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
2017-07-05 11:32:58	ga_s2bm_ard_3-2-1_51KVS_2017-07-05_final.stac-item
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49JFM_2017-09-15_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50KPC_2017-09-29_final.stac-item
2017-11-25 11:37:37	ga_s2bm_ard_3-2-1_50JRT_2017-11-25_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_51JWK_2018-01-31_final.stac-item
2018-03-05 11:42:06	ga_s2bm_ard_3-2-1_51KUV_2018-03-05_final.stac-item
2018-03-25 11:44:34	ga_s2bm_ard_3-2-1_50HQK_2018-03-25_final.stac-item
2018-06-22 12:13:20	ga_s2bm_ard_3-2-1_49KGR_2018-06-22_final.stac-item
2018-07-13 11:40:15	ga_s2bm_ard_3-2-1_50HPK_2018-07-13_final.stac-item
2018-08-12 11:41:45	ga_s2bm_ard_3-2-1_51KVT_2018-08-12_final.stac-item
2018-09-02 11:14:34	ga_s2bm_ard_3-2-1_51JYF_2018-09-02_final.stac-item
2018-12-20 11:43:10	ga_s2bm_ard_3-2-1_51KUT_2018-12-20_final.stac-item
2019-01-19 11:42:27	ga_s2bm_ard_3-2-1_51KVA_2019-01-19_final.stac-item
2019-02-17 12:14:56	ga_s2bm_ard_3-2-1_49JGM_2019-02-17_final.stac-item
2019-03-21 11:16:11	ga_s2bm_ard_3-2-1_51JXF_2019-03-21_final.stac-item
2019-05-12 11:56:34	ga_s2bm_ard_3-2-1_50JLL_2019-05-12_final.stac-item
2019-05-16 11:33:54	ga_s2bm_ard_3-2-1_51KVR_2019-05-16_final.stac-item
2019-05-23 11:27:10	ga_s2bm_ard_3-2-1_51HUC_2019-05-23_final.stac-item
2019-06-15 11:33:52	ga_s2bm_ard_3-2-1_51KVR_2019-06-15_final.stac-item
2019-07-15 11:33:43	ga_s2bm_ard_3-2-1_51KUS_2019-07-15_final.stac-item
2019-08-24 11:33:47	ga_s2bm_ard_3-2-1_51KWR_2019-08-24_final.stac-item
2019-09-12 12:05:52	ga_s2bm_ard_3-2-1_50JLN_2019-09-12_final.stac-item
2019-09-13 11:33:42	ga_s2bm_ard_3-2-1_51KWR_2019-09-13_final.stac-item
2019-12-25 11:42:55	ga_s2bm_ard_3-2-1_51KUU_2019-12-25_final.stac-item
2020-01-08 11:26:42	ga_s2bm_ard_3-2-1_51HUD_2020-01-08_final.stac-item
2020-01-24 11:43:03	ga_s2bm_ard_3-2-1_51KVT_2020-01-24_final.stac-item
2020-01-31 11:33:23	ga_s2bm_ard_3-2-1_51KVS_2020-01-31_final.stac-item
2020-02-07 11:23:37	ga_s2bm_ard_3-2-1_51KXR_2020-02-07_final.stac-item
2020-02-10 11:32:27	ga_s2bm_ard_3-2-1_51KVA_2020-02-10_final.stac-item
2020-04-23 11:43:06	ga_s2bm_ard_3-2-1_51KVT_2020-04-23_final.stac-item
2020-05-30 11:34:12	ga_s2bm_ard_3-2-1_51KWP_2020-05-30_final.stac-item
2020-06-19 11:36:51	ga_s2bm_ard_3-2-1_50HQJ_2020-06-19_final.stac-item
2020-06-29 11:33:11	ga_s2bm_ard_3-2-1_51KXT_2020-06-29_final.stac-item
2020-09-30 11:42:31	ga_s2bm_ard_3-2-1_51KVA_2020-09-30_final.stac-item
2020-10-07 11:34:00	ga_s2bm_ard_3-2-1_51KWQ_2020-10-07_final.stac-item
2020-10-17 11:33:34	ga_s2bm_ard_3-2-1_51KVS_2020-10-17_final.stac-item
2020-12-08 12:14:58	ga_s2bm_ard_3-2-1_49JFM_2020-12-08_final.stac-item
2020-12-19 11:43:07	ga_s2bm_ard_3-2-1_51KVT_2020-12-19_final.stac-item
2021-02-04 11:37:26	ga_s2bm_ard_3-2-1_50HNG_2021-02-04_final
2021-02-17 11:43:09	ga_s2bm_ard_3-2-1_51KVT_2021-02-17_final.stac-item
2021-02-24 11:33:54	ga_s2bm_ard_3-2-1_51KWQ_2021-02-24_final.stac-item
2021-03-20 11:14:40	ga_s2bm_ard_3-2-1_51JYM_2021-03-20_final.stac-item
2021-04-04 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2021-04-04_final.stac-item
2021-05-05 11:32:55	ga_s2bm_ard_3-2-1_51KWU_2021-05-05_final.stac-item
2021-05-14 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2021-05-14_final.stac-item
2021-07-03 12:03:21	ga_s2bm_ard_3-2-1_50KNC_2021-07-03_final.stac-item
2021-07-04 11:36:50	ga_s2bm_ard_3-2-1_50HQJ_2021-07-04_final.stac-item
2021-07-10 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2021-07-10_final.stac-item
2021-08-03 11:32:21	ga_s2bm_ard_3-2-1_51KVB_2021-08-03_final.stac-item
2021-10-11 12:06:11	ga_s2bm_ard_3-2-1_50JKM_2021-10-11_final.stac-item
2021-10-22 11:33:40	ga_s2bm_ard_3-2-1_51KXR_2021-10-22_final.stac-item
2022-01-10 11:33:19	ga_s2bm_ard_3-2-1_51KXS_2022-01-10_final.stac-item
2022-01-23 11:42:58	ga_s2bm_ard_3-2-1_51KTU_2022-01-23_final.stac-item
2022-02-12 11:43:16	ga_s2bm_ard_3-2-1_50KQC_2022-02-12_final.stac-item
2022-02-16 11:23:36	ga_s2bm_ard_3-2-1_51KXR_2022-02-16_final.stac-item
2022-03-01 11:33:35	ga_s2bm_ard_3-2-1_51KXR_2022-03-01_final.stac-item
2022-03-27 11:53:44	ga_s2bm_ard_3-2-1_50KQA_2022-03-27_final.stac-item
2022-04-29 12:04:32	ga_s2bm_ard_3-2-1_49JHN_2022-04-29_final.stac-item
2022-06-28 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2022-06-28_final.stac-item
2022-08-10 12:15:14	ga_s2bm_ard_3-2-1_49JGL_2022-08-10_final.stac-item
2022-09-27 11:33:38	ga_s2bm_ard_3-2-1_51KXR_2022-09-27_final.stac-item
2022-10-07 11:34:08	ga_s2bm_ard_3-2-1_51KWP_2022-10-07_final.stac-item
2022-10-09 12:14:58	ga_s2bm_ard_3-2-1_49JFM_2022-10-09_final.stac-item
2022-10-27 11:33:55	ga_s2bm_ard_3-2-1_51KWQ_2022-10-27_final.stac-item
2022-12-26 11:33:23	ga_s2bm_ard_3-2-1_51KXS_2022-12-26_final.stac-item
2022-12-26 11:33:44	ga_s2bm_ard_3-2-1_51KVR_2022-12-26_final.stac-item
2023-01-02 11:23:56	ga_s2bm_ard_3-2-1_51KXQ_2023-01-02_final.stac-item
2023-01-21 11:53:22	ga_s2bm_ard_3-2-1_50KNC_2023-01-21_final.stac-item
2023-01-24 12:03:42	ga_s2bm_ard_3-2-1_50KKB_2023-01-24_final.stac-item
2023-01-25 11:32:56	ga_s2bm_ard_3-2-1_51KWU_2023-01-25_final.stac-item
2023-03-09 11:42:49	ga_s2bm_ard_3-2-1_51KUV_2023-03-09_final
2023-03-16 11:33:38	ga_s2bm_ard_3-2-1_51KUS_2023-03-16_final
2023-04-19 11:16:24	ga_s2bm_ard_3-2-1_51HYE_2023-04-19_final
2023-04-24 12:04:37	ga_s2bm_ard_3-2-1_49KGP_2023-04-24_final
2023-04-24 12:05:40	ga_s2bm_ard_3-2-1_50JLP_2023-04-24_final
2023-05-01 11:53:55	ga_s2bm_ard_3-2-1_50KQA_2023-05-01_final
2023-05-02 11:23:02	ga_s2bm_ard_3-2-1_51KXU_2023-05-02_final
2023-05-25 11:34:01	ga_s2bm_ard_3-2-1_51KWQ_2023-05-25_final
2023-06-04 11:33:13	ga_s2bm_ard_3-2-1_51KXT_2023-06-04_final
2023-06-24 11:37:21	ga_s2bm_ard_3-2-1_50HQG_2023-06-24_final
2023-07-01 11:26:41	ga_s2bm_ard_3-2-1_51HXD_2023-07-01_final
2023-07-11 11:23:33	ga_s2bm_ard_3-2-1_51KXS_2023-07-11_final
2023-08-13 11:33:47	ga_s2bm_ard_3-2-1_51KWR_2023-08-13_final
2023-08-26 11:42:50	ga_s2bm_ard_3-2-1_51KUV_2023-08-26_final
2023-09-02 11:33:43	ga_s2bm_ard_3-2-1_51KXR_2023-09-02_final
2023-09-09 11:24:01	ga_s2bm_ard_3-2-1_51KXQ_2023-09-09_final
2023-10-12 11:33:15	ga_s2bm_ard_3-2-1_51KWT_2023-10-12_final
2023-11-11 11:32:42	ga_s2bm_ard_3-2-1_51KXV_2023-11-11_final
2023-12-01 11:32:55	ga_s2bm_ard_3-2-1_51KWU_2023-12-01_final
2023-12-21 11:33:39	ga_s2bm_ard_3-2-1_51KXR_2023-12-21_final
2023-12-31 11:33:53	ga_s2bm_ard_3-2-1_51KXQ_2023-12-31_final
2024-01-02 12:15:00	ga_s2bm_ard_3-2-1_49JFM_2024-01-02_final
2024-01-10 11:32:42	ga_s2bm_ard_3-2-1_51KWV_2024-01-10_final
2024-01-10 11:33:11	ga_s2bm_ard_3-2-1_51KWT_2024-01-10_final
2024-01-10 11:33:14	ga_s2bm_ard_3-2-1_51KVT_2024-01-10_final
2024-01-20 11:33:37	ga_s2bm_ard_3-2-1_51KXR_2024-01-20_final
2024-01-22 12:14:59	ga_s2bm_ard_3-2-1_49JFM_2024-01-22_final
2024-01-30 11:34:08	ga_s2bm_ard_3-2-1_51KWP_2024-01-30_final
2024-02-12 11:42:14	ga_s2bm_ard_3-2-1_51KVB_2024-02-12_final
2024-02-26 11:23:42	ga_s2bm_ard_3-2-1_51KXR_2024-02-26_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