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
2017-08-13 12:02:47	ga_s2bm_ard_3-2-1_50KKB_2017-08-13_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HQJ_2017-09-16_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KWB_2018-05-11_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_49JGM_2018-05-20_final.stac-item
2018-05-24 11:37:57	ga_s2bm_ard_3-2-1_50KRC_2018-05-24_final.stac-item
2018-06-12 12:13:19	ga_s2bm_ard_3-2-1_50KKB_2018-06-12_final.stac-item
2018-07-19 12:03:30	ga_s2bm_ard_3-2-1_49JGJ_2018-07-19_final.stac-item
2018-08-23 11:12:48	ga_s2bm_ard_3-2-1_51KZP_2018-08-23_final.stac-item
2018-10-05 11:21:50	ga_s2bm_ard_3-2-1_51JVH_2018-10-05_final.stac-item
2018-10-15 11:20:58	ga_s2bm_ard_3-2-1_51HUC_2018-10-15_final.stac-item
2018-10-31 11:46:25	ga_s2bm_ard_3-2-1_50HNH_2018-10-31_final.stac-item
2018-12-06 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2018-12-06_final.stac-item
2018-12-23 11:56:21	ga_s2bm_ard_3-2-1_50JLL_2018-12-23_final.stac-item
2019-01-15 12:03:44	ga_s2bm_ard_3-2-1_50KKB_2019-01-15_final.stac-item
2019-02-04 12:03:24	ga_s2bm_ard_3-2-1_50KMC_2019-02-04_final.stac-item
2019-04-09 11:43:01	ga_s2bm_ard_3-2-1_51KVU_2019-04-09_final.stac-item
2019-04-15 12:05:57	ga_s2bm_ard_3-2-1_50JLN_2019-04-15_final.stac-item
2019-04-23 11:24:21	ga_s2bm_ard_3-2-1_51KWP_2019-04-23_final.stac-item
2019-04-25 12:05:07	ga_s2bm_ard_3-2-1_49JGM_2019-04-25_final.stac-item
2019-06-14 12:04:25	ga_s2bm_ard_3-2-1_49KGQ_2019-06-14_final.stac-item
2019-07-22 11:26:09	ga_s2bm_ard_3-2-1_51JVG_2019-07-22_final.stac-item
2019-08-24 11:32:34	ga_s2bm_ard_3-2-1_51KWA_2019-08-24_final.stac-item
2019-10-12 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2019-10-12_final.stac-item
2019-10-26 11:43:37	ga_s2bm_ard_3-2-1_51KVR_2019-10-26_final.stac-item
2019-10-30 11:26:48	ga_s2bm_ard_3-2-1_51HUD_2019-10-30_final.stac-item
2019-12-09 11:24:06	ga_s2bm_ard_3-2-1_51KXP_2019-12-09_final.stac-item
2019-12-21 12:03:47	ga_s2bm_ard_3-2-1_50KMA_2019-12-21_final.stac-item
2019-12-29 11:22:36	ga_s2bm_ard_3-2-1_51KYV_2019-12-29_final.stac-item
2020-01-21 11:32:56	ga_s2bm_ard_3-2-1_51KYT_2020-01-21_final.stac-item
2020-02-07 11:24:17	ga_s2bm_ard_3-2-1_51JYN_2020-02-07_final.stac-item
2020-02-16 11:53:20	ga_s2bm_ard_3-2-1_50KNC_2020-02-16_final.stac-item
2020-02-27 11:23:47	ga_s2bm_ard_3-2-1_51KZQ_2020-02-27_final.stac-item
2020-03-07 11:56:02	ga_s2bm_ard_3-2-1_50JNM_2020-03-07_final.stac-item
2020-05-10 11:35:32	ga_s2bm_ard_3-2-1_51JTJ_2020-05-10_final.stac-item
2020-06-09 11:32:31	ga_s2bm_ard_3-2-1_51KWA_2020-06-09_final.stac-item
2020-07-16 11:25:29	ga_s2bm_ard_3-2-1_51JWJ_2020-07-16_final.stac-item
2020-08-15 11:26:42	ga_s2bm_ard_3-2-1_51HXD_2020-08-15_final.stac-item
2020-09-07 11:36:34	ga_s2bm_ard_3-2-1_51HTE_2020-09-07_final.stac-item
2020-09-26 12:05:43	ga_s2bm_ard_3-2-1_50JKP_2020-09-26_final.stac-item
2020-11-16 11:33:23	ga_s2bm_ard_3-2-1_51KUT_2020-11-16_final.stac-item
2020-12-22 11:52:16	ga_s2bm_ard_3-2-1_50KQG_2020-12-22_final
2021-01-01 11:56:09	ga_s2bm_ard_3-2-1_50JLM_2021-01-01_final.stac-item
2021-02-17 11:42:11	ga_s2bm_ard_3-2-1_51KVB_2021-02-17_final.stac-item
2021-02-21 11:26:56	ga_s2bm_ard_3-2-1_51HVC_2021-02-21_final.stac-item
2021-03-06 11:32:18	ga_s2bm_ard_3-2-1_51KVB_2021-03-06_final.stac-item
2021-03-23 11:22:55	ga_s2bm_ard_3-2-1_51KYU_2021-03-23_final.stac-item
2021-06-08 11:14:24	ga_s2bm_ard_3-2-1_51JZN_2021-06-08_final.stac-item
2021-06-13 12:04:49	ga_s2bm_ard_3-2-1_49JHN_2021-06-13_final.stac-item
2021-07-31 11:25:29	ga_s2bm_ard_3-2-1_51JWJ_2021-07-31_final.stac-item
2021-08-13 11:32:47	ga_s2bm_ard_3-2-1_51KVV_2021-08-13_final.stac-item
2021-08-22 12:05:37	ga_s2bm_ard_3-2-1_50JLP_2021-08-22_final.stac-item
2021-09-12 11:32:43	ga_s2bm_ard_3-2-1_51KVV_2021-09-12_final.stac-item
2021-10-11 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2021-10-11_final.stac-item
2021-10-12 11:37:04	ga_s2bm_ard_3-2-1_50HQH_2021-10-12_final.stac-item
2021-11-11 11:32:43	ga_s2bm_ard_3-2-1_51KWV_2021-11-11_final.stac-item
2021-12-08 11:23:45	ga_s2bm_ard_3-2-1_51KZQ_2021-12-08_final.stac-item
2022-01-07 11:22:48	ga_s2bm_ard_3-2-1_51KZU_2022-01-07_final.stac-item
2022-01-17 11:25:53	ga_s2bm_ard_3-2-1_51JWG_2022-01-17_final.stac-item
2022-02-23 11:13:49	ga_s2bm_ard_3-2-1_51KZQ_2022-02-23_final.stac-item
2022-02-25 11:56:00	ga_s2bm_ard_3-2-1_50JNM_2022-02-25_final.stac-item
2022-03-07 11:55:44	ga_s2bm_ard_3-2-1_50JKP_2022-03-07_final.stac-item
2022-03-21 11:36:03	ga_s2bm_ard_3-2-1_50JQM_2022-03-21_final.stac-item
2022-03-30 12:03:41	ga_s2bm_ard_3-2-1_50KNA_2022-03-30_final.stac-item
2022-04-10 11:32:59	ga_s2bm_ard_3-2-1_51KYT_2022-04-10_final.stac-item
2022-04-26 11:56:05	ga_s2bm_ard_3-2-1_50JLM_2022-04-26_final.stac-item
2022-06-06 11:24:12	ga_s2bm_ard_3-2-1_51KXP_2022-06-06_final.stac-item
2022-07-28 12:03:49	ga_s2bm_ard_3-2-1_50KKB_2022-07-28_final.stac-item
2022-08-21 11:44:17	ga_s2bm_ard_3-2-1_51KTP_2022-08-21_final.stac-item
2022-09-13 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2022-09-13_final.stac-item
2022-09-14 11:22:54	ga_s2bm_ard_3-2-1_51KZU_2022-09-14_final.stac-item
2022-09-27 11:36:29	ga_s2bm_ard_3-2-1_51HUE_2022-09-27_final.stac-item
2022-10-07 11:32:41	ga_s2bm_ard_3-2-1_51KWV_2022-10-07_final.stac-item
2022-10-10 11:42:07	ga_s2bm_ard_3-2-1_51KWB_2022-10-10_final.stac-item
2022-12-09 11:43:40	ga_s2bm_ard_3-2-1_51KUR_2022-12-09_final.stac-item
2022-12-25 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2022-12-25_final.stac-item
2023-01-12 11:23:45	ga_s2bm_ard_3-2-1_51KZQ_2023-01-12_final.stac-item
2023-02-04 11:32:23	ga_s2bm_ard_3-2-1_51KXA_2023-02-04_final.stac-item
2023-02-07 11:42:40	ga_s2bm_ard_3-2-1_51KVV_2023-02-07_final
2023-02-20 11:56:36	ga_s2bm_ard_3-2-1_50HMK_2023-02-20_final
2023-03-26 11:33:05	ga_s2bm_ard_3-2-1_51KYT_2023-03-26_final
2023-04-15 11:34:15	ga_s2bm_ard_3-2-1_51KVP_2023-04-15_final
2023-04-15 11:34:30	ga_s2bm_ard_3-2-1_51JVN_2023-04-15_final
2023-05-05 11:33:04	ga_s2bm_ard_3-2-1_51KVU_2023-05-05_final
2023-05-27 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-05-27_final
2023-06-06 12:14:46	ga_s2bm_ard_3-2-1_49JGN_2023-06-06_final
2023-06-28 11:15:00	ga_s2bm_ard_3-2-1_51JYL_2023-06-28_final
2023-07-20 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-07-20_final
2023-08-03 11:32:34	ga_s2bm_ard_3-2-1_51KWA_2023-08-03_final
2023-08-10 11:22:47	ga_s2bm_ard_3-2-1_51KYV_2023-08-10_final
2023-08-20 11:24:13	ga_s2bm_ard_3-2-1_51KYP_2023-08-20_final
2023-10-02 11:32:42	ga_s2bm_ard_3-2-1_51KXV_2023-10-02_final
2023-10-11 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-10-11_final
2023-10-25 11:42:10	ga_s2bm_ard_3-2-1_51KWB_2023-10-25_final
2023-11-28 11:24:08	ga_s2bm_ard_3-2-1_51KXP_2023-11-28_final
2023-12-08 11:25:21	ga_s2bm_ard_3-2-1_51JXJ_2023-12-08_final
2023-12-21 11:32:20	ga_s2bm_ard_3-2-1_51KVB_2023-12-21_final
2023-12-25 11:13:30	ga_s2bm_ard_3-2-1_51KZS_2023-12-25_final
2023-12-31 11:34:06	ga_s2bm_ard_3-2-1_51KXP_2023-12-31_final
2024-01-10 11:32:10	ga_s2bm_ard_3-2-1_51KXB_2024-01-10_final
2024-04-03 11:16:57	ga_s2bm_ard_3-2-1_51HWC_2024-04-03_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

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