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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLP_2015-12-17_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLT_2015-12-17_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_50JLS_2015-12-27_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HQK_2016-09-26_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQH_2016-10-23_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JLS_2016-12-01_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HNG_2016-12-05_final
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-12-11_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HMK_2016-12-28_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50JLP_2017-01-20_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JLP_2017-03-11_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGN_2017-06-02_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKQ_2017-06-19_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49JGN_2017-07-29_final.stac-item
2017-08-11 12:14:43	ga_s2am_ard_3-2-1_49JGN_2017-08-11_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49KGQ_2018-01-08_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_50JLN_2018-02-14_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLM_2018-05-22_final
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HQH_2018-05-29_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HNJ_2018-06-08_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLL_2018-07-11_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JLR_2018-07-24_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50HLK_2018-08-20_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JMM_2018-10-29_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50JKR_2018-11-01_final.stac-item
2018-11-12 11:36:29	ga_s2am_ard_3-2-1_50HQK_2018-11-12_final.stac-item
2018-11-21 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2018-11-21_final.stac-item
2018-11-21 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2018-11-21_final.stac-item
2018-11-24 12:14:34	ga_s2am_ard_3-2-1_49JGN_2018-11-24_final.stac-item
2018-12-15 11:46:21	ga_s2am_ard_3-2-1_50HQK_2018-12-15_final.stac-item
2019-01-07 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-01-07_final.stac-item
2019-01-14 11:46:08	ga_s2am_ard_3-2-1_50JMM_2019-01-14_final.stac-item
2019-02-19 12:05:48	ga_s2am_ard_3-2-1_50JLN_2019-02-19_final.stac-item
2019-03-11 12:05:33	ga_s2am_ard_3-2-1_50JLP_2019-03-11_final.stac-item
2019-03-31 12:05:38	ga_s2am_ard_3-2-1_50JLP_2019-03-31_final.stac-item
2019-04-17 11:55:44	ga_s2am_ard_3-2-1_50JLP_2019-04-17_final.stac-item
2019-04-27 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-04-27_final.stac-item
2019-05-07 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2019-05-07_final.stac-item
2019-05-07 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-05-07_final.stac-item
2019-05-11 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2019-05-11_final.stac-item
2019-08-05 11:55:57	ga_s2am_ard_3-2-1_50JMN_2019-08-05_final.stac-item
2019-09-27 12:04:40	ga_s2am_ard_3-2-1_50JLT_2019-09-27_final.stac-item
2019-10-24 11:56:33	ga_s2am_ard_3-2-1_50HNK_2019-10-24_final.stac-item
2019-11-23 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-11-23_final.stac-item
2019-12-03 11:56:20	ga_s2am_ard_3-2-1_50JML_2019-12-03_final.stac-item
2019-12-19 12:14:06	ga_s2am_ard_3-2-1_49KGQ_2019-12-19_final.stac-item
2020-02-05 11:36:58	ga_s2am_ard_3-2-1_50HPH_2020-02-05_final.stac-item
2020-03-12 11:54:54	ga_s2am_ard_3-2-1_50JLS_2020-03-12_final.stac-item
2020-03-12 11:55:43	ga_s2am_ard_3-2-1_50JKP_2020-03-12_final.stac-item
2020-04-14 12:05:14	ga_s2am_ard_3-2-1_49JGL_2020-04-14_final.stac-item
2020-04-14 12:05:28	ga_s2am_ard_3-2-1_49JGK_2020-04-14_final.stac-item
2020-04-21 11:56:09	ga_s2am_ard_3-2-1_50JMM_2020-04-21_final.stac-item
2020-05-21 11:55:59	ga_s2am_ard_3-2-1_50JMN_2020-05-21_final.stac-item
2020-07-03 12:04:11	ga_s2am_ard_3-2-1_49KHR_2020-07-03_final.stac-item
2020-08-05 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-08-05_final.stac-item
2020-08-12 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2020-08-12_final.stac-item
2020-11-13 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2020-11-13_final.stac-item
2020-11-30 12:04:39	ga_s2am_ard_3-2-1_50JLT_2020-11-30_final.stac-item
2020-12-17 11:56:20	ga_s2am_ard_3-2-1_50JML_2020-12-17_final.stac-item
2021-02-02 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-02-02_final.stac-item
2021-04-06 11:56:18	ga_s2am_ard_3-2-1_50JML_2021-04-06_final.stac-item
2021-04-26 11:56:19	ga_s2am_ard_3-2-1_50JML_2021-04-26_final.stac-item
2021-05-06 11:55:40	ga_s2am_ard_3-2-1_50JLP_2021-05-06_final.stac-item
2021-08-04 11:56:28	ga_s2am_ard_3-2-1_50JLL_2021-08-04_final.stac-item
2021-09-26 12:04:46	ga_s2am_ard_3-2-1_49JHN_2021-09-26_final.stac-item
2021-10-17 11:37:23	ga_s2am_ard_3-2-1_50HQG_2021-10-17_final
2021-11-05 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2021-11-05_final.stac-item
2021-12-29 11:46:14	ga_s2am_ard_3-2-1_50JMM_2021-12-29_final.stac-item
2022-01-08 11:47:11	ga_s2am_ard_3-2-1_50HMH_2022-01-08_final.stac-item
2022-01-18 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-01-18_final.stac-item
2022-02-10 11:56:21	ga_s2am_ard_3-2-1_50JML_2022-02-10_final.stac-item
2022-03-15 12:04:58	ga_s2am_ard_3-2-1_50JLS_2022-03-15_final.stac-item
2022-03-19 11:46:33	ga_s2am_ard_3-2-1_50HQK_2022-03-19_final.stac-item
2022-03-22 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-03-22_final.stac-item
2022-04-14 12:05:54	ga_s2am_ard_3-2-1_50JLN_2022-04-14_final.stac-item
2022-05-01 11:56:27	ga_s2am_ard_3-2-1_50JML_2022-05-01_final.stac-item
2022-07-13 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-07-13_final.stac-item
2022-08-05 12:14:20	ga_s2am_ard_3-2-1_49KHQ_2022-08-05_final.stac-item
2022-12-07 11:57:06	ga_s2am_ard_3-2-1_50HMH_2022-12-07_final.stac-item
2022-12-23 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2022-12-23_final.stac-item
2023-01-09 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-01-09_final.stac-item
2023-02-25 11:56:20	ga_s2am_ard_3-2-1_50JML_2023-02-25_final
2023-08-04 11:57:11	ga_s2am_ard_3-2-1_50HMH_2023-08-04_final
2023-08-14 11:56:42	ga_s2am_ard_3-2-1_50HMK_2023-08-14_final
2023-09-16 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-09-16_final
2023-09-26 12:05:40	ga_s2am_ard_3-2-1_50JLP_2023-09-26_final
2023-10-07 11:37:03	ga_s2am_ard_3-2-1_50HQH_2023-10-07_final
2023-10-17 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2023-10-17_final
2023-11-12 11:55:41	ga_s2am_ard_3-2-1_50JLP_2023-11-12_final
2023-11-19 11:46:10	ga_s2am_ard_3-2-1_50JMM_2023-11-19_final
2023-11-25 12:05:32	ga_s2am_ard_3-2-1_50JLP_2023-11-25_final
2024-01-01 11:56:05	ga_s2am_ard_3-2-1_50JMM_2024-01-01_final
2024-01-08 11:47:05	ga_s2am_ard_3-2-1_50HMH_2024-01-08_final
2024-01-18 11:46:21	ga_s2am_ard_3-2-1_50HQK_2024-01-18_final
2024-01-21 11:55:34	ga_s2am_ard_3-2-1_50JLP_2024-01-21_final
2024-01-25 11:37:11	ga_s2am_ard_3-2-1_50HQG_2024-01-25_final
2024-03-21 11:57:10	ga_s2am_ard_3-2-1_50HLH_2024-03-21_final
2024-04-27 11:46:32	ga_s2am_ard_3-2-1_50HQK_2024-04-27_final
2024-04-27 11:47:12	ga_s2am_ard_3-2-1_50HMH_2024-04-27_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

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