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
2017-08-07 11:38:33	ga_s2bm_ard_3-2-1_51KVA_2017-08-07_final.stac-item
2017-08-07 11:45:07	ga_s2bm_ard_3-2-1_50HLH_2017-08-07_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HPK_2017-09-16_final.stac-item
2017-12-19 11:19:33	ga_s2bm_ard_3-2-1_51KZP_2017-12-19_final.stac-item
2018-01-18 11:16:52	ga_s2bm_ard_3-2-1_51KYS_2018-01-18_final.stac-item
2018-02-23 11:40:38	ga_s2bm_ard_3-2-1_51KVB_2018-02-23_final.stac-item
2018-03-04 12:13:52	ga_s2bm_ard_3-2-1_49JFM_2018-03-04_final.stac-item
2018-03-22 11:29:32	ga_s2bm_ard_3-2-1_51KXT_2018-03-22_final.stac-item
2018-05-05 11:13:23	ga_s2bm_ard_3-2-1_51JXH_2018-05-05_final.stac-item
2018-06-13 11:43:22	ga_s2bm_ard_3-2-1_50JQQ_2018-06-13_final.stac-item
2018-07-03 11:44:57	ga_s2bm_ard_3-2-1_50HPK_2018-07-03_final.stac-item
2018-07-16 11:52:50	ga_s2bm_ard_3-2-1_50JKN_2018-07-16_final.stac-item
2018-10-08 11:30:50	ga_s2bm_ard_3-2-1_51KVV_2018-10-08_final.stac-item
2018-12-17 11:33:57	ga_s2bm_ard_3-2-1_51KUQ_2018-12-17_final.stac-item
2019-02-28 11:42:29	ga_s2bm_ard_3-2-1_51KUA_2019-02-28_final.stac-item
2019-05-29 11:46:57	ga_s2bm_ard_3-2-1_50HQJ_2019-05-29_final.stac-item
2019-06-22 11:25:46	ga_s2bm_ard_3-2-1_51JXH_2019-06-22_final.stac-item
2019-07-02 11:23:43	ga_s2bm_ard_3-2-1_52KBA_2019-07-02_final.stac-item
2019-07-12 11:26:45	ga_s2bm_ard_3-2-1_51HXD_2019-07-12_final.stac-item
2019-08-04 11:32:04	ga_s2bm_ard_3-2-1_51LXC_2019-08-04_final.stac-item
2019-08-08 11:13:33	ga_s2bm_ard_3-2-1_52KBB_2019-08-08_final.stac-item
2019-08-21 11:25:30	ga_s2bm_ard_3-2-1_51JXJ_2019-08-21_final.stac-item
2019-08-28 11:13:30	ga_s2bm_ard_3-2-1_52KBB_2019-08-28_final.stac-item
2019-09-10 11:23:26	ga_s2bm_ard_3-2-1_51KZS_2019-09-10_final.stac-item
2019-11-29 11:23:31	ga_s2bm_ard_3-2-1_51KZR_2019-11-29_final.stac-item
2019-12-28 11:54:14	ga_s2bm_ard_3-2-1_50KPU_2019-12-28_final.stac-item
2020-06-02 11:46:14	ga_s2bm_ard_3-2-1_50JMM_2020-06-02_final.stac-item
2020-06-16 11:25:41	ga_s2bm_ard_3-2-1_51JXH_2020-06-16_final.stac-item
2020-06-25 11:53:13	ga_s2bm_ard_3-2-1_50KRC_2020-06-25_final.stac-item
2020-06-26 11:23:37	ga_s2bm_ard_3-2-1_52KBA_2020-06-26_final.stac-item
2020-09-04 11:23:03	ga_s2bm_ard_3-2-1_51KXU_2020-09-04_final.stac-item
2020-10-04 11:23:20	ga_s2bm_ard_3-2-1_52KCB_2020-10-04_final.stac-item
2020-10-10 11:43:20	ga_s2bm_ard_3-2-1_51KVT_2020-10-10_final.stac-item
2020-11-05 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2020-11-05_final.stac-item
2020-11-05 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2020-11-05_final.stac-item
2020-12-10 11:16:17	ga_s2bm_ard_3-2-1_52HBK_2020-12-10_final.stac-item
2020-12-29 11:42:11	ga_s2bm_ard_3-2-1_51KVB_2020-12-29_final.stac-item
2021-01-11 11:53:17	ga_s2bm_ard_3-2-1_50KQC_2021-01-11_final.stac-item
2021-02-14 11:32:35	ga_s2bm_ard_3-2-1_51KYV_2021-02-14_final.stac-item
2021-03-26 11:34:48	ga_s2bm_ard_3-2-1_51JTM_2021-03-26_final.stac-item
2021-03-26 11:37:20	ga_s2bm_ard_3-2-1_50HPG_2021-03-26_final
2021-03-29 11:43:17	ga_s2bm_ard_3-2-1_50KRC_2021-03-29_final.stac-item
2021-04-17 12:13:50	ga_s2bm_ard_3-2-1_49KHR_2021-04-17_final.stac-item
2021-06-26 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2021-06-26_final.stac-item
2021-07-17 11:43:06	ga_s2bm_ard_3-2-1_50KRD_2021-07-17_final.stac-item
2021-08-19 11:56:25	ga_s2bm_ard_3-2-1_50JLL_2021-08-19_final.stac-item
2021-09-25 11:42:26	ga_s2bm_ard_3-2-1_51KVA_2021-09-25_final.stac-item
2021-10-02 11:32:47	ga_s2bm_ard_3-2-1_51KWV_2021-10-02_final.stac-item
2021-11-22 11:04:40	ga_s2bm_ard_3-2-1_52JFR_2021-11-22_final.stac-item
2022-01-19 12:04:23	ga_s2bm_ard_3-2-1_50KKU_2022-01-19_final.stac-item
2022-02-12 11:42:07	ga_s2bm_ard_3-2-1_51KVB_2022-02-12_final.stac-item
2022-02-18 12:04:54	ga_s2bm_ard_3-2-1_49JGM_2022-02-18_final.stac-item
2022-05-03 11:46:10	ga_s2bm_ard_3-2-1_50JQL_2022-05-03_final.stac-item
2022-05-10 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2022-05-10_final.stac-item
2022-05-27 11:22:52	ga_s2bm_ard_3-2-1_51KZU_2022-05-27_final.stac-item
2022-06-12 11:45:59	ga_s2bm_ard_3-2-1_51JTG_2022-06-12_final.stac-item
2022-07-08 12:04:36	ga_s2bm_ard_3-2-1_49KGP_2022-07-08_final.stac-item
2022-07-09 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2022-07-09_final.stac-item
2022-08-04 11:53:15	ga_s2bm_ard_3-2-1_50KRC_2022-08-04_final.stac-item
2022-08-21 11:44:17	ga_s2bm_ard_3-2-1_51KTP_2022-08-21_final.stac-item
2022-09-07 11:32:52	ga_s2bm_ard_3-2-1_51KYU_2022-09-07_final.stac-item
2022-09-17 11:32:02	ga_s2bm_ard_3-2-1_51LWC_2022-09-17_final.stac-item
2022-11-03 11:23:19	ga_s2bm_ard_3-2-1_51KZS_2022-11-03_final.stac-item
2022-12-16 11:32:51	ga_s2bm_ard_3-2-1_51KVV_2022-12-16_final.stac-item
2022-12-29 11:46:14	ga_s2bm_ard_3-2-1_50JQL_2022-12-29_final.stac-item
2023-01-14 12:04:35	ga_s2bm_ard_3-2-1_50JLT_2023-01-14_final.stac-item
2023-03-29 11:46:00	ga_s2bm_ard_3-2-1_51JTG_2023-03-29_final
2023-05-05 11:32:53	ga_s2bm_ard_3-2-1_51KYU_2023-05-05_final
2023-05-24 12:03:49	ga_s2bm_ard_3-2-1_50KKB_2023-05-24_final
2023-06-13 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-06-13_final
2023-07-01 11:24:13	ga_s2bm_ard_3-2-1_51KYP_2023-07-01_final
2023-07-07 11:46:39	ga_s2bm_ard_3-2-1_50HPK_2023-07-07_final
2023-08-10 11:22:58	ga_s2bm_ard_3-2-1_51KZU_2023-08-10_final
2023-08-23 11:35:20	ga_s2bm_ard_3-2-1_51JUK_2023-08-23_final
2023-08-30 11:23:44	ga_s2bm_ard_3-2-1_51KYR_2023-08-30_final
2023-09-02 11:32:51	ga_s2bm_ard_3-2-1_51KVV_2023-09-02_final
2023-09-25 11:41:36	ga_s2bm_ard_3-2-1_51LUE_2023-09-25_final
2023-10-02 11:36:12	ga_s2bm_ard_3-2-1_51JVF_2023-10-02_final
2023-10-22 11:32:45	ga_s2bm_ard_3-2-1_51KWV_2023-10-22_final
2023-11-10 12:05:17	ga_s2bm_ard_3-2-1_49JGL_2023-11-10_final
2023-11-18 11:23:04	ga_s2bm_ard_3-2-1_52KBC_2023-11-18_final
2023-11-25 11:13:50	ga_s2bm_ard_3-2-1_52KBV_2023-11-25_final
2023-12-03 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2023-12-03_final
2023-12-28 11:23:37	ga_s2bm_ard_3-2-1_51KZR_2023-12-28_final
2023-12-30 12:04:00	ga_s2bm_ard_3-2-1_50KKA_2023-12-30_final
2024-01-19 12:03:40	ga_s2bm_ard_3-2-1_50KLB_2024-01-19_final
2024-01-20 11:37:00	ga_s2bm_ard_3-2-1_51HTC_2024-01-20_final
2024-01-23 11:43:35	ga_s2bm_ard_3-2-1_50KQB_2024-01-23_final
2024-01-24 11:13:38	ga_s2bm_ard_3-2-1_52KBA_2024-01-24_final
2024-01-30 11:32:09	ga_s2bm_ard_3-2-1_51KXB_2024-01-30_final
2024-02-26 11:23:49	ga_s2bm_ard_3-2-1_52KBV_2024-02-26_final
2024-02-28 12:06:03	ga_s2bm_ard_3-2-1_50JLM_2024-02-28_final
2024-03-01 11:04:12	ga_s2bm_ard_3-2-1_52JFT_2024-03-01_final
2024-03-12 12:13:36	ga_s2bm_ard_3-2-1_49KHS_2024-03-12_final
2024-03-21 11:04:43	ga_s2bm_ard_3-2-1_52JFR_2024-03-21_final
2024-03-23 11:41:56	ga_s2bm_ard_3-2-1_51LWC_2024-03-23_final
2024-04-06 11:24:17	ga_s2bm_ard_3-2-1_51JZN_2024-04-06_final
2024-04-13 11:13:40	ga_s2bm_ard_3-2-1_52KBA_2024-04-13_final
2024-05-12 11:41:56	ga_s2bm_ard_3-2-1_51LWC_2024-05-12_final
2024-05-19 11:34:01	ga_s2bm_ard_3-2-1_51KUQ_2024-05-19_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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