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
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JGN_2015-12-27_final.stac-item
2016-01-26 12:04:01	ga_s2am_ard_3-2-1_49KHQ_2016-01-26_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JLP_2016-02-02_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HMJ_2016-03-03_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JML_2016-04-02_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KHS_2016-04-15_final
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50HLK_2016-06-21_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JLP_2016-10-22_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQJ_2016-10-23_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMJ_2016-11-05_final.stac-item
2016-11-08 11:56:13	ga_s2am_ard_3-2-1_50JLM_2016-11-08_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HMH_2016-11-18_final.stac-item
2016-12-18 11:56:02	ga_s2am_ard_3-2-1_50JML_2016-12-18_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50JLM_2016-12-31_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50JLQ_2016-12-31_final.stac-item
2017-01-04 11:46:21	ga_s2am_ard_3-2-1_50HQK_2017-01-04_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HQK_2017-01-14_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HLH_2017-03-25_final.stac-item
2017-03-28 11:56:02	ga_s2am_ard_3-2-1_50JML_2017-03-28_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49JGL_2017-04-20_final.stac-item
2017-08-11 12:14:43	ga_s2am_ard_3-2-1_49JGL_2017-08-11_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HPJ_2017-11-07_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JML_2018-01-12_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-02-17_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-02-24_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HLK_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HNK_2018-03-03_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50JLP_2018-03-03_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-03-26_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLP_2018-06-01_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HNH_2018-06-08_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JLT_2018-06-24_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JLQ_2018-07-04_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLP_2018-09-19_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-10-22_final.stac-item
2018-11-15 11:46:35	ga_s2am_ard_3-2-1_50HMK_2018-11-15_final.stac-item
2019-01-04 11:46:37	ga_s2am_ard_3-2-1_50HQJ_2019-01-04_final.stac-item
2019-03-01 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-03-01_final.stac-item
2019-03-02 11:36:47	ga_s2am_ard_3-2-1_50HPJ_2019-03-02_final.stac-item
2019-03-25 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2019-03-25_final.stac-item
2019-07-19 12:04:51	ga_s2am_ard_3-2-1_49JGN_2019-07-19_final.stac-item
2019-07-19 12:05:02	ga_s2am_ard_3-2-1_50JKS_2019-07-19_final.stac-item
2019-07-26 11:55:47	ga_s2am_ard_3-2-1_50JLP_2019-07-26_final.stac-item
2019-07-26 11:55:51	ga_s2am_ard_3-2-1_50JKP_2019-07-26_final.stac-item
2019-08-15 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2019-08-15_final.stac-item
2019-09-17 12:04:39	ga_s2am_ard_3-2-1_50JLT_2019-09-17_final.stac-item
2019-11-06 12:06:12	ga_s2am_ard_3-2-1_50JKM_2019-11-06_final.stac-item
2019-11-10 11:46:43	ga_s2am_ard_3-2-1_50HMK_2019-11-10_final.stac-item
2019-11-13 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-11-13_final.stac-item
2019-11-16 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2019-11-16_final.stac-item
2019-12-27 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-12-27_final.stac-item
2020-01-29 11:46:59	ga_s2am_ard_3-2-1_50HNH_2020-01-29_final.stac-item
2020-02-08 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-02-08_final.stac-item
2020-04-04 12:05:04	ga_s2am_ard_3-2-1_50JLR_2020-04-04_final.stac-item
2020-04-24 12:04:47	ga_s2am_ard_3-2-1_49JGN_2020-04-24_final.stac-item
2020-05-01 11:56:39	ga_s2am_ard_3-2-1_50HMK_2020-05-01_final.stac-item
2020-05-04 12:04:31	ga_s2am_ard_3-2-1_49KHP_2020-05-04_final.stac-item
2020-05-21 11:56:35	ga_s2am_ard_3-2-1_50HNK_2020-05-21_final.stac-item
2020-06-23 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2020-06-23_final.stac-item
2020-08-29 11:56:41	ga_s2am_ard_3-2-1_50HMK_2020-08-29_final.stac-item
2020-09-08 11:56:44	ga_s2am_ard_3-2-1_50HLK_2020-09-08_final.stac-item
2020-10-08 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-10-08_final.stac-item
2020-10-14 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-10-14_final.stac-item
2020-11-10 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2020-11-10_final.stac-item
2020-11-30 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2020-11-30_final.stac-item
2021-01-30 11:37:26	ga_s2am_ard_3-2-1_50HNG_2021-01-30_final
2021-02-11 12:13:57	ga_s2am_ard_3-2-1_49KGR_2021-02-11_final.stac-item
2021-02-28 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-28_final
2021-03-07 11:56:06	ga_s2am_ard_3-2-1_50JLM_2021-03-07_final.stac-item
2021-03-13 12:14:20	ga_s2am_ard_3-2-1_49KHP_2021-03-13_final.stac-item
2021-04-26 11:57:01	ga_s2am_ard_3-2-1_50HMH_2021-04-26_final.stac-item
2021-04-29 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2021-04-29_final.stac-item
2021-05-26 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-05-26_final.stac-item
2021-06-25 11:57:08	ga_s2am_ard_3-2-1_50HLH_2021-06-25_final.stac-item
2021-08-24 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-08-24_final.stac-item
2021-09-23 11:55:45	ga_s2am_ard_3-2-1_50JLP_2021-09-23_final.stac-item
2021-12-22 11:55:43	ga_s2am_ard_3-2-1_50JLP_2021-12-22_final.stac-item
2021-12-22 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-12-22_final.stac-item
2022-01-21 11:56:30	ga_s2am_ard_3-2-1_50HNK_2022-01-21_final.stac-item
2022-02-10 11:57:08	ga_s2am_ard_3-2-1_50HLH_2022-02-10_final.stac-item
2022-03-05 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-03-05_final.stac-item
2022-03-15 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-03-15_final.stac-item
2022-05-14 12:04:38	ga_s2am_ard_3-2-1_50JKT_2022-05-14_final.stac-item
2022-06-30 11:56:53	ga_s2am_ard_3-2-1_50HLK_2022-06-30_final.stac-item
2022-07-23 12:04:29	ga_s2am_ard_3-2-1_49KGQ_2022-07-23_final.stac-item
2022-10-04 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-10-04_final.stac-item
2022-10-11 12:04:48	ga_s2am_ard_3-2-1_49JHN_2022-10-11_final.stac-item
2022-10-28 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-10-28_final.stac-item
2022-12-04 11:46:13	ga_s2am_ard_3-2-1_50JMM_2022-12-04_final.stac-item
2023-01-19 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-01-19_final.stac-item
2023-02-12 11:46:28	ga_s2am_ard_3-2-1_50HQK_2023-02-12_nrt.stac-item
2023-02-12 11:46:28	ga_s2am_ard_3-2-1_50HQK_2023-02-12_final
2023-05-03 11:47:17	ga_s2am_ard_3-2-1_50HPG_2023-05-03_final
2023-06-02 11:47:14	ga_s2am_ard_3-2-1_50HMH_2023-06-02_final
2023-06-19 11:36:38	ga_s2am_ard_3-2-1_50HQK_2023-06-19_final
2023-07-22 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2023-07-22_final
2023-08-24 11:55:48	ga_s2am_ard_3-2-1_50JLP_2023-08-24_final
2023-12-09 11:46:24	ga_s2am_ard_3-2-1_50HQK_2023-12-09_final
2024-01-14 12:05:20	ga_s2am_ard_3-2-1_50JKQ_2024-01-14_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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