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
2017-11-08 11:53:07	ga_s2bm_ard_3-2-1_50HLJ_2017-11-08_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_49JGM_2017-11-11_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50JLM_2017-11-18_final.stac-item
2017-12-25 11:40:37	ga_s2bm_ard_3-2-1_50JQS_2017-12-25_final.stac-item
2017-12-31 12:02:39	ga_s2bm_ard_3-2-1_50KMC_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
2018-03-08 11:51:37	ga_s2bm_ard_3-2-1_50HLH_2018-03-08_final.stac-item
2018-03-18 11:50:35	ga_s2bm_ard_3-2-1_50HLJ_2018-03-18_final.stac-item
2018-04-01 11:35:24	ga_s2bm_ard_3-2-1_50HPH_2018-04-01_final.stac-item
2018-04-23 12:13:20	ga_s2bm_ard_3-2-1_49KGQ_2018-04-23_final.stac-item
2018-06-03 11:46:44	ga_s2bm_ard_3-2-1_50HPH_2018-06-03_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50HPK_2018-06-23_final.stac-item
2018-07-16 11:52:50	ga_s2bm_ard_3-2-1_50JNQ_2018-07-16_final.stac-item
2018-08-15 11:54:27	ga_s2bm_ard_3-2-1_50HLK_2018-08-15_final.stac-item
2018-09-11 11:41:45	ga_s2bm_ard_3-2-1_50HMH_2018-09-11_final.stac-item
2019-01-12 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2019-01-12_final.stac-item
2019-02-11 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2019-02-11_final.stac-item
2019-03-19 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2019-03-19_final.stac-item
2019-03-26 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2019-03-26_final.stac-item
2019-04-15 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2019-04-15_final.stac-item
2019-05-12 11:56:19	ga_s2bm_ard_3-2-1_50JLM_2019-05-12_final.stac-item
2019-07-11 11:55:36	ga_s2bm_ard_3-2-1_50JLQ_2019-07-11_final.stac-item
2019-07-15 11:36:47	ga_s2bm_ard_3-2-1_50HPK_2019-07-15_final.stac-item
2019-07-24 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-07-24_final.stac-item
2019-09-06 11:46:54	ga_s2bm_ard_3-2-1_50HNJ_2019-09-06_final.stac-item
2019-10-12 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2019-10-12_final.stac-item
2019-11-25 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2019-11-25_final.stac-item
2020-03-30 12:05:49	ga_s2bm_ard_3-2-1_50JLN_2020-03-30_final.stac-item
2020-04-20 11:37:02	ga_s2bm_ard_3-2-1_50HPH_2020-04-20_final.stac-item
2020-04-23 11:46:17	ga_s2bm_ard_3-2-1_50JNL_2020-04-23_final.stac-item
2020-05-09 12:04:55	ga_s2bm_ard_3-2-1_50JKS_2020-05-09_final.stac-item
2020-06-12 11:46:43	ga_s2bm_ard_3-2-1_50HMK_2020-06-12_final.stac-item
2020-06-15 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2020-06-15_final.stac-item
2020-08-01 11:47:09	ga_s2bm_ard_3-2-1_50HNH_2020-08-01_final.stac-item
2020-08-14 11:56:03	ga_s2bm_ard_3-2-1_50JKN_2020-08-14_final.stac-item
2020-10-26 12:04:04	ga_s2bm_ard_3-2-1_50KKA_2020-10-26_final.stac-item
2020-11-25 12:04:46	ga_s2bm_ard_3-2-1_49JGN_2020-11-25_final.stac-item
2020-12-05 12:03:22	ga_s2bm_ard_3-2-1_50KMC_2020-12-05_final.stac-item
2020-12-08 12:13:52	ga_s2bm_ard_3-2-1_50KKA_2020-12-08_final.stac-item
2021-02-07 11:45:24	ga_s2bm_ard_3-2-1_50JNQ_2021-02-07_final.stac-item
2021-02-10 11:56:10	ga_s2bm_ard_3-2-1_50JLM_2021-02-10_final.stac-item
2021-02-10 11:56:28	ga_s2bm_ard_3-2-1_50HNK_2021-02-10_final.stac-item
2021-03-09 11:46:47	ga_s2bm_ard_3-2-1_50HPJ_2021-03-09_final.stac-item
2021-03-18 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2021-03-18_final.stac-item
2021-03-25 12:03:47	ga_s2bm_ard_3-2-1_50KKB_2021-03-25_final.stac-item
2021-04-04 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2021-04-04_final.stac-item
2021-04-14 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2021-04-14_final.stac-item
2021-05-24 12:05:23	ga_s2bm_ard_3-2-1_50JLQ_2021-05-24_final.stac-item
2021-07-07 11:46:39	ga_s2bm_ard_3-2-1_50HNK_2021-07-07_final.stac-item
2021-08-03 11:37:28	ga_s2bm_ard_3-2-1_50HNG_2021-08-03_final
2021-09-18 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2021-09-18_final.stac-item
2021-09-25 11:46:24	ga_s2bm_ard_3-2-1_50JML_2021-09-25_final.stac-item
2021-10-08 11:56:30	ga_s2bm_ard_3-2-1_50HNK_2021-10-08_final.stac-item
2021-10-28 11:55:43	ga_s2bm_ard_3-2-1_50JLP_2021-10-28_final.stac-item
2021-11-03 12:14:28	ga_s2bm_ard_3-2-1_49KGP_2021-11-03_final.stac-item
2021-12-13 12:13:50	ga_s2bm_ard_3-2-1_50KKA_2021-12-13_final.stac-item
2021-12-27 11:56:36	ga_s2bm_ard_3-2-1_50HLK_2021-12-27_final.stac-item
2022-01-02 12:13:50	ga_s2bm_ard_3-2-1_50KKA_2022-01-02_final.stac-item
2022-03-14 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2022-03-14_final.stac-item
2022-04-12 12:13:45	ga_s2bm_ard_3-2-1_50KKA_2022-04-12_final.stac-item
2022-05-16 11:53:24	ga_s2bm_ard_3-2-1_50KNC_2022-05-16_final.stac-item
2022-05-19 12:03:23	ga_s2bm_ard_3-2-1_50KMC_2022-05-19_final.stac-item
2022-07-01 12:13:45	ga_s2bm_ard_3-2-1_50KKB_2022-07-01_final.stac-item
2022-07-15 11:55:57	ga_s2bm_ard_3-2-1_50JMN_2022-07-15_final.stac-item
2022-08-30 12:14:46	ga_s2bm_ard_3-2-1_49JFN_2022-08-30_final.stac-item
2022-10-03 11:53:29	ga_s2bm_ard_3-2-1_50KMC_2022-10-03_final.stac-item
2022-11-05 12:05:13	ga_s2bm_ard_3-2-1_49JGL_2022-11-05_final.stac-item
2022-11-09 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2022-11-09_final.stac-item
2022-11-25 12:05:37	ga_s2bm_ard_3-2-1_50JLP_2022-11-25_final.stac-item
2022-12-05 12:04:54	ga_s2bm_ard_3-2-1_50JKS_2022-12-05_final.stac-item
2022-12-15 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2022-12-15_final.stac-item
2022-12-22 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2022-12-22_final.stac-item
2022-12-25 12:05:40	ga_s2bm_ard_3-2-1_50JKP_2022-12-25_final.stac-item
2023-01-14 12:05:47	ga_s2bm_ard_3-2-1_50JLN_2023-01-14_final.stac-item
2023-01-15 11:36:45	ga_s2bm_ard_3-2-1_50HQJ_2023-01-15_final.stac-item
2023-01-24 12:05:39	ga_s2bm_ard_3-2-1_50JKP_2023-01-24_final.stac-item
2023-02-06 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2023-02-06_final
2023-03-29 11:46:11	ga_s2bm_ard_3-2-1_50JNM_2023-03-29_final
2023-04-14 12:04:27	ga_s2bm_ard_3-2-1_50KKU_2023-04-14_final
2023-04-28 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2023-04-28_final
2023-04-28 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2023-04-28_final
2023-05-04 12:05:43	ga_s2bm_ard_3-2-1_50JKP_2023-05-04_final
2023-05-07 12:14:44	ga_s2bm_ard_3-2-1_49JGN_2023-05-07_final
2023-05-18 11:46:34	ga_s2bm_ard_3-2-1_50HQK_2023-05-18_final
2023-06-06 12:13:59	ga_s2bm_ard_3-2-1_50KKA_2023-06-06_final
2023-06-14 11:37:26	ga_s2bm_ard_3-2-1_50HPG_2023-06-14_final
2023-07-03 12:03:49	ga_s2bm_ard_3-2-1_50KKB_2023-07-03_final
2023-08-15 12:14:36	ga_s2bm_ard_3-2-1_49KFP_2023-08-15_nrt
2023-09-15 11:44:48	ga_s2bm_ard_3-2-1_50JRS_2023-09-15_final
2023-10-14 12:15:13	ga_s2bm_ard_3-2-1_49JGL_2023-10-14_final
2023-10-31 12:04:15	ga_s2bm_ard_3-2-1_50KKV_2023-10-31_final
2023-11-10 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-11-10_final
2023-11-17 11:55:45	ga_s2bm_ard_3-2-1_50JKP_2023-11-17_final
2023-11-24 11:45:13	ga_s2bm_ard_3-2-1_50JQQ_2023-11-24_final
2023-12-20 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2023-12-20_final
2024-01-29 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2024-01-29_final
2024-01-30 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2024-01-30_final
2024-03-09 12:04:29	ga_s2bm_ard_3-2-1_49KGP_2024-03-09_final
2024-03-16 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2024-03-16_final
2024-04-15 11:54:27	ga_s2bm_ard_3-2-1_50KMU_2024-04-15_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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