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_51JTF_2017-07-05_final.stac-item
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51JVJ_2017-09-23_final.stac-item
2017-10-19 11:51:53	ga_s2bm_ard_3-2-1_50KQC_2017-10-19_final.stac-item
2017-10-30 11:25:33	ga_s2bm_ard_3-2-1_51HUC_2017-10-30_final.stac-item
2017-11-08 11:44:06	ga_s2bm_ard_3-2-1_50KRC_2017-11-08_final.stac-item
2017-12-08 11:49:07	ga_s2bm_ard_3-2-1_50KPC_2017-12-08_final.stac-item
2018-01-17 11:49:12	ga_s2bm_ard_3-2-1_50JNM_2018-01-17_final.stac-item
2018-01-21 11:35:57	ga_s2bm_ard_3-2-1_50HPJ_2018-01-21_final.stac-item
2018-02-26 11:49:11	ga_s2bm_ard_3-2-1_50JNM_2018-02-26_final.stac-item
2018-03-01 12:02:40	ga_s2bm_ard_3-2-1_50JLM_2018-03-01_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50KNC_2018-03-11_final.stac-item
2018-03-12 11:35:28	ga_s2bm_ard_3-2-1_51JVG_2018-03-12_final.stac-item
2018-05-10 12:02:48	ga_s2bm_ard_3-2-1_50KKA_2018-05-10_final.stac-item
2018-10-01 11:38:19	ga_s2bm_ard_3-2-1_50KRC_2018-10-01_final.stac-item
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50HNJ_2018-10-11_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JLL_2018-10-24_final.stac-item
2018-11-06 12:03:42	ga_s2bm_ard_3-2-1_50KKB_2018-11-06_final.stac-item
2018-11-11 11:16:28	ga_s2bm_ard_3-2-1_51HWE_2018-11-11_final.stac-item
2019-01-13 11:27:01	ga_s2bm_ard_3-2-1_51HUC_2019-01-13_final.stac-item
2019-02-01 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2019-02-01_final.stac-item
2019-02-17 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-02-17_final.stac-item
2019-03-13 11:53:22	ga_s2bm_ard_3-2-1_50KNC_2019-03-13_final.stac-item
2019-04-09 11:46:23	ga_s2bm_ard_3-2-1_50JPL_2019-04-09_final.stac-item
2019-04-29 11:45:19	ga_s2bm_ard_3-2-1_50JNR_2019-04-29_final.stac-item
2019-05-15 12:04:07	ga_s2bm_ard_3-2-1_50KKA_2019-05-15_final.stac-item
2019-06-02 11:26:26	ga_s2bm_ard_3-2-1_51JUF_2019-06-02_final.stac-item
2019-06-21 11:55:35	ga_s2bm_ard_3-2-1_50JLQ_2019-06-21_final.stac-item
2019-06-28 11:45:01	ga_s2bm_ard_3-2-1_50JPS_2019-06-28_final.stac-item
2019-07-28 11:46:50	ga_s2bm_ard_3-2-1_50HQJ_2019-07-28_final.stac-item
2019-09-16 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2019-09-16_final.stac-item
2019-09-30 11:26:55	ga_s2bm_ard_3-2-1_51HVC_2019-09-30_final.stac-item
2019-10-10 11:26:59	ga_s2bm_ard_3-2-1_51HVC_2019-10-10_final.stac-item
2019-10-15 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-10-15_final.stac-item
2019-10-19 11:55:14	ga_s2bm_ard_3-2-1_50JLR_2019-10-19_final.stac-item
2019-11-05 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2019-11-05_final.stac-item
2019-12-18 11:55:07	ga_s2bm_ard_3-2-1_50JLR_2019-12-18_final.stac-item
2019-12-19 11:25:40	ga_s2bm_ard_3-2-1_51JVH_2019-12-19_final.stac-item
2019-12-24 12:14:51	ga_s2bm_ard_3-2-1_49JGM_2019-12-24_final.stac-item
2019-12-31 12:04:26	ga_s2bm_ard_3-2-1_49KGP_2019-12-31_final.stac-item
2020-01-10 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2020-01-10_final.stac-item
2020-01-20 12:05:23	ga_s2bm_ard_3-2-1_49JGK_2020-01-20_final.stac-item
2020-01-27 11:53:17	ga_s2bm_ard_3-2-1_50KNC_2020-01-27_final.stac-item
2020-04-20 11:36:47	ga_s2bm_ard_3-2-1_50HPJ_2020-04-20_final.stac-item
2020-06-18 12:03:26	ga_s2bm_ard_3-2-1_50KMC_2020-06-18_final.stac-item
2020-06-21 12:14:10	ga_s2bm_ard_3-2-1_50KKV_2020-06-21_final.stac-item
2020-08-14 11:54:48	ga_s2bm_ard_3-2-1_50JLT_2020-08-14_final.stac-item
2020-10-16 12:04:03	ga_s2bm_ard_3-2-1_49KHR_2020-10-16_final.stac-item
2020-11-16 11:35:46	ga_s2bm_ard_3-2-1_51JUH_2020-11-16_final.stac-item
2020-12-12 11:53:33	ga_s2bm_ard_3-2-1_50KPB_2020-12-12_final.stac-item
2021-01-04 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2021-01-04_final.stac-item
2021-01-05 11:36:37	ga_s2bm_ard_3-2-1_50HPK_2021-01-05_final.stac-item
2021-02-23 12:05:39	ga_s2bm_ard_3-2-1_50JKP_2021-02-23_final.stac-item
2021-03-10 11:16:43	ga_s2bm_ard_3-2-1_51HWD_2021-03-10_final.stac-item
2021-04-15 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2021-04-15_final.stac-item
2021-05-18 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2021-05-18_final.stac-item
2021-07-07 11:45:26	ga_s2bm_ard_3-2-1_50JNQ_2021-07-07_final.stac-item
2021-08-09 11:53:56	ga_s2bm_ard_3-2-1_50KQA_2021-08-09_final.stac-item
2021-08-10 11:25:43	ga_s2bm_ard_3-2-1_51JWH_2021-08-10_final.stac-item
2021-08-20 11:26:46	ga_s2bm_ard_3-2-1_51HUD_2021-08-20_final.stac-item
2021-09-05 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2021-09-05_final.stac-item
2021-09-11 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2021-09-11_final.stac-item
2021-10-08 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2021-10-08_final.stac-item
2021-11-01 11:34:44	ga_s2bm_ard_3-2-1_51JVM_2021-11-01_final.stac-item
2021-11-27 11:53:20	ga_s2bm_ard_3-2-1_50KNC_2021-11-27_final.stac-item
2021-12-27 11:56:03	ga_s2bm_ard_3-2-1_50JMM_2021-12-27_final.stac-item
2022-03-04 11:44:48	ga_s2bm_ard_3-2-1_51JUL_2022-03-04_final.stac-item
2022-07-01 12:14:32	ga_s2bm_ard_3-2-1_49KGP_2022-07-01_final.stac-item
2022-07-26 11:26:52	ga_s2bm_ard_3-2-1_51HUD_2022-07-26_final.stac-item
2022-08-12 11:16:26	ga_s2bm_ard_3-2-1_51HYE_2022-08-12_final.stac-item
2022-08-17 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2022-08-17_final.stac-item
2022-10-16 12:04:38	ga_s2bm_ard_3-2-1_49JHN_2022-10-16_final.stac-item
2022-10-24 11:25:45	ga_s2bm_ard_3-2-1_51JVH_2022-10-24_final.stac-item
2022-11-05 12:04:16	ga_s2bm_ard_3-2-1_49KGQ_2022-11-05_final.stac-item
2022-11-23 11:25:30	ga_s2bm_ard_3-2-1_51JVJ_2022-11-23_final.stac-item
2022-12-02 11:55:54	ga_s2bm_ard_3-2-1_50JLN_2022-12-02_final.stac-item
2022-12-26 11:35:03	ga_s2bm_ard_3-2-1_51JTL_2022-12-26_final.stac-item
2023-01-21 11:57:18	ga_s2bm_ard_3-2-1_50HMG_2023-01-21_final
2023-03-08 12:13:58	ga_s2bm_ard_3-2-1_49KHR_2023-03-08_final
2023-04-14 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2023-04-14_final
2023-06-01 11:25:31	ga_s2bm_ard_3-2-1_51JWJ_2023-06-01_final
2023-06-11 11:26:41	ga_s2bm_ard_3-2-1_51HXD_2023-06-11_final
2023-06-14 11:37:26	ga_s2bm_ard_3-2-1_50HPG_2023-06-14_final
2023-06-14 11:37:31	ga_s2bm_ard_3-2-1_50HNG_2023-06-14_final
2023-07-24 11:34:38	ga_s2bm_ard_3-2-1_51JUN_2023-07-24_final
2023-08-13 11:35:39	ga_s2bm_ard_3-2-1_51JTJ_2023-08-13_final
2023-09-12 11:36:03	ga_s2bm_ard_3-2-1_51JUG_2023-09-12_final
2023-09-15 11:44:23	ga_s2bm_ard_3-2-1_50KQU_2023-09-15_final
2023-10-01 12:04:34	ga_s2bm_ard_3-2-1_49KHP_2023-10-01_final
2023-10-05 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2023-10-05_final
2023-10-31 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-31_final
2023-11-04 11:43:21	ga_s2bm_ard_3-2-1_50KRC_2023-11-04_final
2023-11-11 11:36:15	ga_s2bm_ard_3-2-1_51JUF_2023-11-11_final
2023-11-14 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2023-11-14_final
2023-12-30 12:03:57	ga_s2bm_ard_3-2-1_50KLA_2023-12-30_final
2024-03-03 11:45:57	ga_s2bm_ard_3-2-1_50JQM_2024-03-03_final
2024-03-03 11:46:10	ga_s2bm_ard_3-2-1_50JMM_2024-03-03_final
2024-03-03 11:46:59	ga_s2bm_ard_3-2-1_50HPH_2024-03-03_final
2024-03-12 12:14:23	ga_s2bm_ard_3-2-1_49KGP_2024-03-12_final
2024-03-29 12:04:42	ga_s2bm_ard_3-2-1_49JHN_2024-03-29_final
2024-04-29 11:36:28	ga_s2bm_ard_3-2-1_51HUE_2024-04-29_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