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
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JKT_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JLS_2017-07-14_final.stac-item
2017-07-14 12:04:42	ga_s2bm_ard_3-2-1_50JLT_2017-07-14_final.stac-item
2017-08-03 12:04:41	ga_s2bm_ard_3-2-1_50JLT_2017-08-03_final.stac-item
2017-09-12 12:04:33	ga_s2bm_ard_3-2-1_50JLT_2017-09-12_final.stac-item
2017-09-15 12:13:36	ga_s2bm_ard_3-2-1_49KHP_2017-09-15_final.stac-item
2017-10-02 12:04:26	ga_s2bm_ard_3-2-1_49JHN_2017-10-02_final.stac-item
2017-11-11 12:02:35	ga_s2bm_ard_3-2-1_50JLR_2017-11-11_final.stac-item
2018-03-28 11:51:53	ga_s2bm_ard_3-2-1_50JMQ_2018-03-28_final.stac-item
2018-04-27 11:53:35	ga_s2bm_ard_3-2-1_50JLT_2018-04-27_final.stac-item
2018-06-09 12:02:47	ga_s2bm_ard_3-2-1_50JLS_2018-06-09_final.stac-item
2018-06-16 11:51:10	ga_s2bm_ard_3-2-1_50JLS_2018-06-16_final.stac-item
2018-06-26 11:54:14	ga_s2bm_ard_3-2-1_50JLS_2018-06-26_final.stac-item
2018-07-06 11:51:46	ga_s2bm_ard_3-2-1_50JLS_2018-07-06_final.stac-item
2018-07-09 12:03:10	ga_s2bm_ard_3-2-1_50JLS_2018-07-09_final.stac-item
2018-08-25 11:52:52	ga_s2bm_ard_3-2-1_50JLT_2018-08-25_final.stac-item
2018-09-24 11:52:42	ga_s2bm_ard_3-2-1_50JMQ_2018-09-24_final.stac-item
2019-02-01 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2019-02-01_final.stac-item
2019-02-04 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2019-02-04_final.stac-item
2019-05-15 12:05:02	ga_s2bm_ard_3-2-1_50JLS_2019-05-15_final.stac-item
2019-05-15 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-15_final.stac-item
2019-05-22 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-05-22_final.stac-item
2019-05-22 11:55:33	ga_s2bm_ard_3-2-1_50JMQ_2019-05-22_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-07-01 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-07-01_final.stac-item
2019-07-14 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-07-14_final.stac-item
2019-07-31 11:55:06	ga_s2bm_ard_3-2-1_50JLS_2019-07-31_final.stac-item
2019-07-31 11:55:32	ga_s2bm_ard_3-2-1_50JMQ_2019-07-31_final.stac-item
2019-08-10 11:55:05	ga_s2bm_ard_3-2-1_50JLS_2019-08-10_final.stac-item
2019-08-20 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2019-08-20_final.stac-item
2020-03-10 12:05:06	ga_s2bm_ard_3-2-1_50JLR_2020-03-10_final.stac-item
2020-03-27 11:55:22	ga_s2bm_ard_3-2-1_50JMQ_2020-03-27_final.stac-item
2020-05-19 12:05:12	ga_s2bm_ard_3-2-1_50JKR_2020-05-19_final.stac-item
2020-05-19 12:05:19	ga_s2bm_ard_3-2-1_50JKQ_2020-05-19_final.stac-item
2020-06-08 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2020-06-08_final.stac-item
2020-06-08 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2020-06-08_final.stac-item
2020-07-08 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2020-07-08_final.stac-item
2020-07-08 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2020-07-08_final.stac-item
2020-07-18 12:04:55	ga_s2bm_ard_3-2-1_50JLS_2020-07-18_final.stac-item
2020-07-28 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2020-07-28_final.stac-item
2020-07-31 12:14:34	ga_s2bm_ard_3-2-1_49JHN_2020-07-31_final.stac-item
2020-08-17 12:04:50	ga_s2bm_ard_3-2-1_50JLT_2020-08-17_final.stac-item
2020-08-17 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2020-08-17_final.stac-item
2020-09-16 12:04:48	ga_s2bm_ard_3-2-1_50JLT_2020-09-16_final.stac-item
2020-09-16 12:04:50	ga_s2bm_ard_3-2-1_49JHM_2020-09-16_final.stac-item
2020-10-06 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2020-10-06_final.stac-item
2020-10-16 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2020-10-16_final.stac-item
2020-10-16 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2020-10-16_final.stac-item
2021-01-21 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2021-01-21_final.stac-item
2021-02-10 11:55:23	ga_s2bm_ard_3-2-1_50JLQ_2021-02-10_final.stac-item
2021-02-26 12:13:44	ga_s2bm_ard_3-2-1_49KHS_2021-02-26_final
2021-03-09 11:47:27	ga_s2bm_ard_3-2-1_50HLG_2021-03-09_final
2021-03-15 12:04:58	ga_s2bm_ard_3-2-1_50JMR_2021-03-15_final.stac-item
2021-03-22 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2021-03-22_final.stac-item
2021-03-25 12:04:57	ga_s2bm_ard_3-2-1_50JMR_2021-03-25_final.stac-item
2021-04-01 11:55:08	ga_s2bm_ard_3-2-1_50JMR_2021-04-01_final.stac-item
2021-04-04 12:04:44	ga_s2bm_ard_3-2-1_50JLS_2021-04-04_final.stac-item
2021-04-04 12:04:57	ga_s2bm_ard_3-2-1_50JMR_2021-04-04_final.stac-item
2021-04-14 12:04:44	ga_s2bm_ard_3-2-1_49JHM_2021-04-14_final.stac-item
2021-04-24 12:04:53	ga_s2bm_ard_3-2-1_50JMR_2021-04-24_final.stac-item
2021-05-21 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2021-05-21_final.stac-item
2021-06-20 11:55:25	ga_s2bm_ard_3-2-1_50JMQ_2021-06-20_final.stac-item
2021-08-12 12:04:59	ga_s2bm_ard_3-2-1_50JMR_2021-08-12_final.stac-item
2021-08-29 11:54:42	ga_s2bm_ard_3-2-1_50JLT_2021-08-29_final.stac-item
2021-09-11 12:04:43	ga_s2bm_ard_3-2-1_50JLS_2021-09-11_final.stac-item
2021-09-18 11:54:41	ga_s2bm_ard_3-2-1_50JLT_2021-09-18_final.stac-item
2021-10-14 12:13:45	ga_s2bm_ard_3-2-1_49KHS_2021-10-14_final
2021-10-21 12:04:48	ga_s2bm_ard_3-2-1_50JLT_2021-10-21_final.stac-item
2021-10-21 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2021-10-21_final.stac-item
2021-11-17 11:55:22	ga_s2bm_ard_3-2-1_50JMQ_2021-11-17_final.stac-item
2022-03-17 11:55:08	ga_s2bm_ard_3-2-1_50JMR_2022-03-17_final.stac-item
2022-03-30 12:04:41	ga_s2bm_ard_3-2-1_50JLT_2022-03-30_final.stac-item
2022-05-06 11:55:20	ga_s2bm_ard_3-2-1_50JMQ_2022-05-06_final.stac-item
2022-05-16 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2022-05-16_final.stac-item
2022-05-16 11:55:23	ga_s2bm_ard_3-2-1_50JMQ_2022-05-16_final.stac-item
2022-05-19 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2022-05-19_final.stac-item
2022-07-08 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2022-07-08_final.stac-item
2022-07-15 11:55:14	ga_s2bm_ard_3-2-1_50JMR_2022-07-15_final.stac-item
2022-10-16 12:04:43	ga_s2bm_ard_3-2-1_50JLT_2022-10-16_final.stac-item
2022-11-12 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2022-11-12_final.stac-item
2023-02-20 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2023-02-20_final
2023-05-11 11:54:47	ga_s2bm_ard_3-2-1_50JLT_2023-05-11_final
2023-05-21 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-05-21_final
2023-05-31 11:55:02	ga_s2bm_ard_3-2-1_50JLS_2023-05-31_final
2023-06-10 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-06-10_final
2023-06-13 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-06-13_final
2023-06-30 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-06-30_final
2023-06-30 11:55:29	ga_s2bm_ard_3-2-1_50JMQ_2023-06-30_final
2023-07-10 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-07-10_final
2023-07-10 11:55:29	ga_s2bm_ard_3-2-1_50JMQ_2023-07-10_final
2023-07-20 11:54:50	ga_s2bm_ard_3-2-1_50JLT_2023-07-20_final
2023-07-20 11:55:04	ga_s2bm_ard_3-2-1_50JLS_2023-07-20_final
2023-07-20 11:55:30	ga_s2bm_ard_3-2-1_50JMQ_2023-07-20_final
2023-07-30 11:54:50	ga_s2bm_ard_3-2-1_50JLT_2023-07-30_final
2023-07-30 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-07-30_final
2023-08-02 12:05:03	ga_s2bm_ard_3-2-1_50JMR_2023-08-02_final
2023-08-09 11:55:03	ga_s2bm_ard_3-2-1_50JLS_2023-08-09_final
2023-08-15 12:15:16	ga_s2bm_ard_3-2-1_49JGL_2023-08-15_final
2023-08-19 11:54:49	ga_s2bm_ard_3-2-1_50JLT_2023-08-19_final
2023-08-29 11:55:14	ga_s2bm_ard_3-2-1_50JMR_2023-08-29_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