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
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KHR_2015-12-30_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLG_2016-06-11_final
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50JNL_2016-06-21_final.stac-item
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49KHR_2016-08-06_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLK_2016-12-08_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JQR_2016-12-15_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50JQP_2016-12-22_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HLJ_2017-02-26_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGM_2017-07-09_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGK_2017-11-19_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMK_2017-12-03_final.stac-item
2017-12-09 12:14:36	ga_s2am_ard_3-2-1_49JGM_2017-12-09_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGP_2017-12-19_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HNH_2018-03-10_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_49JGJ_2018-05-05_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLT_2018-06-14_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JHN_2018-06-24_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JLN_2018-07-01_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JLL_2018-07-21_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50JKN_2018-07-31_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50JML_2018-08-07_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JNL_2018-09-06_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLN_2018-10-09_final.stac-item
2018-11-08 11:54:36	ga_s2am_ard_3-2-1_50JMT_2018-11-08_final.stac-item
2018-12-18 11:56:05	ga_s2am_ard_3-2-1_50JKM_2018-12-18_final.stac-item
2018-12-24 12:13:50	ga_s2am_ard_3-2-1_49KGR_2018-12-24_final.stac-item
2018-12-31 12:05:09	ga_s2am_ard_3-2-1_49JGL_2018-12-31_final.stac-item
2019-01-13 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-13_final.stac-item
2019-02-02 12:15:07	ga_s2am_ard_3-2-1_49JGL_2019-02-02_final.stac-item
2019-02-16 11:56:14	ga_s2am_ard_3-2-1_50JNL_2019-02-16_final.stac-item
2019-03-08 11:55:07	ga_s2am_ard_3-2-1_50JLR_2019-03-08_final.stac-item
2019-03-28 11:56:17	ga_s2am_ard_3-2-1_50JNL_2019-03-28_final.stac-item
2019-04-04 11:46:23	ga_s2am_ard_3-2-1_50JNL_2019-04-04_final.stac-item
2019-04-24 11:46:18	ga_s2am_ard_3-2-1_50JQL_2019-04-24_final.stac-item
2019-05-27 11:56:02	ga_s2am_ard_3-2-1_50JKN_2019-05-27_final.stac-item
2019-05-30 12:04:45	ga_s2am_ard_3-2-1_50JKT_2019-05-30_final.stac-item
2019-05-31 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2019-05-31_final.stac-item
2019-07-12 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2019-07-12_final.stac-item
2019-07-16 11:54:49	ga_s2am_ard_3-2-1_50JLT_2019-07-16_final.stac-item
2019-07-29 12:05:56	ga_s2am_ard_3-2-1_50JLN_2019-07-29_final.stac-item
2019-07-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-07-30_final.stac-item
2019-08-25 11:56:32	ga_s2am_ard_3-2-1_50HNK_2019-08-25_final.stac-item
2019-10-07 12:04:01	ga_s2am_ard_3-2-1_49KHR_2019-10-07_final.stac-item
2019-11-07 11:37:09	ga_s2am_ard_3-2-1_50HPH_2019-11-07_final.stac-item
2019-11-19 12:14:57	ga_s2am_ard_3-2-1_49JGM_2019-11-19_final.stac-item
2019-11-20 11:46:27	ga_s2am_ard_3-2-1_50JML_2019-11-20_final.stac-item
2020-02-11 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2020-02-11_final.stac-item
2020-04-01 11:57:02	ga_s2am_ard_3-2-1_50HMH_2020-04-01_final.stac-item
2020-05-11 11:56:01	ga_s2am_ard_3-2-1_50JLN_2020-05-11_final.stac-item
2020-05-14 12:05:34	ga_s2am_ard_3-2-1_49JGK_2020-05-14_final.stac-item
2020-06-06 12:15:17	ga_s2am_ard_3-2-1_49JGL_2020-06-06_final.stac-item
2020-07-30 11:55:59	ga_s2am_ard_3-2-1_50JMN_2020-07-30_final.stac-item
2020-09-18 11:55:51	ga_s2am_ard_3-2-1_50JKP_2020-09-18_final.stac-item
2020-10-21 12:04:51	ga_s2am_ard_3-2-1_49JGN_2020-10-21_final.stac-item
2021-01-02 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-01-02_final.stac-item
2021-02-09 11:37:06	ga_s2am_ard_3-2-1_50HPH_2021-02-09_final.stac-item
2021-04-03 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2021-04-03_final.stac-item
2021-05-02 12:15:04	ga_s2am_ard_3-2-1_49JGL_2021-05-02_final.stac-item
2021-07-28 12:05:11	ga_s2am_ard_3-2-1_50JLR_2021-07-28_final.stac-item
2021-08-11 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-08-11_final
2021-10-03 11:56:45	ga_s2am_ard_3-2-1_50HLK_2021-10-03_final.stac-item
2021-10-30 11:47:11	ga_s2am_ard_3-2-1_50HNH_2021-10-30_final.stac-item
2021-11-12 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2021-11-12_final.stac-item
2021-12-16 11:37:11	ga_s2am_ard_3-2-1_50HQH_2021-12-16_final.stac-item
2021-12-19 11:46:31	ga_s2am_ard_3-2-1_50JNL_2021-12-19_final.stac-item
2022-02-04 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2022-02-04_final.stac-item
2022-02-10 11:56:17	ga_s2am_ard_3-2-1_50JNL_2022-02-10_final.stac-item
2022-03-22 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-03-22_final.stac-item
2022-04-11 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-04-11_final.stac-item
2022-04-18 11:46:23	ga_s2am_ard_3-2-1_50JPL_2022-04-18_final.stac-item
2022-05-04 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2022-05-04_final.stac-item
2022-05-14 12:04:39	ga_s2am_ard_3-2-1_49KGP_2022-05-14_final.stac-item
2022-05-14 12:04:43	ga_s2am_ard_3-2-1_50JLT_2022-05-14_final.stac-item
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-06-23_final.stac-item
2022-06-26 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-06-26_final.stac-item
2022-08-09 11:55:50	ga_s2am_ard_3-2-1_50JMP_2022-08-09_final.stac-item
2022-09-18 11:57:00	ga_s2am_ard_3-2-1_50HMJ_2022-09-18_final.stac-item
2022-10-24 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-10-24_final.stac-item
2022-10-31 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-10-31_final.stac-item
2023-01-02 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-01-02_final.stac-item
2023-01-26 11:57:17	ga_s2am_ard_3-2-1_50HMG_2023-01-26_final
2023-01-29 12:05:49	ga_s2am_ard_3-2-1_50JLN_2023-01-29_final.stac-item
2023-02-18 12:06:01	ga_s2am_ard_3-2-1_50JLM_2023-02-18_nrt.stac-item
2023-02-18 12:06:01	ga_s2am_ard_3-2-1_50JLM_2023-02-18_final
2023-04-02 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-04-02_final
2023-04-03 11:45:10	ga_s2am_ard_3-2-1_50JNR_2023-04-03_final
2023-04-13 11:47:02	ga_s2am_ard_3-2-1_50HPH_2023-04-13_final
2023-04-29 12:05:01	ga_s2am_ard_3-2-1_49JGM_2023-04-29_final
2023-07-05 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-05_final
2023-07-08 12:04:33	ga_s2am_ard_3-2-1_49KHP_2023-07-08_final
2023-09-03 11:55:58	ga_s2am_ard_3-2-1_50JMN_2023-09-03_final
2023-09-30 11:47:12	ga_s2am_ard_3-2-1_50HMH_2023-09-30_final
2023-10-10 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-10-10_final
2023-11-15 12:04:26	ga_s2am_ard_3-2-1_49KHP_2023-11-15_final
2023-12-12 11:55:55	ga_s2am_ard_3-2-1_50JKN_2023-12-12_final
2023-12-15 12:05:47	ga_s2am_ard_3-2-1_50JLN_2023-12-15_final
2023-12-26 11:36:23	ga_s2am_ard_3-2-1_50JPL_2023-12-26_final
2024-03-11 11:56:30	ga_s2am_ard_3-2-1_50HNK_2024-03-11_final
2024-03-21 11:56:31	ga_s2am_ard_3-2-1_50HNK_2024-03-21_final
2024-03-24 12:05:53	ga_s2am_ard_3-2-1_50JLN_2024-03-24_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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