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
2017-09-23 11:29:24	ga_s2bm_ard_3-2-1_51KXS_2017-09-23_final.stac-item
2017-10-13 11:30:03	ga_s2bm_ard_3-2-1_51KVB_2017-10-13_final.stac-item
2018-01-30 12:02:42	ga_s2bm_ard_3-2-1_49JGJ_2018-01-30_final.stac-item
2018-03-25 11:44:34	ga_s2bm_ard_3-2-1_50JMM_2018-03-25_final.stac-item
2018-05-04 11:38:16	ga_s2bm_ard_3-2-1_51KUS_2018-05-04_final.stac-item
2018-05-04 11:38:16	ga_s2bm_ard_3-2-1_51KVU_2018-05-04_final.stac-item
2018-05-04 11:43:41	ga_s2bm_ard_3-2-1_51KUQ_2018-05-04_final.stac-item
2018-06-02 12:13:22	ga_s2bm_ard_3-2-1_49KHP_2018-06-02_final.stac-item
2018-07-03 11:38:24	ga_s2bm_ard_3-2-1_51KUT_2018-07-03_final.stac-item
2018-08-29 11:30:45	ga_s2bm_ard_3-2-1_51KUT_2018-08-29_final.stac-item
2018-09-20 12:13:54	ga_s2bm_ard_3-2-1_49KHP_2018-09-20_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_51JTH_2018-09-21_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_51KWB_2018-09-21_final.stac-item
2018-09-22 11:12:44	ga_s2bm_ard_3-2-1_51JYH_2018-09-22_final.stac-item
2018-09-27 12:04:56	ga_s2bm_ard_3-2-1_49JGJ_2018-09-27_final.stac-item
2019-02-04 12:05:44	ga_s2bm_ard_3-2-1_49JGJ_2019-02-04_final.stac-item
2019-02-05 11:32:32	ga_s2bm_ard_3-2-1_51KVA_2019-02-05_final.stac-item
2019-07-12 11:26:45	ga_s2bm_ard_3-2-1_51HXD_2019-07-12_final.stac-item
2019-07-27 12:14:12	ga_s2bm_ard_3-2-1_50KKV_2019-07-27_final.stac-item
2020-04-03 11:43:22	ga_s2bm_ard_3-2-1_51KVS_2020-04-03_final.stac-item
2020-04-30 11:32:10	ga_s2bm_ard_3-2-1_51KWB_2020-04-30_final.stac-item
2020-05-13 11:43:14	ga_s2bm_ard_3-2-1_51KUT_2020-05-13_final.stac-item
2020-05-23 11:43:15	ga_s2bm_ard_3-2-1_51KUT_2020-05-23_final.stac-item
2020-06-02 11:42:11	ga_s2bm_ard_3-2-1_51KWB_2020-06-02_final.stac-item
2020-07-06 11:23:59	ga_s2bm_ard_3-2-1_51KXQ_2020-07-06_final.stac-item
2020-08-01 11:43:18	ga_s2bm_ard_3-2-1_51KUT_2020-08-01_final.stac-item
2020-08-08 11:32:18	ga_s2bm_ard_3-2-1_51KWB_2020-08-08_final.stac-item
2020-09-10 11:42:48	ga_s2bm_ard_3-2-1_51KUV_2020-09-10_final.stac-item
2020-09-17 11:32:16	ga_s2bm_ard_3-2-1_51KWB_2020-09-17_final.stac-item
2021-04-22 11:23:22	ga_s2bm_ard_3-2-1_51KXS_2021-04-22_final.stac-item
2021-04-25 11:33:07	ga_s2bm_ard_3-2-1_51KWT_2021-04-25_final.stac-item
2021-07-30 11:52:21	ga_s2bm_ard_3-2-1_50KQG_2021-07-30_final
2021-09-18 11:56:14	ga_s2bm_ard_3-2-1_50JNL_2021-09-18_final.stac-item
2021-09-28 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2021-09-28_final.stac-item
2021-10-08 11:56:12	ga_s2bm_ard_3-2-1_50JLM_2021-10-08_final.stac-item
2021-10-18 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2021-10-18_final.stac-item
2021-10-18 11:57:07	ga_s2bm_ard_3-2-1_50HMH_2021-10-18_final.stac-item
2021-10-18 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2021-10-18_final.stac-item
2021-12-25 11:16:36	ga_s2bm_ard_3-2-1_51HXD_2021-12-25_final.stac-item
2022-01-17 11:26:54	ga_s2bm_ard_3-2-1_51HVC_2022-01-17_final.stac-item
2022-02-15 11:56:08	ga_s2bm_ard_3-2-1_50JKM_2022-02-15_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 11:57:05	ga_s2bm_ard_3-2-1_50HLH_2022-04-16_final.stac-item
2022-04-23 11:46:57	ga_s2bm_ard_3-2-1_50HPH_2022-04-23_final.stac-item
2022-04-30 11:34:43	ga_s2bm_ard_3-2-1_51JTM_2022-04-30_final.stac-item
2022-04-30 11:34:54	ga_s2bm_ard_3-2-1_51JUL_2022-04-30_final.stac-item
2022-04-30 11:35:38	ga_s2bm_ard_3-2-1_51JUH_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
2022-05-30 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2022-05-30_final.stac-item
2022-06-29 11:37:06	ga_s2bm_ard_3-2-1_51HTC_2022-06-29_final.stac-item
2022-07-22 11:43:20	ga_s2bm_ard_3-2-1_51KUT_2022-07-22_final.stac-item
2022-08-14 11:56:54	ga_s2bm_ard_3-2-1_50HMJ_2022-08-14_final.stac-item
2022-09-10 11:46:54	ga_s2bm_ard_3-2-1_50HNJ_2022-09-10_final.stac-item
2022-09-13 11:56:24	ga_s2bm_ard_3-2-1_50JML_2022-09-13_final.stac-item
2022-09-30 11:43:03	ga_s2bm_ard_3-2-1_50KRD_2022-09-30_final.stac-item
2022-10-03 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2022-10-03_final.stac-item
2022-10-13 11:56:35	ga_s2bm_ard_3-2-1_50HMK_2022-10-13_final.stac-item
2023-02-20 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2023-02-20_final
2023-04-21 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-04-21_final
2023-05-05 11:36:45	ga_s2bm_ard_3-2-1_51HUD_2023-05-05_final
2023-05-11 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2023-05-11_final
2023-05-15 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2023-05-15_final
2023-06-01 11:24:01	ga_s2bm_ard_3-2-1_51KXQ_2023-06-01_final
2023-06-21 11:25:57	ga_s2bm_ard_3-2-1_51JXG_2023-06-21_final
2023-06-27 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-06-27_final
2023-07-20 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-07-20_final
2023-08-03 11:33:57	ga_s2bm_ard_3-2-1_51KXQ_2023-08-03_final
2023-08-09 11:56:56	ga_s2bm_ard_3-2-1_50HMJ_2023-08-09_final
2023-08-13 11:37:12	ga_s2bm_ard_3-2-1_50HPH_2023-08-13_final
2023-08-16 11:43:22	ga_s2bm_ard_3-2-1_51KUT_2023-08-16_final
2023-08-19 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2023-08-19_final
2023-08-29 11:56:30	ga_s2bm_ard_3-2-1_50JLL_2023-08-29_final
2023-08-29 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2023-08-29_final
2023-09-28 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2023-09-28_final
2023-10-05 11:46:48	ga_s2bm_ard_3-2-1_50HPJ_2023-10-05_final
2023-10-05 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2023-10-05_final
2023-10-08 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2023-10-08_final
2023-10-15 11:46:50	ga_s2bm_ard_3-2-1_50HPJ_2023-10-15_final
2023-10-18 11:56:32	ga_s2bm_ard_3-2-1_50HNK_2023-10-18_final
2023-10-25 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2023-10-25_final
2023-11-20 12:05:49	ga_s2bm_ard_3-2-1_50JLN_2023-11-20_final
2023-12-14 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2023-12-14_final
2023-12-17 11:52:37	ga_s2bm_ard_3-2-1_50KPF_2023-12-17_final
2023-12-17 11:56:17	ga_s2bm_ard_3-2-1_50JNL_2023-12-17_final
2024-01-10 11:36:32	ga_s2bm_ard_3-2-1_51HVD_2024-01-10_final
2024-01-26 11:56:24	ga_s2bm_ard_3-2-1_50JLL_2024-01-26_final
2024-01-29 12:05:42	ga_s2bm_ard_3-2-1_49JGJ_2024-01-29_final
2024-02-03 11:15:51	ga_s2bm_ard_3-2-1_51JYG_2024-02-03_final
2024-02-15 11:52:21	ga_s2bm_ard_3-2-1_50KQG_2024-02-15_final
2024-02-22 11:47:27	ga_s2bm_ard_3-2-1_50HLG_2024-02-22_final
2024-03-23 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2024-03-23_final
2024-03-30 11:33:23	ga_s2bm_ard_3-2-1_51KXS_2024-03-30_final
2024-04-02 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2024-04-02_final
2024-04-02 11:47:01	ga_s2bm_ard_3-2-1_50HPH_2024-04-02_final
2024-04-05 11:52:35	ga_s2bm_ard_3-2-1_50KPF_2024-04-05_final
2024-04-18 12:05:45	ga_s2bm_ard_3-2-1_49JGJ_2024-04-18_final
2024-04-26 11:23:41	ga_s2bm_ard_3-2-1_51KXR_2024-04-26_final
2024-04-29 11:34:05	ga_s2bm_ard_3-2-1_51KXP_2024-04-29_final
2024-05-02 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2024-05-02_final
2024-05-09 11:33:39	ga_s2bm_ard_3-2-1_51KXR_2024-05-09_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