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
2017-08-28 11:11:56	ga_s2bm_ard_3-2-1_51JZM_2017-08-28_final.stac-item
2017-12-06 11:11:50	ga_s2bm_ard_3-2-1_51JYF_2017-12-06_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50JMS_2017-12-18_final.stac-item
2017-12-18 11:50:34	ga_s2bm_ard_3-2-1_50KNU_2017-12-18_final.stac-item
2018-03-25 11:44:34	ga_s2bm_ard_3-2-1_50HPK_2018-03-25_final.stac-item
2018-04-05 11:11:18	ga_s2bm_ard_3-2-1_51JYF_2018-04-05_final.stac-item
2018-06-24 11:09:06	ga_s2bm_ard_3-2-1_51JZM_2018-06-24_final.stac-item
2018-10-02 11:12:46	ga_s2bm_ard_3-2-1_51HXE_2018-10-02_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JMT_2018-10-24_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50KNU_2018-10-24_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50JLN_2018-11-03_final.stac-item
2018-11-23 11:54:19	ga_s2bm_ard_3-2-1_50KNU_2018-11-23_final.stac-item
2019-01-15 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2019-01-15_final.stac-item
2019-01-15 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2019-01-15_final.stac-item
2019-02-24 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2019-02-24_final.stac-item
2019-03-01 11:14:36	ga_s2bm_ard_3-2-1_51JZM_2019-03-01_final.stac-item
2019-03-27 11:34:47	ga_s2bm_ard_3-2-1_51JUM_2019-03-27_final.stac-item
2019-04-12 11:54:56	ga_s2bm_ard_3-2-1_50JNS_2019-04-12_final.stac-item
2019-05-16 11:36:55	ga_s2bm_ard_3-2-1_51HTD_2019-05-16_final.stac-item
2019-07-18 11:44:28	ga_s2bm_ard_3-2-1_50KQU_2019-07-18_final.stac-item
2019-07-24 12:04:22	ga_s2bm_ard_3-2-1_50KKV_2019-07-24_final.stac-item
2019-07-25 11:34:55	ga_s2bm_ard_3-2-1_51JUM_2019-07-25_final.stac-item
2019-09-16 11:44:02	ga_s2bm_ard_3-2-1_50KRV_2019-09-16_final.stac-item
2019-09-26 11:44:16	ga_s2bm_ard_3-2-1_50KRU_2019-09-26_final.stac-item
2019-10-06 11:44:17	ga_s2bm_ard_3-2-1_51KTP_2019-10-06_final.stac-item
2019-10-30 11:24:27	ga_s2bm_ard_3-2-1_51JXN_2019-10-30_final.stac-item
2019-12-22 11:34:24	ga_s2bm_ard_3-2-1_51JVN_2019-12-22_final.stac-item
2019-12-25 11:45:27	ga_s2bm_ard_3-2-1_50JQP_2019-12-25_final.stac-item
2020-01-01 11:34:56	ga_s2bm_ard_3-2-1_51JUL_2020-01-01_final.stac-item
2020-01-08 11:25:33	ga_s2bm_ard_3-2-1_51JXH_2020-01-08_final.stac-item
2020-02-04 11:16:01	ga_s2bm_ard_3-2-1_51JYF_2020-02-04_final.stac-item
2020-02-27 11:24:34	ga_s2bm_ard_3-2-1_51JYM_2020-02-27_final.stac-item
2020-05-06 11:54:38	ga_s2bm_ard_3-2-1_50JMT_2020-05-06_final.stac-item
2020-05-09 12:04:11	ga_s2bm_ard_3-2-1_50KKV_2020-05-09_final.stac-item
2020-05-09 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2020-05-09_final.stac-item
2020-06-06 11:24:28	ga_s2bm_ard_3-2-1_51JXN_2020-06-06_final.stac-item
2020-06-22 11:44:19	ga_s2bm_ard_3-2-1_51KTP_2020-06-22_final.stac-item
2020-07-05 11:54:25	ga_s2bm_ard_3-2-1_50KNU_2020-07-05_final.stac-item
2020-07-08 12:04:27	ga_s2bm_ard_3-2-1_50KLU_2020-07-08_final.stac-item
2020-07-15 11:52:50	ga_s2bm_ard_3-2-1_50KQE_2020-07-15_final
2020-08-15 11:24:30	ga_s2bm_ard_3-2-1_51JXN_2020-08-15_final.stac-item
2020-09-10 11:44:19	ga_s2bm_ard_3-2-1_50KRU_2020-09-10_final.stac-item
2020-09-23 11:55:12	ga_s2bm_ard_3-2-1_50JMR_2020-09-23_final.stac-item
2020-10-07 11:36:21	ga_s2bm_ard_3-2-1_51JTF_2020-10-07_final.stac-item
2020-10-21 11:14:41	ga_s2bm_ard_3-2-1_51JZM_2020-10-21_final.stac-item
2020-11-19 11:43:34	ga_s2bm_ard_3-2-1_50KRB_2020-11-19_final.stac-item
2020-11-22 11:54:52	ga_s2bm_ard_3-2-1_50JNS_2020-11-22_final.stac-item
2020-12-03 11:24:54	ga_s2bm_ard_3-2-1_51JXL_2020-12-03_final.stac-item
2020-12-22 11:54:34	ga_s2bm_ard_3-2-1_50JNT_2020-12-22_final.stac-item
2021-04-12 11:25:53	ga_s2bm_ard_3-2-1_51JWG_2021-04-12_final.stac-item
2021-04-12 11:26:08	ga_s2bm_ard_3-2-1_51JWF_2021-04-12_final.stac-item
2021-07-20 11:52:51	ga_s2bm_ard_3-2-1_50KQE_2021-07-20_final
2021-10-25 11:44:21	ga_s2bm_ard_3-2-1_50KQU_2021-10-25_final.stac-item
2021-11-07 11:54:23	ga_s2bm_ard_3-2-1_50KNU_2021-11-07_final.stac-item
2022-01-03 11:43:29	ga_s2bm_ard_3-2-1_50KRB_2022-01-03_final.stac-item
2022-01-03 11:45:14	ga_s2bm_ard_3-2-1_50JQQ_2022-01-03_final.stac-item
2022-01-04 11:16:04	ga_s2bm_ard_3-2-1_51JYF_2022-01-04_final.stac-item
2022-01-13 11:43:29	ga_s2bm_ard_3-2-1_50KRB_2022-01-13_final.stac-item
2022-01-16 11:54:33	ga_s2bm_ard_3-2-1_50JNT_2022-01-16_final.stac-item
2022-02-03 11:16:02	ga_s2bm_ard_3-2-1_51JYF_2022-02-03_final.stac-item
2022-03-28 11:26:12	ga_s2bm_ard_3-2-1_51JVF_2022-03-28_final.stac-item
2022-05-16 11:52:33	ga_s2bm_ard_3-2-1_50KQF_2022-05-16_final
2022-07-13 11:16:30	ga_s2bm_ard_3-2-1_51HXE_2022-07-13_final.stac-item
2022-08-22 11:15:55	ga_s2bm_ard_3-2-1_51JYG_2022-08-22_final.stac-item
2022-08-31 11:43:34	ga_s2bm_ard_3-2-1_50KRB_2022-08-31_final.stac-item
2022-12-02 11:54:21	ga_s2bm_ard_3-2-1_50KNU_2022-12-02_final.stac-item
2023-01-01 11:53:49	ga_s2bm_ard_3-2-1_50KPA_2023-01-01_final.stac-item
2023-01-09 11:16:05	ga_s2bm_ard_3-2-1_51JYF_2023-01-09_final.stac-item
2023-02-17 11:45:19	ga_s2bm_ard_3-2-1_50JPQ_2023-02-17_final
2023-04-19 11:15:55	ga_s2bm_ard_3-2-1_51JYG_2023-04-19_final
2023-04-29 11:15:55	ga_s2bm_ard_3-2-1_51JYG_2023-04-29_final
2023-05-11 11:52:04	ga_s2bm_ard_3-2-1_50LRH_2023-05-11_nrt
2023-05-24 12:04:47	ga_s2bm_ard_3-2-1_50JKT_2023-05-24_final
2023-05-31 11:51:08	ga_s2bm_ard_3-2-1_50LRM_2023-05-31_nrt
2023-06-18 11:15:58	ga_s2bm_ard_3-2-1_51JYG_2023-06-18_final
2023-06-28 11:15:58	ga_s2bm_ard_3-2-1_51JYG_2023-06-28_final
2023-08-20 11:25:33	ga_s2bm_ard_3-2-1_51JWJ_2023-08-20_final
2023-08-25 12:13:48	ga_s2bm_ard_3-2-1_49KGS_2023-08-25_nrt
2023-08-29 11:54:09	ga_s2bm_ard_3-2-1_50KPV_2023-08-29_final
2023-09-18 11:54:26	ga_s2bm_ard_3-2-1_50KNU_2023-09-18_final
2023-09-25 11:43:51	ga_s2bm_ard_3-2-1_50KRA_2023-09-25_final
2023-10-31 12:04:15	ga_s2bm_ard_3-2-1_50KKV_2023-10-31_final
2023-11-04 11:44:51	ga_s2bm_ard_3-2-1_50JQS_2023-11-04_final
2023-11-08 11:24:43	ga_s2bm_ard_3-2-1_51JXM_2023-11-08_final
2023-11-08 11:25:26	ga_s2bm_ard_3-2-1_51JXJ_2023-11-08_final
2023-11-10 12:04:30	ga_s2bm_ard_3-2-1_49KHP_2023-11-10_final
2023-11-30 12:04:39	ga_s2bm_ard_3-2-1_50JKT_2023-11-30_final
2023-12-15 11:14:36	ga_s2bm_ard_3-2-1_51JZM_2023-12-15_final
2023-12-17 11:54:51	ga_s2bm_ard_3-2-1_50JNS_2023-12-17_final
2023-12-17 11:54:54	ga_s2bm_ard_3-2-1_50JMS_2023-12-17_final
2023-12-21 11:37:18	ga_s2bm_ard_3-2-1_50HQG_2023-12-21_final
2023-12-24 11:45:05	ga_s2bm_ard_3-2-1_50JQR_2023-12-24_final
2023-12-24 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2023-12-24_final
2023-12-30 12:04:40	ga_s2bm_ard_3-2-1_50JLT_2023-12-30_final
2024-01-03 11:45:22	ga_s2bm_ard_3-2-1_50JPQ_2024-01-03_final
2024-01-09 12:01:22	ga_s2bm_ard_3-2-1_50LNL_2024-01-09_nrt
2024-02-08 12:04:10	ga_s2bm_ard_3-2-1_50KLV_2024-02-08_final
2024-02-08 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2024-02-08_final
2024-02-18 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2024-02-18_final
2024-02-18 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2024-02-18_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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