-15_final
2023-05-24 10:24:44	ga_s2bm_ard_3-2-1_53JQL_2023-05-24_final
2023-05-30 10:46:13	ga_s2bm_ard_3-2-1_53HLE_2023-05-30_final
2023-06-06 10:34:23	ga_s2bm_ard_3-2-1_53JQM_2023-06-06_final
2023-06-06 10:34:41	ga_s2bm_ard_3-2-1_53JPL_2023-06-06_final
2023-06-26 12:15:01	ga_s2bm_ard_3-2-1_49JGM_2023-06-26_final
2023-07-21 11:23:19	ga_s2bm_ard_3-2-1_51KXT_2023-07-21_final
2023-08-02 10:24:45	ga_s2bm_ard_3-2-1_53JQL_2023-08-02_final
2023-09-04 10:34:04	ga_s2bm_ard_3-2-1_54JTT_2023-09-04_final
2023-09-22 11:32:32	ga_s2bm_ard_3-2-1_51KWA_2023-09-22_final
2024-03-01 11:02:09	ga_s2bm_ard_3-2-1_52KHF_2024-03-01_final
2024-03-22 10:32:37	ga_s2bm_ard_3-2-1_53KQU_2024-03-22_final
2024-04-11 10:34:25	ga_s2bm_ard_3-2-1_53JNM_2024-04-11_final
2024-04-23 11:16:44	ga_s2bm_ard_3-2-1_51HWD_2024-04-23_final
2024-04-29 09:58:04	ga_s2bm_ard_3-2-1_55GBR_2024-04-29_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