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
2017-08-27 11:40:44	ga_s2bm_ard_3-2-1_50HNH_2017-08-27_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50JLP_2017-09-22_final.stac-item
2017-11-22 11:30:28	ga_s2bm_ard_3-2-1_50JQN_2017-11-22_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_50KKA_2017-12-31_final.stac-item
2018-01-27 11:56:04	ga_s2bm_ard_3-2-1_50HMH_2018-01-27_final.stac-item
2018-04-24 11:41:02	ga_s2bm_ard_3-2-1_50JMM_2018-04-24_final.stac-item
2018-06-30 11:33:25	ga_s2bm_ard_3-2-1_50JQL_2018-06-30_final.stac-item
2018-07-10 11:30:50	ga_s2bm_ard_3-2-1_50HQJ_2018-07-10_final.stac-item
2018-08-05 11:52:56	ga_s2bm_ard_3-2-1_50JMT_2018-08-05_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JKS_2018-08-08_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50JPL_2018-09-11_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49JHN_2018-10-07_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGM_2018-10-20_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50KLU_2018-10-27_final.stac-item
2018-10-31 11:46:25	ga_s2bm_ard_3-2-1_50HMJ_2018-10-31_final.stac-item
2018-11-19 12:14:24	ga_s2bm_ard_3-2-1_49KGP_2018-11-19_final.stac-item
2018-12-10 11:45:59	ga_s2bm_ard_3-2-1_50JMM_2018-12-10_final.stac-item
2019-01-08 12:13:53	ga_s2bm_ard_3-2-1_50KKA_2019-01-08_final.stac-item
2019-02-27 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2019-02-27_final.stac-item
2019-03-16 12:05:13	ga_s2bm_ard_3-2-1_49JGL_2019-03-16_final.stac-item
2019-03-16 12:06:02	ga_s2bm_ard_3-2-1_50JLM_2019-03-16_final.stac-item
2019-03-26 12:04:29	ga_s2bm_ard_3-2-1_49KHP_2019-03-26_final.stac-item
2019-05-09 11:46:27	ga_s2bm_ard_3-2-1_50JPL_2019-05-09_final.stac-item
2019-05-22 11:56:27	ga_s2bm_ard_3-2-1_50JNL_2019-05-22_final.stac-item
2019-07-18 11:46:28	ga_s2bm_ard_3-2-1_50JPL_2019-07-18_final.stac-item
2019-09-19 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2019-09-19_final.stac-item
2019-10-15 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2019-10-15_final.stac-item
2019-11-11 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2019-11-11_final.stac-item
2019-11-24 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2019-11-24_final.stac-item
2020-01-07 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2020-01-07_final.stac-item
2020-01-10 12:04:19	ga_s2bm_ard_3-2-1_50KLU_2020-01-10_final.stac-item
2020-02-16 11:57:01	ga_s2bm_ard_3-2-1_50HMH_2020-02-16_final.stac-item
2020-04-09 12:05:40	ga_s2bm_ard_3-2-1_49JGJ_2020-04-09_final.stac-item
2020-04-16 11:56:26	ga_s2bm_ard_3-2-1_50HNK_2020-04-16_final.stac-item
2020-04-29 12:05:11	ga_s2bm_ard_3-2-1_49JGL_2020-04-29_final.stac-item
2020-06-12 11:45:20	ga_s2bm_ard_3-2-1_50JQQ_2020-06-12_final.stac-item
2020-07-05 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2020-07-05_final.stac-item
2020-08-01 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2020-08-01_final.stac-item
2020-08-31 11:47:10	ga_s2bm_ard_3-2-1_50HNH_2020-08-31_final.stac-item
2020-09-06 12:03:44	ga_s2bm_ard_3-2-1_50KLB_2020-09-06_final.stac-item
2020-10-07 11:36:41	ga_s2bm_ard_3-2-1_50HPK_2020-10-07_final.stac-item
2020-10-13 11:56:00	ga_s2bm_ard_3-2-1_50JLN_2020-10-13_final.stac-item
2020-10-30 11:46:40	ga_s2bm_ard_3-2-1_50HNK_2020-10-30_final.stac-item
2020-11-09 11:46:39	ga_s2bm_ard_3-2-1_50HNK_2020-11-09_final.stac-item
2020-11-15 12:04:32	ga_s2bm_ard_3-2-1_49KGP_2020-11-15_final.stac-item
2020-11-16 11:37:07	ga_s2bm_ard_3-2-1_50HPH_2020-11-16_final.stac-item
2021-01-01 11:54:32	ga_s2bm_ard_3-2-1_50JPT_2021-01-01_final.stac-item
2021-01-18 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2021-01-18_final.stac-item
2021-02-24 11:37:01	ga_s2bm_ard_3-2-1_50HQH_2021-02-24_final.stac-item
2021-03-12 11:55:56	ga_s2bm_ard_3-2-1_50JLN_2021-03-12_final.stac-item
2021-04-14 12:03:52	ga_s2bm_ard_3-2-1_50KLA_2021-04-14_final.stac-item
2021-05-08 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2021-05-08_final.stac-item
2021-05-25 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2021-05-25_final.stac-item
2021-06-10 11:53:52	ga_s2bm_ard_3-2-1_50KNA_2021-06-10_final.stac-item
2021-07-03 12:04:22	ga_s2bm_ard_3-2-1_49KHQ_2021-07-03_final.stac-item
2021-08-06 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2021-08-06_final.stac-item
2021-09-11 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2021-09-11_final.stac-item
2021-09-15 11:47:17	ga_s2bm_ard_3-2-1_50HNG_2021-09-15_final
2021-10-05 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2021-10-05_final.stac-item
2021-10-28 11:57:24	ga_s2bm_ard_3-2-1_50HLG_2021-10-28_final
2021-12-30 12:03:23	ga_s2bm_ard_3-2-1_50KMC_2021-12-30_final.stac-item
2022-02-02 11:46:42	ga_s2bm_ard_3-2-1_50HPJ_2022-02-02_final.stac-item
2022-02-12 11:47:04	ga_s2bm_ard_3-2-1_50HMH_2022-02-12_final.stac-item
2022-03-04 11:45:00	ga_s2bm_ard_3-2-1_50JQR_2022-03-04_final.stac-item
2022-04-12 12:13:51	ga_s2bm_ard_3-2-1_50KKA_2022-04-12_final.stac-item
2022-05-02 12:15:05	ga_s2bm_ard_3-2-1_49JGL_2022-05-02_final.stac-item
2022-06-01 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2022-06-01_final.stac-item
2022-08-24 11:56:30	ga_s2bm_ard_3-2-1_50HNK_2022-08-24_final.stac-item
2022-10-06 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2022-10-06_final.stac-item
2022-10-16 12:04:47	ga_s2bm_ard_3-2-1_49JGN_2022-10-16_final.stac-item
2022-11-06 11:36:18	ga_s2bm_ard_3-2-1_50JQL_2022-11-06_final.stac-item
2022-11-19 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2022-11-19_final.stac-item
2022-11-28 12:13:57	ga_s2bm_ard_3-2-1_49KGR_2022-11-28_final.stac-item
2022-12-25 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2022-12-25_final.stac-item
2023-01-04 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2023-01-04_final.stac-item
2023-01-04 12:04:26	ga_s2bm_ard_3-2-1_50KKU_2023-01-04_final.stac-item
2023-01-24 12:05:39	ga_s2bm_ard_3-2-1_50JKP_2023-01-24_final.stac-item
2023-02-13 12:03:43	ga_s2bm_ard_3-2-1_50KNA_2023-02-13_final
2023-02-23 12:04:10	ga_s2bm_ard_3-2-1_50KLV_2023-02-23_final
2023-03-05 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2023-03-05_final
2023-04-25 11:37:23	ga_s2bm_ard_3-2-1_50HPG_2023-04-25_final
2023-06-26 12:13:44	ga_s2bm_ard_3-2-1_50KKB_2023-06-26_final
2023-06-26 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2023-06-26_final
2023-07-06 12:15:16	ga_s2bm_ard_3-2-1_49JGL_2023-07-06_final
2023-07-17 11:46:43	ga_s2bm_ard_3-2-1_50HNK_2023-07-17_final
2023-08-25 12:13:59	ga_s2bm_ard_3-2-1_49KHR_2023-08-25_final
2023-10-01 12:05:25	ga_s2bm_ard_3-2-1_50JLQ_2023-10-01_final
2023-10-08 11:56:02	ga_s2bm_ard_3-2-1_50JLN_2023-10-08_final
2023-10-28 11:53:32	ga_s2bm_ard_3-2-1_50KMC_2023-10-28_final
2023-11-11 11:36:53	ga_s2bm_ard_3-2-1_50HPJ_2023-11-11_final
2023-12-07 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2023-12-07_final
2024-01-06 11:53:30	ga_s2bm_ard_3-2-1_50KMC_2024-01-06_final
2024-02-01 12:14:38	ga_s2bm_ard_3-2-1_49JGN_2024-02-01_final
2024-02-05 11:54:50	ga_s2bm_ard_3-2-1_50JNS_2024-02-05_final
2024-02-18 12:05:20	ga_s2bm_ard_3-2-1_49JGL_2024-02-18_final
2024-03-19 12:04:48	ga_s2bm_ard_3-2-1_50JMS_2024-03-19_final
2024-03-23 11:46:30	ga_s2bm_ard_3-2-1_50HQK_2024-03-23_final
2024-05-02 11:46:13	ga_s2bm_ard_3-2-1_50JMM_2024-05-02_final
2024-05-12 11:46:23	ga_s2bm_ard_3-2-1_50JNL_2024-05-12_final
2024-05-19 11:37:20	ga_s2bm_ard_3-2-1_50HPG_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

All years