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
2017-07-05 11:32:58	ga_s2bm_ard_3-2-1_50HQJ_2017-07-05_final.stac-item
2017-07-31 11:49:45	ga_s2bm_ard_3-2-1_50KMC_2017-07-31_final.stac-item
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49KGR_2017-09-15_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_49KHQ_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50KLB_2017-09-22_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_49JHM_2017-10-02_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_50JKQ_2017-10-02_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_50JLS_2017-10-02_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_50JMR_2017-10-02_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50HMK_2017-10-06_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50HNH_2017-10-06_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50JML_2017-10-06_final.stac-item
2017-11-15 11:46:01	ga_s2bm_ard_3-2-1_50HNH_2017-11-15_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50HNJ_2017-12-25_final.stac-item
2018-02-06 11:49:12	ga_s2bm_ard_3-2-1_50HNK_2018-02-06_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JML_2018-04-27_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JNM_2018-04-27_final.stac-item
2018-04-27 11:54:58	ga_s2bm_ard_3-2-1_50JNP_2018-04-27_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50JPP_2018-05-07_final.stac-item
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50KMA_2018-05-07_final.stac-item
2018-05-10 12:02:48	ga_s2bm_ard_3-2-1_50KKU_2018-05-10_final.stac-item
2018-05-13 12:14:07	ga_s2bm_ard_3-2-1_49KGQ_2018-05-13_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50JML_2018-05-14_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50JQM_2018-05-14_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_49JGL_2018-05-20_final.stac-item
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50KMC_2018-05-20_final.stac-item
2018-05-24 11:45:49	ga_s2bm_ard_3-2-1_50HPK_2018-05-24_final.stac-item
2018-05-24 11:45:49	ga_s2bm_ard_3-2-1_50HQK_2018-05-24_final.stac-item
2018-05-31 11:32:50	ga_s2bm_ard_3-2-1_50HQK_2018-05-31_final.stac-item
2018-05-31 11:32:50	ga_s2bm_ard_3-2-1_50JQN_2018-05-31_final.stac-item
2018-06-12 12:13:19	ga_s2bm_ard_3-2-1_50KKB_2018-06-12_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_50KKB_2018-07-09_final.stac-item
2018-07-29 12:04:59	ga_s2bm_ard_3-2-1_49JGK_2018-07-29_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50HNJ_2018-09-21_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_50JML_2018-09-21_final.stac-item
2018-11-10 11:46:53	ga_s2bm_ard_3-2-1_50HMJ_2018-11-10_final.stac-item
2018-11-30 11:47:10	ga_s2bm_ard_3-2-1_50HLH_2018-11-30_final.stac-item
2018-12-03 11:57:01	ga_s2bm_ard_3-2-1_50HMH_2018-12-03_final.stac-item
2019-02-08 11:47:07	ga_s2bm_ard_3-2-1_50HNH_2019-02-08_final.stac-item
2019-04-02 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2019-04-02_final.stac-item
2019-07-31 11:56:22	ga_s2bm_ard_3-2-1_50JKM_2019-07-31_final.stac-item
2019-10-29 11:57:10	ga_s2bm_ard_3-2-1_50HLH_2019-10-29_final.stac-item
2020-01-14 11:46:32	ga_s2bm_ard_3-2-1_50HNK_2020-01-14_final.stac-item
2020-01-14 11:46:35	ga_s2bm_ard_3-2-1_50HMK_2020-01-14_final.stac-item
2020-04-03 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2020-04-03_final.stac-item
2020-04-06 11:54:55	ga_s2bm_ard_3-2-1_50JLS_2020-04-06_final.stac-item
2020-04-06 11:55:39	ga_s2bm_ard_3-2-1_50JLP_2020-04-06_final.stac-item
2020-04-06 11:56:48	ga_s2bm_ard_3-2-1_50HMJ_2020-04-06_final.stac-item
2020-08-04 11:56:02	ga_s2bm_ard_3-2-1_50JKN_2020-08-04_final.stac-item
2020-09-07 11:36:29	ga_s2bm_ard_3-2-1_50JPL_2020-09-07_final.stac-item
2020-10-30 11:47:17	ga_s2bm_ard_3-2-1_50HLH_2020-10-30_final.stac-item
2021-01-08 11:46:54	ga_s2bm_ard_3-2-1_50HMJ_2021-01-08_final.stac-item
2021-01-18 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2021-01-18_final.stac-item
2021-03-19 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2021-03-19_final.stac-item
2021-05-31 11:56:15	ga_s2bm_ard_3-2-1_50JKM_2021-05-31_final.stac-item
2022-02-15 11:56:48	ga_s2bm_ard_3-2-1_50HLJ_2022-02-15_final.stac-item
2022-03-07 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-07_final.stac-item
2022-03-17 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-17_final.stac-item
2022-03-24 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2022-03-24_final.stac-item
2022-05-03 11:46:32	ga_s2bm_ard_3-2-1_50HNK_2022-05-03_final.stac-item
2022-11-12 11:56:21	ga_s2bm_ard_3-2-1_50JNL_2022-11-12_final.stac-item
2022-12-12 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2022-12-12_final.stac-item
2023-01-31 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2023-01-31_final.stac-item
2023-02-20 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2023-02-20_final
2023-05-04 12:03:22	ga_s2bm_ard_3-2-1_50KNC_2023-05-04_final
2023-05-11 11:55:49	ga_s2bm_ard_3-2-1_50JKP_2023-05-11_final
2023-05-21 11:53:29	ga_s2bm_ard_3-2-1_50KNC_2023-05-21_final
2023-05-24 12:03:25	ga_s2bm_ard_3-2-1_50KNC_2023-05-24_final
2023-05-24 12:03:28	ga_s2bm_ard_3-2-1_50KMC_2023-05-24_final
2023-06-26 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2023-06-26_final
2023-07-20 11:53:30	ga_s2bm_ard_3-2-1_50KNC_2023-07-20_final
2023-07-27 11:46:29	ga_s2bm_ard_3-2-1_50JNL_2023-07-27_final
2023-07-30 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-07-30_final
2023-09-01 12:03:31	ga_s2bm_ard_3-2-1_50KLC_2023-09-01_final
2023-09-14 12:14:01	ga_s2bm_ard_3-2-1_49KGR_2023-09-14_final
2023-09-18 11:56:59	ga_s2bm_ard_3-2-1_50HLJ_2023-09-18_final
2023-09-21 12:04:02	ga_s2bm_ard_3-2-1_50KKA_2023-09-21_final
2023-09-28 11:56:54	ga_s2bm_ard_3-2-1_50HMJ_2023-09-28_final
2023-10-21 12:04:01	ga_s2bm_ard_3-2-1_50KKA_2023-10-21_final
2023-10-24 12:14:09	ga_s2bm_ard_3-2-1_50KKV_2023-10-24_final
2023-11-14 11:46:52	ga_s2bm_ard_3-2-1_50HNJ_2023-11-14_final
2023-11-20 12:03:56	ga_s2bm_ard_3-2-1_50KKA_2023-11-20_final
2023-11-30 12:03:38	ga_s2bm_ard_3-2-1_50KLB_2023-11-30_final
2023-11-30 12:03:56	ga_s2bm_ard_3-2-1_50KKA_2023-11-30_final
2023-12-20 12:03:41	ga_s2bm_ard_3-2-1_50KLB_2023-12-20_final
2023-12-20 12:03:59	ga_s2bm_ard_3-2-1_50KKA_2023-12-20_final
2023-12-30 12:04:00	ga_s2bm_ard_3-2-1_49KHR_2023-12-30_final
2024-01-16 11:53:30	ga_s2bm_ard_3-2-1_50KMC_2024-01-16_final
2024-01-19 12:03:19	ga_s2bm_ard_3-2-1_50KNC_2024-01-19_final
2024-01-23 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2024-01-23_final
2024-01-29 12:03:39	ga_s2bm_ard_3-2-1_50KLB_2024-01-29_final
2024-02-08 12:03:19	ga_s2bm_ard_3-2-1_50KNC_2024-02-08_final
2024-02-08 12:03:44	ga_s2bm_ard_3-2-1_50KKB_2024-02-08_final
2024-02-12 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2024-02-12_final
2024-02-15 11:54:47	ga_s2bm_ard_3-2-1_50JMS_2024-02-15_final
2024-02-28 12:05:54	ga_s2bm_ard_3-2-1_50JKN_2024-02-28_final
2024-03-26 11:56:51	ga_s2bm_ard_3-2-1_50HMJ_2024-03-26_final
2024-04-08 12:06:09	ga_s2bm_ard_3-2-1_50JKM_2024-04-08_final
2024-05-18 12:03:25	ga_s2bm_ard_3-2-1_50KLC_2024-05-18_nrt
2024-05-18 12:03:57	ga_s2bm_ard_3-2-1_50KKA_2024-05-18_nrt

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