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

79 results

Time (local)	Label
2017-12-24 10:26:56	ga_s2bm_ard_3-2-1_53JPM_2017-12-24_final.stac-item
2018-04-07 11:46:20	ga_s2bm_ard_3-2-1_50KPC_2018-04-07_final.stac-item
2018-04-13 10:27:05	ga_s2bm_ard_3-2-1_54JTR_2018-04-13_final.stac-item
2018-04-14 09:57:05	ga_s2bm_ard_3-2-1_54HVD_2018-04-14_final.stac-item
2018-05-21 11:31:10	ga_s2bm_ard_3-2-1_51KWQ_2018-05-21_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_51KVS_2018-07-10_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_51KUT_2018-07-13_final.stac-item
2018-12-07 11:33:25	ga_s2bm_ard_3-2-1_51KVS_2018-12-07_final.stac-item
2018-12-24 11:23:02	ga_s2bm_ard_3-2-1_51KZT_2018-12-24_final.stac-item
2019-01-03 11:23:23	ga_s2bm_ard_3-2-1_51KYS_2019-01-03_final.stac-item
2019-01-09 11:42:59	ga_s2bm_ard_3-2-1_51KUU_2019-01-09_final.stac-item
2019-01-29 11:43:12	ga_s2bm_ard_3-2-1_51KVT_2019-01-29_final.stac-item
2019-03-17 11:33:40	ga_s2bm_ard_3-2-1_51KWR_2019-03-17_final.stac-item
2019-03-24 11:23:10	ga_s2bm_ard_3-2-1_51KYT_2019-03-24_final.stac-item
2019-05-23 11:23:19	ga_s2bm_ard_3-2-1_51KYT_2019-05-23_final.stac-item
2019-11-25 11:43:11	ga_s2bm_ard_3-2-1_51KUT_2019-11-25_final.stac-item
2020-02-10 11:33:22	ga_s2bm_ard_3-2-1_51KWS_2020-02-10_final.stac-item
2020-06-12 11:43:31	ga_s2bm_ard_3-2-1_51KUS_2020-06-12_final.stac-item
2020-07-04 10:44:08	ga_s2bm_ard_3-2-1_53JNN_2020-07-04_final.stac-item
2020-07-13 11:13:15	ga_s2bm_ard_3-2-1_52KBC_2020-07-13_final.stac-item
2020-07-20 11:03:00	ga_s2bm_ard_3-2-1_52KGC_2020-07-20_final.stac-item
2020-07-29 11:33:59	ga_s2bm_ard_3-2-1_51KWQ_2020-07-29_final.stac-item
2020-08-12 11:16:44	ga_s2bm_ard_3-2-1_51HXD_2020-08-12_final.stac-item
2020-08-20 10:34:22	ga_s2bm_ard_3-2-1_53JQM_2020-08-20_final.stac-item
2020-11-10 11:13:56	ga_s2bm_ard_3-2-1_52KBV_2020-11-10_final.stac-item
2020-11-13 11:23:26	ga_s2bm_ard_3-2-1_51KYS_2020-11-13_final.stac-item
2020-11-16 11:33:13	ga_s2bm_ard_3-2-1_51KWT_2020-11-16_final.stac-item
2020-11-18 10:33:46	ga_s2bm_ard_3-2-1_54KTU_2020-11-18_final.stac-item
2021-01-13 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2021-01-13_final.stac-item
2021-04-27 10:33:59	ga_s2bm_ard_3-2-1_53JQN_2021-04-27_final.stac-item
2021-04-27 10:34:24	ga_s2bm_ard_3-2-1_54JTR_2021-04-27_final.stac-item
2021-05-15 11:33:41	ga_s2bm_ard_3-2-1_51KWR_2021-05-15_final.stac-item
2021-05-30 10:44:21	ga_s2bm_ard_3-2-1_53JNM_2021-05-30_final.stac-item
2021-06-01 09:46:17	ga_s2bm_ard_3-2-1_55HEC_2021-06-01_final.stac-item
2021-06-08 09:35:28	ga_s2bm_ard_3-2-1_56JKL_2021-06-08_final.stac-item
2021-07-14 11:33:44	ga_s2bm_ard_3-2-1_51KWR_2021-07-14_final.stac-item
2021-07-20 10:15:31	ga_s2bm_ard_3-2-1_54JVM_2021-07-20_final.stac-item
2021-07-21 11:23:30	ga_s2bm_ard_3-2-1_51KXS_2021-07-21_final.stac-item
2021-08-30 09:46:46	ga_s2bm_ard_3-2-1_55HDA_2021-08-30_final.stac-item
2021-10-07 10:44:17	ga_s2bm_ard_3-2-1_53JPM_2021-10-07_final.stac-item
2022-01-10 11:33:23	ga_s2bm_ard_3-2-1_51KWS_2022-01-10_final.stac-item
2022-01-17 09:43:08	ga_s2bm_ard_3-2-1_55KHQ_2022-01-17_final.stac-item
2022-02-17 10:50:28	ga_s2bm_ard_3-2-1_53LPG_2022-02-17_final.stac-item
2022-02-22 11:43:09	ga_s2bm_ard_3-2-1_51KUT_2022-02-22_final.stac-item
2022-04-02 10:33:46	ga_s2bm_ard_3-2-1_53KQP_2022-04-02_final.stac-item
2022-05-27 11:24:02	ga_s2bm_ard_3-2-1_51KWQ_2022-05-27_final.stac-item
2022-06-24 10:43:53	ga_s2bm_ard_3-2-1_53KPP_2022-06-24_final.stac-item
2022-08-11 11:42:31	ga_s2bm_ard_3-2-1_51KVA_2022-08-11_final.stac-item
2022-08-18 11:33:15	ga_s2bm_ard_3-2-1_51KWT_2022-08-18_final.stac-item
2022-09-07 11:32:56	ga_s2bm_ard_3-2-1_51KXU_2022-09-07_final.stac-item
2022-11-19 10:01:32	ga_s2bm_ard_3-2-1_55KEB_2022-11-19_final.stac-item
2022-12-06 09:52:10	ga_s2bm_ard_3-2-1_55KGU_2022-12-06_final.stac-item
2022-12-06 11:33:31	ga_s2bm_ard_3-2-1_51KUS_2022-12-06_final.stac-item
2022-12-08 10:34:10	ga_s2bm_ard_3-2-1_53JNN_2022-12-08_final.stac-item
2022-12-18 10:35:07	ga_s2bm_ard_3-2-1_54JTN_2022-12-18_final.stac-item
2023-02-04 11:33:42	ga_s2bm_ard_3-2-1_51KVR_2023-02-04_final.stac-item
2023-04-01 11:56:14	ga_s2bm_ard_3-2-1_50JLM_2023-04-01_final
2023-04-24 10:20:30	ga_s2bm_ard_3-2-1_54LXM_2023-04-24_final
2023-05-22 11:23:15	ga_s2bm_ard_3-2-1_51KYT_2023-05-22_final
2023-07-13 10:24:44	ga_s2bm_ard_3-2-1_53JQL_2023-07-13_final
2023-09-19 11:23:17	ga_s2bm_ard_3-2-1_51KXT_2023-09-19_final
2023-09-26 09:33:02	ga_s2bm_ard_3-2-1_56KLA_2023-09-26_final
2023-11-01 11:33:33	ga_s2bm_ard_3-2-1_51KVS_2023-11-01_final
2023-11-10 10:24:41	ga_s2bm_ard_3-2-1_53JQL_2023-11-10_final
2023-11-18 11:23:23	ga_s2bm_ard_3-2-1_51KYS_2023-11-18_final
2023-12-12 11:06:21	ga_s2bm_ard_3-2-1_52HCK_2023-12-12_final
2023-12-23 10:34:04	ga_s2bm_ard_3-2-1_53JRN_2023-12-23_final
2024-01-20 11:32:57	ga_s2bm_ard_3-2-1_51KWU_2024-01-20_final
2024-01-22 10:33:48	ga_s2bm_ard_3-2-1_53KQP_2024-01-22_final
2024-02-09 11:33:45	ga_s2bm_ard_3-2-1_51KVR_2024-02-09_final
2024-03-02 10:31:46	ga_s2bm_ard_3-2-1_54KTG_2024-03-02_final
2024-03-09 10:20:26	ga_s2bm_ard_3-2-1_54LWM_2024-03-09_final
2024-03-25 10:41:46	ga_s2bm_ard_3-2-1_53KRB_2024-03-25_final
2024-04-12 11:40:58	ga_s2bm_ard_3-2-1_51LWG_2024-04-12_final
2024-04-18 10:21:01	ga_s2bm_ard_3-2-1_54LWK_2024-04-18_final
2024-04-19 11:33:28	ga_s2bm_ard_3-2-1_51KWS_2024-04-19_final
2024-04-29 11:33:30	ga_s2bm_ard_3-2-1_51KVS_2024-04-29_final
2024-05-12 10:01:29	ga_s2bm_ard_3-2-1_55KFB_2024-05-12_nrt
2024-05-13 11:13:54	ga_s2bm_ard_3-2-1_51KZQ_2024-05-13_nrt

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