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
2017-07-17 12:13:21	ga_s2bm_ard_3-2-1_50KKA_2017-07-17_final.stac-item
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50JLP_2017-11-08_final.stac-item
2017-11-15 11:40:36	ga_s2bm_ard_3-2-1_50JNQ_2017-11-15_final.stac-item
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50HPH_2018-01-24_final.stac-item
2018-02-04 11:11:54	ga_s2bm_ard_3-2-1_51JYL_2018-02-04_final.stac-item
2018-02-16 11:54:55	ga_s2bm_ard_3-2-1_50JKN_2018-02-16_final.stac-item
2018-04-14 11:40:40	ga_s2bm_ard_3-2-1_50KRD_2018-04-14_final.stac-item
2018-04-21 11:33:07	ga_s2bm_ard_3-2-1_51KVQ_2018-04-21_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JKN_2018-04-27_final.stac-item
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50KPC_2018-05-17_final.stac-item
2018-05-24 11:43:21	ga_s2bm_ard_3-2-1_51KUR_2018-05-24_final.stac-item
2018-07-06 11:51:46	ga_s2bm_ard_3-2-1_50HNK_2018-07-06_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_51KTT_2018-08-12_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JNP_2018-09-11_final.stac-item
2018-10-01 11:44:52	ga_s2bm_ard_3-2-1_50JQN_2018-10-01_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49KGP_2018-10-07_final.stac-item
2018-10-31 11:39:52	ga_s2bm_ard_3-2-1_50HPK_2018-10-31_final.stac-item
2018-10-31 11:46:25	ga_s2bm_ard_3-2-1_50HNJ_2018-10-31_final.stac-item
2018-12-03 11:53:20	ga_s2bm_ard_3-2-1_50KNC_2018-12-03_final.stac-item
2019-02-14 12:06:04	ga_s2bm_ard_3-2-1_50JLM_2019-02-14_final.stac-item
2019-02-15 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2019-02-15_final.stac-item
2019-03-03 11:56:28	ga_s2bm_ard_3-2-1_50HNK_2019-03-03_final.stac-item
2019-05-25 12:04:51	ga_s2bm_ard_3-2-1_50JKT_2019-05-25_final.stac-item
2019-07-14 12:05:53	ga_s2bm_ard_3-2-1_49JGJ_2019-07-14_final.stac-item
2019-09-06 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2019-09-06_final.stac-item
2019-09-09 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2019-09-09_final.stac-item
2019-10-03 11:36:34	ga_s2bm_ard_3-2-1_50HQK_2019-10-03_final.stac-item
2019-10-16 11:46:09	ga_s2bm_ard_3-2-1_50JNM_2019-10-16_final.stac-item
2019-10-16 11:46:20	ga_s2bm_ard_3-2-1_50JPL_2019-10-16_final.stac-item
2019-10-20 11:26:30	ga_s2bm_ard_3-2-1_51HVE_2019-10-20_final.stac-item
2019-11-09 11:26:58	ga_s2bm_ard_3-2-1_51HVC_2019-11-09_final.stac-item
2019-12-08 11:53:19	ga_s2bm_ard_3-2-1_50KNC_2019-12-08_final.stac-item
2019-12-08 11:56:16	ga_s2bm_ard_3-2-1_50JML_2019-12-08_final.stac-item
2019-12-31 12:03:33	ga_s2bm_ard_3-2-1_50KMB_2019-12-31_final.stac-item
2020-01-15 11:16:24	ga_s2bm_ard_3-2-1_51HYE_2020-01-15_final.stac-item
2020-01-31 11:36:39	ga_s2bm_ard_3-2-1_51HTD_2020-01-31_final.stac-item
2020-03-04 11:43:15	ga_s2bm_ard_3-2-1_51KTT_2020-03-04_final.stac-item
2020-05-17 11:26:40	ga_s2bm_ard_3-2-1_51HWD_2020-05-17_final.stac-item
2020-06-03 11:16:14	ga_s2bm_ard_3-2-1_51JXF_2020-06-03_final.stac-item
2020-06-18 12:05:29	ga_s2bm_ard_3-2-1_50JLQ_2020-06-18_final.stac-item
2020-07-02 11:45:56	ga_s2bm_ard_3-2-1_50JNN_2020-07-02_final.stac-item
2020-07-25 11:53:27	ga_s2bm_ard_3-2-1_50KNC_2020-07-25_final.stac-item
2020-10-13 11:56:15	ga_s2bm_ard_3-2-1_50JLM_2020-10-13_final.stac-item
2021-01-04 12:05:25	ga_s2bm_ard_3-2-1_50JKQ_2021-01-04_final.stac-item
2021-01-15 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2021-01-15_final.stac-item
2021-01-15 11:35:59	ga_s2bm_ard_3-2-1_51JUG_2021-01-15_final.stac-item
2021-02-13 12:04:41	ga_s2bm_ard_3-2-1_50JKT_2021-02-13_final.stac-item
2021-03-05 12:03:40	ga_s2bm_ard_3-2-1_50KLB_2021-03-05_final.stac-item
2021-03-06 11:33:59	ga_s2bm_ard_3-2-1_51KVQ_2021-03-06_final.stac-item
2021-04-07 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2021-04-07_final.stac-item
2021-04-12 11:24:29	ga_s2bm_ard_3-2-1_51JZM_2021-04-12_final.stac-item
2021-04-18 11:43:31	ga_s2bm_ard_3-2-1_51KVR_2021-04-18_final.stac-item
2021-05-19 11:16:58	ga_s2bm_ard_3-2-1_51HWC_2021-05-19_final
2021-06-03 12:05:52	ga_s2bm_ard_3-2-1_50JLN_2021-06-03_final.stac-item
2021-06-07 11:44:17	ga_s2bm_ard_3-2-1_50KRU_2021-06-07_final.stac-item
2021-06-18 11:14:42	ga_s2bm_ard_3-2-1_51JYM_2021-06-18_final.stac-item
2021-07-07 11:45:41	ga_s2bm_ard_3-2-1_50JNP_2021-07-07_final.stac-item
2021-08-09 11:56:41	ga_s2bm_ard_3-2-1_50HLK_2021-08-09_final.stac-item
2021-08-15 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2021-08-15_final.stac-item
2021-08-15 12:15:02	ga_s2bm_ard_3-2-1_49JGM_2021-08-15_final.stac-item
2021-09-15 11:42:09	ga_s2bm_ard_3-2-1_51KVB_2021-09-15_final.stac-item
2021-09-21 12:03:45	ga_s2bm_ard_3-2-1_50KKB_2021-09-21_final.stac-item
2021-10-05 11:43:24	ga_s2bm_ard_3-2-1_51KTS_2021-10-05_final.stac-item
2021-11-01 11:34:33	ga_s2bm_ard_3-2-1_51JUN_2021-11-01_final.stac-item
2021-11-08 11:24:27	ga_s2bm_ard_3-2-1_51JYN_2021-11-08_final.stac-item
2021-11-21 11:34:29	ga_s2bm_ard_3-2-1_51JUN_2021-11-21_final.stac-item
2021-12-15 11:16:53	ga_s2bm_ard_3-2-1_51HWC_2021-12-15_final
2022-03-07 11:53:15	ga_s2bm_ard_3-2-1_50KQC_2022-03-07_final.stac-item
2022-05-06 11:56:50	ga_s2bm_ard_3-2-1_50HLJ_2022-05-06_final.stac-item
2022-06-18 12:05:05	ga_s2bm_ard_3-2-1_49JGM_2022-06-18_final.stac-item
2022-06-28 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2022-06-28_final.stac-item
2022-07-12 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2022-07-12_final.stac-item
2022-09-30 11:43:17	ga_s2bm_ard_3-2-1_51KTT_2022-09-30_final.stac-item
2022-11-23 11:25:05	ga_s2bm_ard_3-2-1_51JYK_2022-11-23_final.stac-item
2022-12-09 11:43:00	ga_s2bm_ard_3-2-1_50KRD_2022-12-09_final.stac-item
2022-12-15 12:03:57	ga_s2bm_ard_3-2-1_49KHR_2022-12-15_final.stac-item
2023-02-11 11:25:02	ga_s2bm_ard_3-2-1_51JVL_2023-02-11_final
2023-02-23 12:04:21	ga_s2bm_ard_3-2-1_50KMU_2023-02-23_final
2023-05-02 11:24:43	ga_s2bm_ard_3-2-1_51JXM_2023-05-02_final
2023-05-05 11:34:05	ga_s2bm_ard_3-2-1_51KUQ_2023-05-05_final
2023-05-14 12:04:34	ga_s2bm_ard_3-2-1_50JMT_2023-05-14_final
2023-06-03 12:04:17	ga_s2bm_ard_3-2-1_50KKV_2023-06-03_final
2023-06-07 11:46:35	ga_s2bm_ard_3-2-1_50HQK_2023-06-07_final
2023-06-10 11:53:08	ga_s2bm_ard_3-2-1_50KQD_2023-06-10_final
2023-07-10 11:56:04	ga_s2bm_ard_3-2-1_50JKN_2023-07-10_final
2023-08-13 11:34:31	ga_s2bm_ard_3-2-1_51JWN_2023-08-13_final
2023-08-16 11:47:30	ga_s2bm_ard_3-2-1_50HMG_2023-08-16_final
2023-08-26 11:46:42	ga_s2bm_ard_3-2-1_50HNK_2023-08-26_final
2023-09-02 11:36:36	ga_s2bm_ard_3-2-1_51HTE_2023-09-02_final
2023-09-16 11:16:47	ga_s2bm_ard_3-2-1_51HWD_2023-09-16_final
2023-10-01 12:04:01	ga_s2bm_ard_3-2-1_50KKA_2023-10-01_final
2023-10-28 11:57:10	ga_s2bm_ard_3-2-1_50HMH_2023-10-28_final
2023-11-14 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2023-11-14_final
2023-11-28 11:24:23	ga_s2bm_ard_3-2-1_51JXN_2023-11-28_final
2023-12-27 11:53:22	ga_s2bm_ard_3-2-1_50KPC_2023-12-27_final
2024-01-03 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2024-01-03_final
2024-01-13 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2024-01-13_final
2024-01-29 12:03:21	ga_s2bm_ard_3-2-1_50KMC_2024-01-29_final
2024-03-20 11:36:19	ga_s2bm_ard_3-2-1_50JQL_2024-03-20_final
2024-04-15 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2024-04-15_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