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
2017-09-17 11:11:51	ga_s2bm_ard_3-2-1_51HYE_2017-09-17_final.stac-item
2017-09-17 11:11:51	ga_s2bm_ard_3-2-1_51JXH_2017-09-17_final.stac-item
2017-09-19 11:55:56	ga_s2bm_ard_3-2-1_50HMK_2017-09-19_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50JLP_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50JLS_2017-09-22_final.stac-item
2017-10-09 11:55:53	ga_s2bm_ard_3-2-1_50HLK_2017-10-09_final.stac-item
2017-11-19 11:16:47	ga_s2bm_ard_3-2-1_51JVF_2017-11-19_final.stac-item
2017-12-05 11:40:37	ga_s2bm_ard_3-2-1_51JUN_2017-12-05_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50KRD_2017-12-18_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_51HVE_2017-12-22_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HNH_2017-12-25_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50HNK_2017-12-28_final.stac-item
2018-01-01 11:30:30	ga_s2bm_ard_3-2-1_51JVF_2018-01-01_final.stac-item
2018-01-14 11:46:06	ga_s2bm_ard_3-2-1_50HNJ_2018-01-14_final.stac-item
2018-01-18 11:16:52	ga_s2bm_ard_3-2-1_51JWF_2018-01-18_final.stac-item
2018-02-07 11:16:52	ga_s2bm_ard_3-2-1_51HUE_2018-02-07_final.stac-item
2018-02-07 11:16:52	ga_s2bm_ard_3-2-1_51JVJ_2018-02-07_final.stac-item
2018-02-27 11:21:10	ga_s2bm_ard_3-2-1_51JVF_2018-02-27_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50HLK_2018-04-27_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JMR_2018-04-27_final.stac-item
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_50HPJ_2018-05-04_final.stac-item
2018-05-05 11:13:23	ga_s2bm_ard_3-2-1_51HYE_2018-05-05_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50HLK_2018-05-07_final.stac-item
2018-05-10 12:02:48	ga_s2bm_ard_3-2-1_50KKU_2018-05-10_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50HPH_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50JQN_2018-05-11_final.stac-item
2018-05-13 12:13:20	ga_s2bm_ard_3-2-1_49KGR_2018-05-13_final.stac-item
2018-05-13 12:14:07	ga_s2bm_ard_3-2-1_50KKV_2018-05-13_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50JNM_2018-05-14_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_51JTF_2018-05-14_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JKP_2018-05-20_final.stac-item
2018-05-30 12:02:46	ga_s2bm_ard_3-2-1_50KLB_2018-05-30_final.stac-item
2018-06-16 11:51:10	ga_s2bm_ard_3-2-1_50JKN_2018-06-16_final.stac-item
2018-07-29 12:02:46	ga_s2bm_ard_3-2-1_49KHR_2018-07-29_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50JLM_2018-08-05_final.stac-item
2018-09-02 11:14:34	ga_s2bm_ard_3-2-1_51HWE_2018-09-02_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JUF_2018-09-05_final.stac-item
2018-09-05 11:21:46	ga_s2bm_ard_3-2-1_51JVF_2018-09-05_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HMJ_2018-09-21_final.stac-item
2019-01-09 11:47:08	ga_s2bm_ard_3-2-1_50HMH_2019-01-09_final.stac-item
2019-02-18 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2019-02-18_final.stac-item
2019-03-01 11:16:42	ga_s2bm_ard_3-2-1_51HWD_2019-03-01_final.stac-item
2019-06-05 11:34:11	ga_s2bm_ard_3-2-1_51KUQ_2019-06-05_final.stac-item
2019-06-15 11:36:39	ga_s2bm_ard_3-2-1_51HTE_2019-06-15_final.stac-item
2019-08-14 11:34:21	ga_s2bm_ard_3-2-1_51KVP_2019-08-14_final.stac-item
2019-12-08 11:53:25	ga_s2bm_ard_3-2-1_50KMC_2019-12-08_final.stac-item
2019-12-19 11:26:13	ga_s2bm_ard_3-2-1_51JUF_2019-12-19_final.stac-item
2019-12-25 11:46:50	ga_s2bm_ard_3-2-1_50HMJ_2019-12-25_final.stac-item
2020-03-27 11:53:22	ga_s2bm_ard_3-2-1_50KNC_2020-03-27_final.stac-item
2020-03-30 12:05:53	ga_s2bm_ard_3-2-1_50JKN_2020-03-30_final.stac-item
2020-04-07 11:26:08	ga_s2bm_ard_3-2-1_51JWF_2020-04-07_final.stac-item
2020-04-20 11:33:25	ga_s2bm_ard_3-2-1_51KVS_2020-04-20_final.stac-item
2020-06-02 11:43:16	ga_s2bm_ard_3-2-1_51KUT_2020-06-02_final.stac-item
2020-06-19 11:33:36	ga_s2bm_ard_3-2-1_51KUS_2020-06-19_final.stac-item
2020-08-20 12:15:00	ga_s2bm_ard_3-2-1_49JGM_2020-08-20_final.stac-item
2020-12-29 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2020-12-29_final.stac-item
2021-01-18 11:45:50	ga_s2bm_ard_3-2-1_50JPN_2021-01-18_final.stac-item
2021-02-10 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2021-02-10_final.stac-item
2021-02-16 12:13:52	ga_s2bm_ard_3-2-1_49KHR_2021-02-16_final.stac-item
2021-07-27 11:42:48	ga_s2bm_ard_3-2-1_51KUV_2021-07-27_final.stac-item
2021-08-10 11:24:33	ga_s2bm_ard_3-2-1_51JZM_2021-08-10_final.stac-item
2021-09-02 11:36:16	ga_s2bm_ard_3-2-1_50JQL_2021-09-02_final.stac-item
2021-09-22 11:34:13	ga_s2bm_ard_3-2-1_51JXN_2021-09-22_final.stac-item
2021-10-28 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2021-10-28_final.stac-item
2022-04-30 11:36:31	ga_s2bm_ard_3-2-1_50HPK_2022-04-30_final.stac-item
2022-05-03 11:46:10	ga_s2bm_ard_3-2-1_50JQL_2022-05-03_final.stac-item
2022-05-06 11:52:15	ga_s2bm_ard_3-2-1_50KQG_2022-05-06_final
2022-07-22 11:47:11	ga_s2bm_ard_3-2-1_50HNH_2022-07-22_final.stac-item
2022-07-25 11:53:36	ga_s2bm_ard_3-2-1_50KMC_2022-07-25_final.stac-item
2022-07-28 12:03:49	ga_s2bm_ard_3-2-1_50KKB_2022-07-28_final.stac-item
2022-10-29 12:15:09	ga_s2bm_ard_3-2-1_49JGL_2022-10-29_final.stac-item
2022-12-19 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2022-12-19_final.stac-item
2022-12-22 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2022-12-22_final.stac-item
2023-01-18 11:47:07	ga_s2bm_ard_3-2-1_50HMH_2023-01-18_final.stac-item
2023-02-06 12:14:54	ga_s2bm_ard_3-2-1_49JGM_2023-02-06_final
2023-04-28 11:43:05	ga_s2bm_ard_3-2-1_51KTU_2023-04-28_final
2023-05-04 12:03:47	ga_s2bm_ard_3-2-1_50KKB_2023-05-04_final
2023-05-12 11:25:59	ga_s2bm_ard_3-2-1_51JWG_2023-05-12_final
2023-05-24 12:04:04	ga_s2bm_ard_3-2-1_50KKA_2023-05-24_final
2023-06-03 12:05:59	ga_s2bm_ard_3-2-1_50JKN_2023-06-03_final
2023-06-13 12:03:32	ga_s2bm_ard_3-2-1_50KLC_2023-06-13_final
2023-06-30 11:55:51	ga_s2bm_ard_3-2-1_50JKP_2023-06-30_final
2023-09-19 11:26:36	ga_s2bm_ard_3-2-1_51HUE_2023-09-19_final
2023-10-08 11:55:57	ga_s2bm_ard_3-2-1_50JKN_2023-10-08_final
2023-10-29 11:26:38	ga_s2bm_ard_3-2-1_51HXD_2023-10-29_final
2023-10-31 12:03:46	ga_s2bm_ard_3-2-1_50KKB_2023-10-31_final
2023-11-11 11:36:25	ga_s2bm_ard_3-2-1_51HVE_2023-11-11_final
2023-11-17 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2023-11-17_final
2023-11-20 12:03:41	ga_s2bm_ard_3-2-1_49KHS_2023-11-20_final
2023-12-10 12:03:41	ga_s2bm_ard_3-2-1_49KHS_2023-12-10_final
2023-12-14 11:42:26	ga_s2bm_ard_3-2-1_51KVA_2023-12-14_final
2024-01-12 12:15:08	ga_s2bm_ard_3-2-1_49JGL_2024-01-12_final
2024-01-23 11:43:50	ga_s2bm_ard_3-2-1_50KQA_2024-01-23_final
2024-02-05 11:52:36	ga_s2bm_ard_3-2-1_50KPF_2024-02-05_final
2024-03-13 11:45:00	ga_s2bm_ard_3-2-1_50JQR_2024-03-13_final
2024-03-13 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2024-03-13_final
2024-04-05 11:53:29	ga_s2bm_ard_3-2-1_50KMC_2024-04-05_final
2024-04-06 11:26:13	ga_s2bm_ard_3-2-1_51JVF_2024-04-06_final
2024-04-15 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2024-04-15_final
2024-05-15 11:52:18	ga_s2bm_ard_3-2-1_50KQG_2024-05-15_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