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
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HMK_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50HPK_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50JNL_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50JPN_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_51JTJ_2017-09-16_final.stac-item
2017-10-03 11:35:52	ga_s2bm_ard_3-2-1_51JUF_2017-10-03_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JKN_2017-11-11_final.stac-item
2017-12-22 11:27:17	ga_s2bm_ard_3-2-1_51JVF_2017-12-22_final.stac-item
2018-01-25 11:07:05	ga_s2bm_ard_3-2-1_51JYH_2018-01-25_final.stac-item
2018-02-07 11:16:52	ga_s2bm_ard_3-2-1_51HVE_2018-02-07_final.stac-item
2018-04-28 11:18:17	ga_s2bm_ard_3-2-1_51KXS_2018-04-28_final.stac-item
2018-04-28 11:18:17	ga_s2bm_ard_3-2-1_51KYT_2018-04-28_final.stac-item
2018-05-05 11:13:23	ga_s2bm_ard_3-2-1_51JXF_2018-05-05_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50JLR_2018-05-07_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_50JQL_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_51HUE_2018-05-11_final.stac-item
2018-05-11 11:32:38	ga_s2bm_ard_3-2-1_51JTF_2018-05-11_final.stac-item
2018-05-14 11:37:58	ga_s2bm_ard_3-2-1_51KTU_2018-05-14_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50HPK_2018-05-14_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JKN_2018-05-20_final.stac-item
2018-05-23 12:13:19	ga_s2bm_ard_3-2-1_49KGR_2018-05-23_final.stac-item
2018-05-24 11:45:49	ga_s2bm_ard_3-2-1_50HMJ_2018-05-24_final.stac-item
2018-05-31 11:27:22	ga_s2bm_ard_3-2-1_51KVU_2018-05-31_final.stac-item
2018-06-14 11:10:36	ga_s2bm_ard_3-2-1_51KZS_2018-06-14_final.stac-item
2018-06-17 11:19:48	ga_s2bm_ard_3-2-1_51KYT_2018-06-17_final.stac-item
2018-06-20 11:26:19	ga_s2bm_ard_3-2-1_51KWB_2018-06-20_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KUT_2018-06-23_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50JLN_2018-10-04_final.stac-item
2018-11-20 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2018-11-20_final.stac-item
2019-03-19 12:15:09	ga_s2bm_ard_3-2-1_49JGL_2019-03-19_final.stac-item
2019-04-09 11:43:08	ga_s2bm_ard_3-2-1_50KRD_2019-04-09_final.stac-item
2019-05-15 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-05-15_final.stac-item
2019-06-18 11:43:22	ga_s2bm_ard_3-2-1_51KUT_2019-06-18_final.stac-item
2019-06-22 11:23:33	ga_s2bm_ard_3-2-1_51KYS_2019-06-22_final.stac-item
2019-07-04 12:04:07	ga_s2bm_ard_3-2-1_50KKA_2019-07-04_final.stac-item
2019-12-09 11:24:17	ga_s2bm_ard_3-2-1_51JYN_2019-12-09_final.stac-item
2020-01-28 11:26:12	ga_s2bm_ard_3-2-1_51JUF_2020-01-28_final.stac-item
2020-02-06 11:56:45	ga_s2bm_ard_3-2-1_50HMJ_2020-02-06_final.stac-item
2020-02-17 11:26:25	ga_s2bm_ard_3-2-1_51HVE_2020-02-17_final.stac-item
2020-03-07 11:57:03	ga_s2bm_ard_3-2-1_50HMH_2020-03-07_final.stac-item
2020-03-28 11:26:30	ga_s2bm_ard_3-2-1_51HUE_2020-03-28_final.stac-item
2020-04-07 11:26:11	ga_s2bm_ard_3-2-1_51JVF_2020-04-07_final.stac-item
2020-05-17 11:23:35	ga_s2bm_ard_3-2-1_51KZR_2020-05-17_final.stac-item
2020-06-16 11:23:27	ga_s2bm_ard_3-2-1_51KYS_2020-06-16_final.stac-item
2020-07-06 11:23:42	ga_s2bm_ard_3-2-1_51KXR_2020-07-06_final.stac-item
2020-07-29 11:33:11	ga_s2bm_ard_3-2-1_51KXT_2020-07-29_final.stac-item
2020-07-29 11:33:48	ga_s2bm_ard_3-2-1_51KVR_2020-07-29_final.stac-item
2020-08-02 11:16:58	ga_s2bm_ard_3-2-1_51HXC_2020-08-02_final
2020-08-08 11:36:37	ga_s2bm_ard_3-2-1_51HVD_2020-08-08_final.stac-item
2020-09-16 12:04:51	ga_s2bm_ard_3-2-1_49JGN_2020-09-16_final.stac-item
2020-11-13 11:26:15	ga_s2bm_ard_3-2-1_51JVF_2020-11-13_final.stac-item
2020-12-28 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2020-12-28_final.stac-item
2021-03-12 11:56:07	ga_s2bm_ard_3-2-1_50JMM_2021-03-12_final.stac-item
2021-03-16 11:32:21	ga_s2bm_ard_3-2-1_51KYA_2021-03-16_final.stac-item
2021-04-04 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2021-04-04_final.stac-item
2021-04-14 12:05:25	ga_s2bm_ard_3-2-1_49JGK_2021-04-14_final.stac-item
2021-07-11 11:23:23	ga_s2bm_ard_3-2-1_51KZS_2021-07-11_final.stac-item
2021-07-17 11:41:35	ga_s2bm_ard_3-2-1_51LUE_2021-07-17_final.stac-item
2021-08-29 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2021-08-29_final.stac-item
2021-11-14 11:47:13	ga_s2bm_ard_3-2-1_50HLH_2021-11-14_final.stac-item
2022-01-23 11:47:04	ga_s2bm_ard_3-2-1_50HMH_2022-01-23_final.stac-item
2022-03-07 11:56:11	ga_s2bm_ard_3-2-1_50JKM_2022-03-07_final.stac-item
2022-04-12 12:13:45	ga_s2bm_ard_3-2-1_50KKA_2022-04-12_final.stac-item
2022-05-19 12:03:59	ga_s2bm_ard_3-2-1_49KHR_2022-05-19_final.stac-item
2022-06-01 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2022-06-01_final.stac-item
2022-06-05 11:56:30	ga_s2bm_ard_3-2-1_50HNK_2022-06-05_final.stac-item
2022-08-02 11:13:45	ga_s2bm_ard_3-2-1_51KZR_2022-08-02_final.stac-item
2022-10-16 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2022-10-16_final.stac-item
2022-11-06 11:37:05	ga_s2bm_ard_3-2-1_50HPH_2022-11-06_final.stac-item
2023-05-04 12:03:47	ga_s2bm_ard_3-2-1_49KHS_2023-05-04_final
2023-05-05 11:34:18	ga_s2bm_ard_3-2-1_51JXN_2023-05-05_final
2023-06-24 11:33:13	ga_s2bm_ard_3-2-1_51KXT_2023-06-24_final
2023-07-01 11:26:49	ga_s2bm_ard_3-2-1_51HVD_2023-07-01_final
2023-07-04 11:36:01	ga_s2bm_ard_3-2-1_51JVG_2023-07-04_final
2023-07-10 11:52:25	ga_s2bm_ard_3-2-1_50KQG_2023-07-10_final
2023-07-10 11:56:04	ga_s2bm_ard_3-2-1_50JKN_2023-07-10_final
2023-07-11 11:23:30	ga_s2bm_ard_3-2-1_51KYS_2023-07-11_final
2023-07-21 11:23:16	ga_s2bm_ard_3-2-1_51KYT_2023-07-21_final
2023-07-30 11:55:52	ga_s2bm_ard_3-2-1_50JKP_2023-07-30_final
2023-08-02 12:04:18	ga_s2bm_ard_3-2-1_50KKV_2023-08-02_final
2023-08-17 11:13:34	ga_s2bm_ard_3-2-1_51KZS_2023-08-17_final
2023-09-02 11:36:36	ga_s2bm_ard_3-2-1_51HTE_2023-09-02_final
2023-09-22 11:36:30	ga_s2bm_ard_3-2-1_50JPL_2023-09-22_final
2023-10-18 11:56:06	ga_s2bm_ard_3-2-1_50JLN_2023-10-18_final
2023-10-18 11:57:22	ga_s2bm_ard_3-2-1_50HMG_2023-10-18_final
2023-10-28 11:56:15	ga_s2bm_ard_3-2-1_50JKM_2023-10-28_final
2023-12-07 11:53:28	ga_s2bm_ard_3-2-1_50KMC_2023-12-07_final
2023-12-10 12:03:40	ga_s2bm_ard_3-2-1_50KKB_2023-12-10_final
2023-12-17 11:57:09	ga_s2bm_ard_3-2-1_50HLH_2023-12-17_final
2023-12-23 12:14:57	ga_s2bm_ard_3-2-1_49JGM_2023-12-23_final
2023-12-27 11:53:32	ga_s2bm_ard_3-2-1_50KMC_2023-12-27_final
2024-01-16 11:52:18	ga_s2bm_ard_3-2-1_50KQG_2024-01-16_final
2024-01-19 12:05:55	ga_s2bm_ard_3-2-1_50JKN_2024-01-19_final
2024-01-23 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2024-01-23_final
2024-02-12 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2024-02-12_final
2024-02-26 11:26:29	ga_s2bm_ard_3-2-1_51HVE_2024-02-26_final
2024-03-23 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2024-03-23_final
2024-03-26 11:56:00	ga_s2bm_ard_3-2-1_50JKN_2024-03-26_final
2024-03-29 12:03:44	ga_s2bm_ard_3-2-1_50KKB_2024-03-29_final
2024-04-12 11:47:10	ga_s2bm_ard_3-2-1_50HMH_2024-04-12_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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