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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HMH_2015-10-22_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HPK_2016-01-07_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JLT_2016-07-01_final.stac-item
2016-07-11 11:56:11	ga_s2am_ard_3-2-1_50HLK_2016-07-11_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKP_2016-07-14_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JLP_2016-08-23_final.stac-item
2016-11-08 11:56:06	ga_s2am_ard_3-2-1_50JNL_2016-11-08_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HNG_2016-11-12_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNJ_2016-11-15_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HPG_2016-12-22_final
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KGQ_2016-12-24_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HLK_2017-04-27_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JMN_2017-05-17_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JMM_2017-08-25_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_49KGQ_2017-11-06_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50JML_2017-11-13_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49JGN_2017-12-19_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HMH_2017-12-23_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HMH_2017-12-30_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HLK_2018-02-01_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HNJ_2018-02-28_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGM_2018-04-28_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HQK_2018-05-29_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HQH_2018-07-08_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JGL_2018-08-13_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JMP_2018-08-20_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-10-25_final.stac-item
2018-11-21 12:05:57	ga_s2am_ard_3-2-1_50JLM_2018-11-21_final.stac-item
2018-12-01 12:04:10	ga_s2am_ard_3-2-1_49KGQ_2018-12-01_final.stac-item
2018-12-02 11:36:58	ga_s2am_ard_3-2-1_50HPH_2018-12-02_final.stac-item
2018-12-18 11:55:33	ga_s2am_ard_3-2-1_50JLP_2018-12-18_final.stac-item
2018-12-18 11:55:55	ga_s2am_ard_3-2-1_50JNM_2018-12-18_final.stac-item
2018-12-25 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2018-12-25_final.stac-item
2018-12-28 11:55:35	ga_s2am_ard_3-2-1_50JLP_2018-12-28_final.stac-item
2019-01-07 11:56:17	ga_s2am_ard_3-2-1_50JML_2019-01-07_final.stac-item
2019-06-03 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2019-06-03_final.stac-item
2019-07-23 11:46:13	ga_s2am_ard_3-2-1_50JNM_2019-07-23_final.stac-item
2019-07-26 11:55:14	ga_s2am_ard_3-2-1_50JMR_2019-07-26_final.stac-item
2019-09-07 12:04:27	ga_s2am_ard_3-2-1_49KHP_2019-09-07_final.stac-item
2019-09-17 12:04:27	ga_s2am_ard_3-2-1_49KHP_2019-09-17_final.stac-item
2019-10-21 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-10-21_final.stac-item
2019-11-13 11:56:17	ga_s2am_ard_3-2-1_50JNL_2019-11-13_final.stac-item
2019-11-16 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-11-16_final.stac-item
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_50JKT_2019-12-16_final.stac-item
2019-12-23 11:56:16	ga_s2am_ard_3-2-1_50JML_2019-12-23_final.stac-item
2020-01-12 11:55:47	ga_s2am_ard_3-2-1_50JMN_2020-01-12_final.stac-item
2020-01-12 11:56:16	ga_s2am_ard_3-2-1_50JML_2020-01-12_final.stac-item
2020-03-05 12:03:59	ga_s2am_ard_3-2-1_49KHQ_2020-03-05_final.stac-item
2020-03-05 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2020-03-05_final.stac-item
2020-03-09 11:46:26	ga_s2am_ard_3-2-1_50HQK_2020-03-09_final.stac-item
2020-04-11 11:55:51	ga_s2am_ard_3-2-1_50JMN_2020-04-11_final.stac-item
2020-06-03 12:04:20	ga_s2am_ard_3-2-1_49KHQ_2020-06-03_final.stac-item
2020-06-13 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-06-13_final.stac-item
2020-08-02 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-08-02_final.stac-item
2020-10-25 11:46:31	ga_s2am_ard_3-2-1_50JML_2020-10-25_final.stac-item
2020-12-20 12:04:44	ga_s2am_ard_3-2-1_49JGN_2020-12-20_final.stac-item
2020-12-27 11:55:41	ga_s2am_ard_3-2-1_50JLP_2020-12-27_final.stac-item
2021-02-05 11:54:40	ga_s2am_ard_3-2-1_50JMT_2021-02-05_final.stac-item
2021-02-22 11:47:02	ga_s2am_ard_3-2-1_50HPH_2021-02-22_final.stac-item
2021-02-25 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-02-25_final.stac-item
2021-03-17 11:57:19	ga_s2am_ard_3-2-1_50HMG_2021-03-17_final
2021-07-18 12:04:57	ga_s2am_ard_3-2-1_50JLS_2021-07-18_final.stac-item
2021-08-04 11:55:45	ga_s2am_ard_3-2-1_50JLP_2021-08-04_final.stac-item
2021-08-11 11:46:43	ga_s2am_ard_3-2-1_50HMK_2021-08-11_final.stac-item
2021-09-07 11:37:11	ga_s2am_ard_3-2-1_50HQH_2021-09-07_final.stac-item
2021-12-26 11:36:39	ga_s2am_ard_3-2-1_50HPK_2021-12-26_final.stac-item
2022-01-01 11:56:24	ga_s2am_ard_3-2-1_50JML_2022-01-01_final.stac-item
2022-01-21 11:55:42	ga_s2am_ard_3-2-1_50JLP_2022-01-21_final.stac-item
2022-04-14 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2022-04-14_final.stac-item
2022-05-31 11:55:20	ga_s2am_ard_3-2-1_50JLR_2022-05-31_final.stac-item
2022-06-30 11:57:04	ga_s2am_ard_3-2-1_50HMJ_2022-06-30_final.stac-item
2022-08-22 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-08-22_final.stac-item
2022-09-28 11:55:54	ga_s2am_ard_3-2-1_50JKP_2022-09-28_final.stac-item
2022-10-01 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-10-01_final.stac-item
2022-10-28 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-10-28_final.stac-item
2022-11-10 12:05:00	ga_s2am_ard_3-2-1_49JHM_2022-11-10_final.stac-item
2022-11-27 11:56:22	ga_s2am_ard_3-2-1_50JML_2022-11-27_final.stac-item
2022-12-14 11:46:30	ga_s2am_ard_3-2-1_50HQK_2022-12-14_final.stac-item
2022-12-14 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-12-14_final.stac-item
2023-01-13 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-01-13_final.stac-item
2023-01-20 11:36:47	ga_s2am_ard_3-2-1_50HPJ_2023-01-20_final.stac-item
2023-01-29 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2023-01-29_final.stac-item
2023-02-09 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2023-02-09_final.stac-item
2023-02-18 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-18_nrt.stac-item
2023-02-18 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-18_final
2023-03-03 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2023-03-03_final
2023-03-07 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-03-07_final
2023-04-23 11:46:25	ga_s2am_ard_3-2-1_50JML_2023-04-23_final
2023-06-08 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-06-08_final
2023-06-25 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2023-06-25_final
2023-07-28 12:05:17	ga_s2am_ard_3-2-1_50JKR_2023-07-28_final
2023-08-04 11:55:58	ga_s2am_ard_3-2-1_50JMN_2023-08-04_final
2023-08-04 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-08-04_final
2023-10-20 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-10-20_final
2023-12-12 11:55:37	ga_s2am_ard_3-2-1_50JLP_2023-12-12_final
2024-02-10 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2024-02-10_final
2024-02-10 11:57:02	ga_s2am_ard_3-2-1_50HMH_2024-02-10_final
2024-03-24 12:03:46	ga_s2am_ard_3-2-1_49KHS_2024-03-24_final
2024-04-04 11:37:18	ga_s2am_ard_3-2-1_50HPG_2024-04-04_final
2024-04-07 11:47:05	ga_s2am_ard_3-2-1_50HNH_2024-04-07_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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