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_51JTN_2017-09-16_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50KKB_2017-11-11_final.stac-item
2018-01-28 11:25:10	ga_s2bm_ard_3-2-1_51JVJ_2018-01-28_final.stac-item
2018-05-07 11:48:28	ga_s2bm_ard_3-2-1_50KRC_2018-05-07_final.stac-item
2018-05-10 12:02:48	ga_s2bm_ard_3-2-1_50KMC_2018-05-10_final.stac-item
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50HLH_2018-05-17_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50KRB_2018-09-21_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_51JTG_2018-09-21_final.stac-item
2018-10-08 11:30:50	ga_s2bm_ard_3-2-1_51JUF_2018-10-08_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50HNK_2018-10-24_final.stac-item
2018-11-16 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2018-11-16_final.stac-item
2018-12-06 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2018-12-06_final.stac-item
2019-02-01 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2019-02-01_final.stac-item
2019-03-13 11:55:03	ga_s2bm_ard_3-2-1_50JNR_2019-03-13_final.stac-item
2019-06-22 11:26:30	ga_s2bm_ard_3-2-1_51HXE_2019-06-22_final.stac-item
2019-08-03 12:03:52	ga_s2bm_ard_3-2-1_50KKB_2019-08-03_final.stac-item
2019-11-04 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-11-04_final.stac-item
2019-12-11 12:03:38	ga_s2bm_ard_3-2-1_50KKB_2019-12-11_final.stac-item
2020-01-28 11:26:54	ga_s2bm_ard_3-2-1_51HUC_2020-01-28_final.stac-item
2020-05-13 11:46:41	ga_s2bm_ard_3-2-1_50HQJ_2020-05-13_final.stac-item
2020-08-11 11:44:56	ga_s2bm_ard_3-2-1_50JPS_2020-08-11_final.stac-item
2020-09-06 12:04:21	ga_s2bm_ard_3-2-1_49KGQ_2020-09-06_final.stac-item
2020-09-09 12:13:57	ga_s2bm_ard_3-2-1_50KKA_2020-09-09_final.stac-item
2020-09-10 11:46:56	ga_s2bm_ard_3-2-1_50HQH_2020-09-10_final.stac-item
2020-09-13 11:53:27	ga_s2bm_ard_3-2-1_50KNC_2020-09-13_final.stac-item
2020-09-13 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2020-09-13_final.stac-item
2020-09-16 12:04:08	ga_s2bm_ard_3-2-1_50KKV_2020-09-16_final.stac-item
2020-09-20 11:45:52	ga_s2bm_ard_3-2-1_50JPN_2020-09-20_final.stac-item
2020-10-04 11:25:16	ga_s2bm_ard_3-2-1_51JWK_2020-10-04_final.stac-item
2020-10-07 11:35:48	ga_s2bm_ard_3-2-1_51JUH_2020-10-07_final.stac-item
2020-11-16 11:35:46	ga_s2bm_ard_3-2-1_51JUH_2020-11-16_final.stac-item
2020-11-18 12:15:11	ga_s2bm_ard_3-2-1_49JGL_2020-11-18_final.stac-item
2021-05-31 11:52:35	ga_s2bm_ard_3-2-1_50KQF_2021-05-31_final
2021-05-31 11:53:25	ga_s2bm_ard_3-2-1_50KNC_2021-05-31_final.stac-item
2021-09-08 11:56:14	ga_s2bm_ard_3-2-1_50JNL_2021-09-08_final.stac-item
2021-09-11 12:06:01	ga_s2bm_ard_3-2-1_50JLM_2021-09-11_final.stac-item
2021-09-18 11:56:14	ga_s2bm_ard_3-2-1_50JNL_2021-09-18_final.stac-item
2021-09-25 11:47:22	ga_s2bm_ard_3-2-1_50HMG_2021-09-25_final
2021-10-08 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2021-10-08_final.stac-item
2022-01-19 12:03:54	ga_s2bm_ard_3-2-1_49KHR_2022-01-19_final.stac-item
2022-01-26 11:56:49	ga_s2bm_ard_3-2-1_50HLJ_2022-01-26_final.stac-item
2022-01-29 12:04:33	ga_s2bm_ard_3-2-1_50JLT_2022-01-29_final.stac-item
2022-01-30 11:36:28	ga_s2bm_ard_3-2-1_51HVD_2022-01-30_final.stac-item
2022-02-28 12:06:00	ga_s2bm_ard_3-2-1_50JLM_2022-02-28_final.stac-item
2022-03-01 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2022-03-01_final.stac-item
2022-03-14 11:46:41	ga_s2bm_ard_3-2-1_50HQJ_2022-03-14_final.stac-item
2022-03-24 11:46:05	ga_s2bm_ard_3-2-1_51JTF_2022-03-24_final.stac-item
2022-04-06 11:56:15	ga_s2bm_ard_3-2-1_50JNL_2022-04-06_final.stac-item
2022-04-06 11:56:37	ga_s2bm_ard_3-2-1_50HLK_2022-04-06_final.stac-item
2022-04-26 11:56:19	ga_s2bm_ard_3-2-1_50JLL_2022-04-26_final.stac-item
2022-04-26 11:56:30	ga_s2bm_ard_3-2-1_50HMK_2022-04-26_final.stac-item
2022-04-30 11:34:40	ga_s2bm_ard_3-2-1_51JUM_2022-04-30_final.stac-item
2022-06-15 11:56:21	ga_s2bm_ard_3-2-1_50JNL_2022-06-15_final.stac-item
2022-07-15 11:56:15	ga_s2bm_ard_3-2-1_50JLM_2022-07-15_final.stac-item
2022-07-15 11:57:10	ga_s2bm_ard_3-2-1_50HMH_2022-07-15_final.stac-item
2022-08-31 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2022-08-31_final.stac-item
2022-08-31 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2022-08-31_final.stac-item
2022-09-06 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2022-09-06_final.stac-item
2022-10-03 11:56:24	ga_s2bm_ard_3-2-1_50JLL_2022-10-03_final.stac-item
2022-10-07 11:36:40	ga_s2bm_ard_3-2-1_51HUD_2022-10-07_final.stac-item
2022-10-13 11:56:10	ga_s2bm_ard_3-2-1_50JLM_2022-10-13_final.stac-item
2022-10-26 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2022-10-26_final.stac-item
2022-12-25 12:04:27	ga_s2bm_ard_3-2-1_50KKU_2022-12-25_final.stac-item
2023-01-04 12:06:08	ga_s2bm_ard_3-2-1_50JKM_2023-01-04_final.stac-item
2023-01-05 11:36:32	ga_s2bm_ard_3-2-1_51HVD_2023-01-05_final.stac-item
2023-01-24 12:06:02	ga_s2bm_ard_3-2-1_50JLM_2023-01-24_final.stac-item
2023-02-14 11:34:38	ga_s2bm_ard_3-2-1_51JWM_2023-02-14_final
2023-04-08 11:47:12	ga_s2bm_ard_3-2-1_50HMH_2023-04-08_final
2023-04-21 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-04-21_final
2023-04-21 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2023-04-21_final
2023-05-11 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2023-05-11_final
2023-05-12 11:26:38	ga_s2bm_ard_3-2-1_51HXD_2023-05-12_final
2023-05-15 11:36:47	ga_s2bm_ard_3-2-1_51HUD_2023-05-15_final
2023-05-22 11:26:45	ga_s2bm_ard_3-2-1_51HWD_2023-05-22_final
2023-05-22 11:26:52	ga_s2bm_ard_3-2-1_51HUD_2023-05-22_final
2023-06-04 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2023-06-04_final
2023-06-27 11:46:48	ga_s2bm_ard_3-2-1_50HQJ_2023-06-27_final
2023-07-17 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-07-17_final
2023-07-18 11:16:49	ga_s2bm_ard_3-2-1_51HWD_2023-07-18_final
2023-08-19 11:56:27	ga_s2bm_ard_3-2-1_50JML_2023-08-19_final
2023-08-19 11:56:56	ga_s2bm_ard_3-2-1_50HMJ_2023-08-19_final
2023-08-26 11:46:52	ga_s2bm_ard_3-2-1_50HPJ_2023-08-26_final
2023-09-06 11:16:31	ga_s2bm_ard_3-2-1_51HXE_2023-09-06_final
2023-09-28 11:56:14	ga_s2bm_ard_3-2-1_50JLM_2023-09-28_final
2023-10-09 11:26:59	ga_s2bm_ard_3-2-1_51HVC_2023-10-09_final
2023-10-15 11:47:09	ga_s2bm_ard_3-2-1_50HNH_2023-10-15_final
2023-10-19 11:26:07	ga_s2bm_ard_3-2-1_51JUG_2023-10-19_final
2023-10-25 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2023-10-25_final
2023-11-18 11:26:34	ga_s2bm_ard_3-2-1_51HXD_2023-11-18_final
2023-12-07 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2023-12-07_final
2023-12-14 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2023-12-14_final
2023-12-20 12:05:15	ga_s2bm_ard_3-2-1_49JGL_2023-12-20_final
2024-01-16 11:53:49	ga_s2bm_ard_3-2-1_50KPA_2024-01-16_final
2024-01-26 11:56:21	ga_s2bm_ard_3-2-1_50JML_2024-01-26_final
2024-02-02 11:46:40	ga_s2bm_ard_3-2-1_50HQJ_2024-02-02_final
2024-02-12 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2024-02-12_final
2024-02-26 11:26:21	ga_s2bm_ard_3-2-1_51HXE_2024-02-26_final
2024-02-28 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2024-02-28_final
2024-03-03 11:46:59	ga_s2bm_ard_3-2-1_50HPH_2024-03-03_final
2024-03-06 11:56:13	ga_s2bm_ard_3-2-1_50JNL_2024-03-06_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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