Search ga_s2am_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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JHM_2015-10-28_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHP_2015-10-28_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JKS_2016-03-16_final.stac-item
2016-05-26 11:36:09	ga_s2am_ard_3-2-1_50HQK_2016-05-26_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JKT_2016-06-24_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JLT_2016-08-23_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2016-09-12_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50JMM_2016-11-05_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLG_2016-11-28_final
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HMK_2017-01-14_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HMK_2017-01-24_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50HMK_2017-03-08_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHQ_2017-03-14_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_50JKT_2017-07-19_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JKQ_2017-08-18_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JKR_2017-09-27_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JKS_2017-11-06_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50JKR_2017-11-26_final.stac-item
2018-01-02 11:56:01	ga_s2am_ard_3-2-1_50HMK_2018-01-02_final.stac-item
2018-01-22 11:56:02	ga_s2am_ard_3-2-1_50HMK_2018-01-22_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JLQ_2018-02-11_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JMT_2018-02-24_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-02-27_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49JHM_2018-03-16_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HQH_2018-03-20_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMH_2018-03-30_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HMK_2018-04-02_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HMJ_2018-05-22_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLR_2018-06-21_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JHM_2018-09-02_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKS_2018-10-12_final.stac-item
2018-11-14 12:14:15	ga_s2am_ard_3-2-1_49KHP_2018-11-14_final.stac-item
2018-11-24 12:14:14	ga_s2am_ard_3-2-1_49KHP_2018-11-24_final.stac-item
2018-12-01 12:04:48	ga_s2am_ard_3-2-1_50JKS_2018-12-01_final.stac-item
2018-12-08 11:55:30	ga_s2am_ard_3-2-1_50JMP_2018-12-08_final.stac-item
2018-12-11 12:04:45	ga_s2am_ard_3-2-1_50JLS_2018-12-11_final.stac-item
2018-12-22 11:36:26	ga_s2am_ard_3-2-1_50HQK_2018-12-22_final.stac-item
2018-12-31 12:04:51	ga_s2am_ard_3-2-1_50JKS_2018-12-31_final.stac-item
2019-03-15 11:46:37	ga_s2am_ard_3-2-1_50HMK_2019-03-15_final.stac-item
2019-03-15 11:47:13	ga_s2am_ard_3-2-1_50HLH_2019-03-15_final.stac-item
2019-03-25 11:47:09	ga_s2am_ard_3-2-1_50HMH_2019-03-25_final.stac-item
2019-04-24 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2019-04-24_final.stac-item
2019-04-27 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2019-04-27_final.stac-item
2019-05-20 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-05-20_final.stac-item
2019-06-29 12:05:01	ga_s2am_ard_3-2-1_49JHM_2019-06-29_final.stac-item
2019-06-29 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2019-06-29_final.stac-item
2019-07-29 12:05:27	ga_s2am_ard_3-2-1_49JGK_2019-07-29_final.stac-item
2019-08-01 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2019-08-01_final.stac-item
2019-08-08 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2019-08-08_final.stac-item
2019-08-25 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2019-08-25_final.stac-item
2019-09-07 12:04:56	ga_s2am_ard_3-2-1_49JHM_2019-09-07_final.stac-item
2019-10-10 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2019-10-10_final.stac-item
2019-12-16 12:04:51	ga_s2am_ard_3-2-1_49JHM_2019-12-16_final.stac-item
2019-12-20 11:45:48	ga_s2am_ard_3-2-1_50JNN_2019-12-20_final.stac-item
2020-01-05 12:04:51	ga_s2am_ard_3-2-1_50JKS_2020-01-05_final.stac-item
2020-01-19 11:45:48	ga_s2am_ard_3-2-1_50JNN_2020-01-19_final.stac-item
2020-03-05 12:04:52	ga_s2am_ard_3-2-1_49JHM_2020-03-05_final.stac-item
2020-04-01 11:54:40	ga_s2am_ard_3-2-1_50JLT_2020-04-01_final.stac-item
2020-04-21 11:54:41	ga_s2am_ard_3-2-1_50JMT_2020-04-21_final.stac-item
2020-04-24 12:04:41	ga_s2am_ard_3-2-1_50JLT_2020-04-24_final.stac-item
2020-05-01 11:55:52	ga_s2am_ard_3-2-1_50JNN_2020-05-01_final.stac-item
2020-07-27 11:45:59	ga_s2am_ard_3-2-1_50JNN_2020-07-27_final.stac-item
2021-04-23 11:47:10	ga_s2am_ard_3-2-1_50HLH_2021-04-23_final.stac-item
2021-05-03 11:46:39	ga_s2am_ard_3-2-1_50HMK_2021-05-03_final.stac-item
2021-06-28 12:04:55	ga_s2am_ard_3-2-1_50JLS_2021-06-28_final.stac-item
2021-07-09 11:37:14	ga_s2am_ard_3-2-1_50HQG_2021-07-09_final
2021-07-25 11:55:16	ga_s2am_ard_3-2-1_50JLR_2021-07-25_final.stac-item
2021-07-28 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-28_final
2021-08-20 12:14:23	ga_s2am_ard_3-2-1_49KHP_2021-08-20_final.stac-item
2021-09-13 11:54:56	ga_s2am_ard_3-2-1_50JMS_2021-09-13_final.stac-item
2021-09-20 11:47:17	ga_s2am_ard_3-2-1_50HLH_2021-09-20_final.stac-item
2021-11-08 12:14:24	ga_s2am_ard_3-2-1_49KHP_2021-11-08_final.stac-item
2021-12-09 11:45:52	ga_s2am_ard_3-2-1_50JNN_2021-12-09_final.stac-item
2022-03-12 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-12_final.stac-item
2022-03-22 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-22_final.stac-item
2022-04-14 12:05:00	ga_s2am_ard_3-2-1_50JKS_2022-04-14_final.stac-item
2022-04-24 12:05:02	ga_s2am_ard_3-2-1_50JKS_2022-04-24_final.stac-item
2022-05-01 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2022-05-01_final.stac-item
2022-05-04 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2022-05-04_final.stac-item
2022-07-13 12:04:52	ga_s2am_ard_3-2-1_50JLT_2022-07-13_final.stac-item
2022-07-23 12:05:34	ga_s2am_ard_3-2-1_50JLQ_2022-07-23_final.stac-item
2022-09-21 12:04:40	ga_s2am_ard_3-2-1_49JHN_2022-09-21_final.stac-item
2022-09-28 11:55:46	ga_s2am_ard_3-2-1_50JMP_2022-09-28_final.stac-item
2022-11-07 11:54:44	ga_s2am_ard_3-2-1_50JMT_2022-11-07_final.stac-item
2023-02-19 11:37:23	ga_s2am_ard_3-2-1_50HNG_2023-02-19_final
2023-04-19 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-04-19_final
2023-05-09 12:04:23	ga_s2am_ard_3-2-1_49KHP_2023-05-09_final
2023-06-08 12:05:01	ga_s2am_ard_3-2-1_50JKS_2023-06-08_final
2023-06-08 12:05:15	ga_s2am_ard_3-2-1_50JKR_2023-06-08_final
2023-08-01 11:47:15	ga_s2am_ard_3-2-1_50HMH_2023-08-01_final
2023-09-23 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2023-09-23_final
2023-10-06 12:04:55	ga_s2am_ard_3-2-1_50JLS_2023-10-06_final
2023-10-20 11:46:53	ga_s2am_ard_3-2-1_50HQH_2023-10-20_final
2023-11-18 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2023-11-18_final
2023-12-28 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2023-12-28_final
2023-12-28 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-12-28_final
2024-01-11 11:55:04	ga_s2am_ard_3-2-1_50JMR_2024-01-11_final
2024-02-06 12:13:36	ga_s2am_ard_3-2-1_49KHS_2024-02-06_final
2024-03-11 11:57:22	ga_s2am_ard_3-2-1_50HLG_2024-03-11_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A 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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