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
2018-09-20 12:13:54	ga_s2bm_ard_3-2-1_49JGN_2018-09-20_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HLH_2018-09-21_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50HLH_2018-09-24_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_50KKA_2018-10-10_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_50KKV_2018-10-10_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49KGQ_2018-10-17_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50KLC_2018-10-27_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JGL_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JGN_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_50KKV_2018-10-30_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50JPP_2018-11-03_final.stac-item
2018-11-06 12:04:16	ga_s2bm_ard_3-2-1_49KGQ_2018-11-06_final.stac-item
2018-11-19 12:14:18	ga_s2bm_ard_3-2-1_49KHP_2018-11-19_final.stac-item
2018-12-09 12:14:02	ga_s2bm_ard_3-2-1_50KKV_2018-12-09_final.stac-item
2019-04-15 12:05:49	ga_s2bm_ard_3-2-1_49JGJ_2019-04-15_final.stac-item
2019-07-24 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-07-24_final.stac-item
2019-11-04 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2019-11-04_final.stac-item
2019-11-14 12:13:53	ga_s2bm_ard_3-2-1_50KKA_2019-11-14_final.stac-item
2020-08-10 12:14:02	ga_s2bm_ard_3-2-1_49KGR_2020-08-10_final.stac-item
2020-09-13 11:56:16	ga_s2bm_ard_3-2-1_50JKM_2020-09-13_final.stac-item
2020-09-13 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2020-09-13_final.stac-item
2020-09-19 12:13:56	ga_s2bm_ard_3-2-1_50KKA_2020-09-19_final.stac-item
2020-09-23 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2020-09-23_final.stac-item
2020-09-23 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2020-09-23_final.stac-item
2020-09-29 12:13:59	ga_s2bm_ard_3-2-1_50KKA_2020-09-29_final.stac-item
2020-12-08 12:13:56	ga_s2bm_ard_3-2-1_49KGR_2020-12-08_final.stac-item
2021-09-05 11:46:40	ga_s2bm_ard_3-2-1_50HQJ_2021-09-05_final.stac-item
2021-09-08 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2021-09-08_final.stac-item
2021-09-08 11:56:33	ga_s2bm_ard_3-2-1_50HMK_2021-09-08_final.stac-item
2021-09-28 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2021-09-28_final.stac-item
2021-10-08 11:56:18	ga_s2bm_ard_3-2-1_50JNL_2021-10-08_final.stac-item
2021-10-18 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2021-10-18_final.stac-item
2021-11-07 11:56:18	ga_s2bm_ard_3-2-1_50JNL_2021-11-07_final.stac-item
2021-11-07 11:56:40	ga_s2bm_ard_3-2-1_50HLK_2021-11-07_final.stac-item
2021-11-24 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2021-11-24_final.stac-item
2021-12-17 11:56:05	ga_s2bm_ard_3-2-1_50JLM_2021-12-17_final.stac-item
2021-12-24 11:46:43	ga_s2bm_ard_3-2-1_50HPJ_2021-12-24_final.stac-item
2021-12-27 11:56:06	ga_s2bm_ard_3-2-1_50JLM_2021-12-27_final.stac-item
2022-01-03 11:46:39	ga_s2bm_ard_3-2-1_50HQJ_2022-01-03_final.stac-item
2022-01-03 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2022-01-03_final.stac-item
2022-01-09 12:05:47	ga_s2bm_ard_3-2-1_50JLN_2022-01-09_final.stac-item
2022-01-10 11:36:59	ga_s2bm_ard_3-2-1_50HQH_2022-01-10_final.stac-item
2022-01-13 11:46:58	ga_s2bm_ard_3-2-1_50HPH_2022-01-13_final.stac-item
2022-01-26 11:56:24	ga_s2bm_ard_3-2-1_50HNK_2022-01-26_final.stac-item
2022-01-29 12:05:58	ga_s2bm_ard_3-2-1_50JLM_2022-01-29_final.stac-item
2022-02-02 11:46:42	ga_s2bm_ard_3-2-1_50HPJ_2022-02-02_final.stac-item
2022-02-05 11:56:16	ga_s2bm_ard_3-2-1_50JML_2022-02-05_final.stac-item
2022-02-05 11:56:24	ga_s2bm_ard_3-2-1_50HNK_2022-02-05_final.stac-item
2022-02-15 11:56:16	ga_s2bm_ard_3-2-1_50JML_2022-02-15_final.stac-item
2022-03-24 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2022-03-24_final.stac-item
2022-03-27 11:56:08	ga_s2bm_ard_3-2-1_50JLM_2022-03-27_final.stac-item
2022-04-16 11:56:22	ga_s2bm_ard_3-2-1_50JLL_2022-04-16_final.stac-item
2022-04-16 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2022-04-16_final.stac-item
2022-04-26 11:56:16	ga_s2bm_ard_3-2-1_50JML_2022-04-26_final.stac-item
2022-04-30 11:34:42	ga_s2bm_ard_3-2-1_50JRS_2022-04-30_final.stac-item
2022-05-06 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2022-05-06_final.stac-item
2022-05-26 11:56:22	ga_s2bm_ard_3-2-1_50JML_2022-05-26_final.stac-item
2022-06-22 11:46:56	ga_s2bm_ard_3-2-1_50HNJ_2022-06-22_final.stac-item
2022-07-12 11:46:56	ga_s2bm_ard_3-2-1_50HNJ_2022-07-12_final.stac-item
2022-07-18 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2022-07-18_final.stac-item
2022-08-07 12:05:59	ga_s2bm_ard_3-2-1_50JKN_2022-08-07_final.stac-item
2022-09-10 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2022-09-10_final.stac-item
2022-09-27 11:37:07	ga_s2bm_ard_3-2-1_50HPH_2022-09-27_final.stac-item
2022-10-03 11:56:21	ga_s2bm_ard_3-2-1_50JML_2022-10-03_final.stac-item
2022-10-20 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2022-10-20_final.stac-item
2022-10-26 12:06:03	ga_s2bm_ard_3-2-1_50JLM_2022-10-26_final.stac-item
2022-11-02 11:56:20	ga_s2bm_ard_3-2-1_50JML_2022-11-02_final.stac-item
2022-11-02 11:56:53	ga_s2bm_ard_3-2-1_50HLJ_2022-11-02_final.stac-item
2022-11-09 11:46:47	ga_s2bm_ard_3-2-1_50HPJ_2022-11-09_final.stac-item
2022-11-29 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2022-11-29_final.stac-item
2022-12-05 12:05:49	ga_s2bm_ard_3-2-1_50JLN_2022-12-05_final.stac-item
2022-12-09 11:46:39	ga_s2bm_ard_3-2-1_50HQJ_2022-12-09_final.stac-item
2023-01-01 11:56:17	ga_s2bm_ard_3-2-1_50JNL_2023-01-01_final.stac-item
2023-01-05 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2023-01-05_final.stac-item
2023-01-05 11:37:01	ga_s2bm_ard_3-2-1_50HQH_2023-01-05_final.stac-item
2023-03-05 12:05:54	ga_s2bm_ard_3-2-1_50JLN_2023-03-05_final
2023-03-09 11:46:47	ga_s2bm_ard_3-2-1_50HQJ_2023-03-09_final
2023-03-12 11:56:26	ga_s2bm_ard_3-2-1_50JML_2023-03-12_final
2023-03-29 11:46:46	ga_s2bm_ard_3-2-1_50HQJ_2023-03-29_final
2023-03-29 11:46:51	ga_s2bm_ard_3-2-1_50HPJ_2023-03-29_final
2023-05-01 11:56:32	ga_s2bm_ard_3-2-1_50HNK_2023-05-01_final
2023-05-01 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-05-01_final
2023-05-11 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2023-05-11_final
2023-06-17 11:47:15	ga_s2bm_ard_3-2-1_50HMH_2023-06-17_final
2023-06-30 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-06-30_final
2023-08-19 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-08-19_final
2023-09-02 11:37:22	ga_s2bm_ard_3-2-1_50HQG_2023-09-02_final
2023-09-25 11:47:10	ga_s2bm_ard_3-2-1_50HNH_2023-09-25_final
2023-09-28 11:56:21	ga_s2bm_ard_3-2-1_50JNL_2023-09-28_final
2023-10-01 12:06:06	ga_s2bm_ard_3-2-1_50JLM_2023-10-01_final
2023-10-11 12:06:06	ga_s2bm_ard_3-2-1_50JLM_2023-10-11_final
2023-12-24 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2023-12-24_final
2023-12-30 12:06:05	ga_s2bm_ard_3-2-1_50JLM_2023-12-30_final
2024-01-26 11:56:33	ga_s2bm_ard_3-2-1_50HLK_2024-01-26_final
2024-02-02 11:46:56	ga_s2bm_ard_3-2-1_50HPH_2024-02-02_final
2024-02-02 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2024-02-02_final
2024-02-22 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2024-02-22_final
2024-04-12 11:46:57	ga_s2bm_ard_3-2-1_50HPH_2024-04-12_final
2024-04-18 12:05:45	ga_s2bm_ard_3-2-1_49JGJ_2024-04-18_final
2024-05-12 11:47:17	ga_s2bm_ard_3-2-1_50HPG_2024-05-12_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

All years