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
2017-11-20 10:47:12	ga_s2bm_ard_3-2-1_53LMG_2017-11-20_final.stac-item
2017-12-19 11:25:05	ga_s2bm_ard_3-2-1_51HUC_2017-12-19_final.stac-item
2018-04-18 11:23:34	ga_s2bm_ard_3-2-1_51HVC_2018-04-18_final.stac-item
2018-07-23 11:40:57	ga_s2bm_ard_3-2-1_51KUV_2018-07-23_final.stac-item
2018-07-27 11:23:26	ga_s2bm_ard_3-2-1_51HXD_2018-07-27_final.stac-item
2018-08-31 10:30:56	ga_s2bm_ard_3-2-1_53HNB_2018-08-31_final.stac-item
2018-11-06 10:24:16	ga_s2bm_ard_3-2-1_53JRM_2018-11-06_final.stac-item
2018-11-19 10:32:59	ga_s2bm_ard_3-2-1_53KRS_2018-11-19_final.stac-item
2018-11-19 10:34:15	ga_s2bm_ard_3-2-1_53JQM_2018-11-19_final.stac-item
2018-11-27 11:33:12	ga_s2bm_ard_3-2-1_51KVT_2018-11-27_final.stac-item
2018-12-14 11:23:22	ga_s2bm_ard_3-2-1_51KXS_2018-12-14_final.stac-item
2018-12-16 12:04:25	ga_s2bm_ard_3-2-1_49KGP_2018-12-16_final.stac-item
2019-01-04 10:51:20	ga_s2bm_ard_3-2-1_53LND_2019-01-04_final.stac-item
2019-01-10 11:16:35	ga_s2bm_ard_3-2-1_51HYD_2019-01-10_final.stac-item
2019-01-29 11:42:46	ga_s2bm_ard_3-2-1_51KUV_2019-01-29_final.stac-item
2019-02-07 10:34:00	ga_s2bm_ard_3-2-1_53JRN_2019-02-07_final.stac-item
2019-02-15 11:33:36	ga_s2bm_ard_3-2-1_51KVR_2019-02-15_final.stac-item
2019-03-06 10:26:30	ga_s2bm_ard_3-2-1_53HQC_2019-03-06_final.stac-item
2019-03-11 11:13:11	ga_s2bm_ard_3-2-1_52KCB_2019-03-11_final.stac-item
2019-04-01 10:41:11	ga_s2bm_ard_3-2-1_53LPE_2019-04-01_final.stac-item
2019-04-15 12:03:29	ga_s2bm_ard_3-2-1_50KMC_2019-04-15_final.stac-item
2019-05-11 10:44:29	ga_s2bm_ard_3-2-1_53JNM_2019-05-11_final.stac-item
2019-08-06 10:34:40	ga_s2bm_ard_3-2-1_53JQL_2019-08-06_final.stac-item
2019-10-02 10:27:05	ga_s2bm_ard_3-2-1_53HPA_2019-10-02_final.stac-item
2019-11-19 11:23:26	ga_s2bm_ard_3-2-1_51KXS_2019-11-19_final.stac-item
2019-12-20 10:55:33	ga_s2bm_ard_3-2-1_52JGM_2019-12-20_final.stac-item
2020-01-01 11:33:25	ga_s2bm_ard_3-2-1_51KVS_2020-01-01_final.stac-item
2020-01-13 10:34:20	ga_s2bm_ard_3-2-1_53JNM_2020-01-13_final.stac-item
2020-01-14 11:43:12	ga_s2bm_ard_3-2-1_51KTT_2020-01-14_final.stac-item
2020-01-14 11:43:19	ga_s2bm_ard_3-2-1_51KVS_2020-01-14_final.stac-item
2020-01-25 11:10:36	ga_s2bm_ard_3-2-1_52LGM_2020-01-25_final.stac-item
2020-03-02 11:01:49	ga_s2bm_ard_3-2-1_53KLB_2020-03-02_final.stac-item
2020-03-10 12:03:42	ga_s2bm_ard_3-2-1_50KKB_2020-03-10_final.stac-item
2020-04-06 11:53:14	ga_s2bm_ard_3-2-1_50KQC_2020-04-06_final.stac-item
2020-04-07 11:23:47	ga_s2bm_ard_3-2-1_51KZQ_2020-04-07_final.stac-item
2020-04-13 11:46:39	ga_s2bm_ard_3-2-1_50HQJ_2020-04-13_final.stac-item
2020-04-24 11:10:27	ga_s2bm_ard_3-2-1_52LFN_2020-04-24_final
2020-05-24 11:15:54	ga_s2bm_ard_3-2-1_51JYG_2020-05-24_final.stac-item
2020-06-12 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2020-06-12_final.stac-item
2020-10-03 11:52:23	ga_s2bm_ard_3-2-1_50KQG_2020-10-03_final
2020-10-04 11:24:44	ga_s2bm_ard_3-2-1_51JXM_2020-10-04_final.stac-item
2020-10-19 10:34:51	ga_s2bm_ard_3-2-1_53JQK_2020-10-19_final.stac-item
2020-10-29 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2020-10-29_final.stac-item
2020-10-30 11:43:28	ga_s2bm_ard_3-2-1_51KVS_2020-10-30_final.stac-item
2020-11-06 11:33:47	ga_s2bm_ard_3-2-1_51KVR_2020-11-06_final.stac-item
2020-11-20 11:13:30	ga_s2bm_ard_3-2-1_52KEA_2020-11-20_final.stac-item
2020-12-07 11:02:38	ga_s2bm_ard_3-2-1_53KKU_2020-12-07_final.stac-item
2021-01-15 11:33:30	ga_s2bm_ard_3-2-1_51KVS_2021-01-15_final.stac-item
2021-01-24 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2021-01-24_final.stac-item
2021-02-05 11:00:39	ga_s2bm_ard_3-2-1_53LLG_2021-02-05_final.stac-item
2021-02-17 11:43:22	ga_s2bm_ard_3-2-1_51KVS_2021-02-17_final.stac-item
2021-03-17 11:00:44	ga_s2bm_ard_3-2-1_52LHM_2021-03-17_final.stac-item
2021-03-24 10:52:20	ga_s2bm_ard_3-2-1_53KLV_2021-03-24_final.stac-item
2021-04-02 11:23:52	ga_s2bm_ard_3-2-1_51KYQ_2021-04-02_final.stac-item
2021-04-05 11:31:16	ga_s2bm_ard_3-2-1_52LBK_2021-04-05_final.stac-item
2021-04-20 10:43:47	ga_s2bm_ard_3-2-1_53KNP_2021-04-20_final.stac-item
2021-06-18 11:11:05	ga_s2bm_ard_3-2-1_52LEL_2021-06-18_final
2021-06-19 10:42:22	ga_s2bm_ard_3-2-1_53KPV_2021-06-19_final.stac-item
2021-07-06 10:35:03	ga_s2bm_ard_3-2-1_53JQJ_2021-07-06_final.stac-item
2021-09-12 11:33:41	ga_s2bm_ard_3-2-1_51KVR_2021-09-12_final.stac-item
2021-09-25 11:41:54	ga_s2bm_ard_3-2-1_51LWC_2021-09-25_final.stac-item
2021-10-24 10:35:03	ga_s2bm_ard_3-2-1_53JQJ_2021-10-24_final.stac-item
2021-10-31 10:27:02	ga_s2bm_ard_3-2-1_53HQA_2021-10-31_final.stac-item
2021-11-25 11:10:37	ga_s2bm_ard_3-2-1_52LGM_2021-11-25_final.stac-item
2022-01-01 11:00:41	ga_s2bm_ard_3-2-1_52LHM_2022-01-01_final.stac-item
2022-02-04 10:44:01	ga_s2bm_ard_3-2-1_53JNN_2022-02-04_final.stac-item
2022-04-02 10:33:42	ga_s2bm_ard_3-2-1_53KRP_2022-04-02_final.stac-item
2022-04-02 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2022-04-02_final.stac-item
2022-05-19 10:26:53	ga_s2bm_ard_3-2-1_53HNB_2022-05-19_final.stac-item
2022-06-04 10:45:58	ga_s2bm_ard_3-2-1_53JKF_2022-06-04_final.stac-item
2022-06-22 11:42:50	ga_s2bm_ard_3-2-1_51KUV_2022-06-22_final.stac-item
2022-06-28 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2022-06-28_final.stac-item
2022-07-15 11:53:15	ga_s2bm_ard_3-2-1_50KRC_2022-07-15_final.stac-item
2022-07-18 10:26:41	ga_s2bm_ard_3-2-1_53HPC_2022-07-18_final.stac-item
2022-10-26 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2022-10-26_final.stac-item
2022-11-08 10:36:05	ga_s2bm_ard_3-2-1_53HNE_2022-11-08_final.stac-item
2022-11-10 11:13:32	ga_s2bm_ard_3-2-1_52KDA_2022-11-10_final.stac-item
2022-11-28 10:34:03	ga_s2bm_ard_3-2-1_53JQN_2022-11-28_final.stac-item
2022-12-16 11:33:22	ga_s2bm_ard_3-2-1_51KXS_2022-12-16_final.stac-item
2023-01-15 11:32:25	ga_s2bm_ard_3-2-1_51KWA_2023-01-15_final.stac-item
2023-01-15 11:33:38	ga_s2bm_ard_3-2-1_51KWR_2023-01-15_final.stac-item
2023-01-16 11:00:25	ga_s2bm_ard_3-2-1_53LKH_2023-01-16_final.stac-item
2023-02-14 11:36:25	ga_s2bm_ard_3-2-1_50JPL_2023-02-14_final
2023-03-09 11:41:37	ga_s2bm_ard_3-2-1_51LUE_2023-03-09_final
2023-03-28 10:33:48	ga_s2bm_ard_3-2-1_53KRP_2023-03-28_final
2023-04-12 11:22:53	ga_s2bm_ard_3-2-1_52KBD_2023-04-12_final
2023-04-17 10:34:27	ga_s2bm_ard_3-2-1_53JNM_2023-04-17_final
2023-05-14 10:26:36	ga_s2bm_ard_3-2-1_53HQC_2023-05-14_final
2023-07-04 11:33:18	ga_s2bm_ard_3-2-1_51KWT_2023-07-04_final
2023-07-07 11:41:03	ga_s2bm_ard_3-2-1_51LWG_2023-07-07_final
2023-08-15 10:34:20	ga_s2bm_ard_3-2-1_53JRM_2023-08-15_final
2023-09-01 10:27:06	ga_s2bm_ard_3-2-1_53HQA_2023-09-01_final
2023-09-04 10:34:30	ga_s2bm_ard_3-2-1_53JNM_2023-09-04_final
2023-09-24 10:34:22	ga_s2bm_ard_3-2-1_53JQM_2023-09-24_final
2023-11-11 11:33:46	ga_s2bm_ard_3-2-1_51KVR_2023-11-11_final
2023-11-13 10:33:44	ga_s2bm_ard_3-2-1_53KQQ_2023-11-13_final
2024-01-13 11:42:44	ga_s2bm_ard_3-2-1_51KUV_2024-01-13_final
2024-02-29 11:32:18	ga_s2bm_ard_3-2-1_51KVB_2024-02-29_final
2024-03-24 11:10:44	ga_s2bm_ard_3-2-1_52LGM_2024-03-24_final
2024-04-17 10:50:39	ga_s2bm_ard_3-2-1_53LNG_2024-04-17_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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