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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HNG_2015-11-21_final
2015-12-28 11:36:25	ga_s2am_ard_3-2-1_50JPL_2015-12-28_final.stac-item
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JFN_2016-07-07_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2016-12-14_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50JNL_2017-02-03_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KGP_2017-03-14_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50JKP_2017-04-27_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HLJ_2017-04-27_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_50JKT_2017-05-20_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGP_2017-07-12_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50JPL_2017-07-30_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50JNN_2017-09-01_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JLN_2017-10-04_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HLH_2017-10-24_final.stac-item
2017-11-23 11:56:04	ga_s2am_ard_3-2-1_50JLM_2017-11-23_final.stac-item
2018-01-18 12:14:35	ga_s2am_ard_3-2-1_49JGL_2018-01-18_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JLN_2018-04-05_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-04-15_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HMJ_2018-05-02_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50HLJ_2018-07-01_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HPK_2018-07-18_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HMH_2018-09-06_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLN_2018-10-22_final.stac-item
2018-11-15 11:46:57	ga_s2am_ard_3-2-1_50HPH_2018-11-15_final.stac-item
2018-11-24 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-11-24_final.stac-item
2018-12-11 12:05:06	ga_s2am_ard_3-2-1_49JGL_2018-12-11_final.stac-item
2018-12-18 11:56:21	ga_s2am_ard_3-2-1_50HNK_2018-12-18_final.stac-item
2018-12-21 12:04:23	ga_s2am_ard_3-2-1_49KGP_2018-12-21_final.stac-item
2018-12-28 11:56:33	ga_s2am_ard_3-2-1_50HLK_2018-12-28_final.stac-item
2018-12-31 12:05:45	ga_s2am_ard_3-2-1_50JLN_2018-12-31_final.stac-item
2019-01-01 11:37:00	ga_s2am_ard_3-2-1_50HPH_2019-01-01_final.stac-item
2019-03-05 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2019-03-05_final.stac-item
2019-03-12 11:36:58	ga_s2am_ard_3-2-1_50HQH_2019-03-12_final.stac-item
2019-03-31 12:03:59	ga_s2am_ard_3-2-1_49KHR_2019-03-31_final.stac-item
2019-04-21 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2019-04-21_final.stac-item
2019-05-21 11:37:06	ga_s2am_ard_3-2-1_50HQH_2019-05-21_final.stac-item
2019-05-31 11:36:40	ga_s2am_ard_3-2-1_50HPK_2019-05-31_final.stac-item
2019-06-29 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2019-06-29_final.stac-item
2019-06-29 12:04:36	ga_s2am_ard_3-2-1_49KGP_2019-06-29_final.stac-item
2019-07-02 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2019-07-02_final.stac-item
2019-08-02 11:45:29	ga_s2am_ard_3-2-1_50JNQ_2019-08-02_final.stac-item
2019-08-15 11:55:56	ga_s2am_ard_3-2-1_50JMN_2019-08-15_final.stac-item
2019-08-25 11:56:42	ga_s2am_ard_3-2-1_50HLK_2019-08-25_final.stac-item
2019-10-10 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-10-10_final.stac-item
2019-10-20 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-10-20_final.stac-item
2019-11-17 11:37:08	ga_s2am_ard_3-2-1_50HPH_2019-11-17_final.stac-item
2019-11-20 11:47:11	ga_s2am_ard_3-2-1_50HMH_2019-11-20_final.stac-item
2020-01-08 12:14:21	ga_s2am_ard_3-2-1_49KGP_2020-01-08_final.stac-item
2020-03-22 11:55:56	ga_s2am_ard_3-2-1_50JKN_2020-03-22_final.stac-item
2020-07-03 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-07-03_final.stac-item
2020-07-23 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-07-23_final.stac-item
2020-09-28 11:55:47	ga_s2am_ard_3-2-1_50JLP_2020-09-28_final.stac-item
2020-12-07 11:56:28	ga_s2am_ard_3-2-1_50HNK_2020-12-07_final.stac-item
2021-01-19 12:04:32	ga_s2am_ard_3-2-1_49KGP_2021-01-19_final.stac-item
2021-01-19 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2021-01-19_final.stac-item
2021-01-23 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-23_final.stac-item
2021-01-29 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-01-29_final.stac-item
2021-02-02 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-02-02_final
2021-02-05 11:56:04	ga_s2am_ard_3-2-1_50JNM_2021-02-05_final.stac-item
2021-02-15 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2021-02-15_final.stac-item
2021-03-20 12:05:14	ga_s2am_ard_3-2-1_49JGL_2021-03-20_final.stac-item
2021-04-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2021-04-22_final.stac-item
2021-05-10 11:36:33	ga_s2am_ard_3-2-1_50HQK_2021-05-10_final.stac-item
2021-06-28 12:05:13	ga_s2am_ard_3-2-1_50JKR_2021-06-28_final.stac-item
2021-07-02 11:47:26	ga_s2am_ard_3-2-1_50HMG_2021-07-02_final
2021-07-25 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2021-07-25_final.stac-item
2021-09-29 12:14:45	ga_s2am_ard_3-2-1_49JGN_2021-09-29_final.stac-item
2021-10-16 12:05:02	ga_s2am_ard_3-2-1_50JKS_2021-10-16_final.stac-item
2022-01-17 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-01-17_final.stac-item
2022-01-21 11:56:18	ga_s2am_ard_3-2-1_50JNL_2022-01-21_final.stac-item
2022-02-23 12:04:33	ga_s2am_ard_3-2-1_49KGP_2022-02-23_final.stac-item
2022-02-27 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2022-02-27_final.stac-item
2022-03-09 11:47:06	ga_s2am_ard_3-2-1_50HPH_2022-03-09_final.stac-item
2022-05-11 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-05-11_final.stac-item
2022-05-11 11:56:40	ga_s2am_ard_3-2-1_50HMK_2022-05-11_final.stac-item
2022-06-27 11:47:19	ga_s2am_ard_3-2-1_50HNH_2022-06-27_final.stac-item
2022-08-12 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-08-12_final.stac-item
2022-08-16 11:45:19	ga_s2am_ard_3-2-1_50JPR_2022-08-16_final.stac-item
2022-09-11 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-09-11_final.stac-item
2022-12-20 12:04:44	ga_s2am_ard_3-2-1_49JGN_2022-12-20_final.stac-item
2023-01-26 11:56:37	ga_s2am_ard_3-2-1_50HLK_2023-01-26_final.stac-item
2023-01-26 11:57:20	ga_s2am_ard_3-2-1_50HLG_2023-01-26_final
2023-02-02 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-02-02_final
2023-02-21 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-02-21_nrt.stac-item
2023-02-21 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-02-21_final
2023-03-14 11:46:34	ga_s2am_ard_3-2-1_50HNK_2023-03-14_final
2023-04-19 12:05:54	ga_s2am_ard_3-2-1_50JKN_2023-04-19_final
2023-05-22 12:15:02	ga_s2am_ard_3-2-1_49JFM_2023-05-22_final
2023-06-21 12:14:45	ga_s2am_ard_3-2-1_49JGN_2023-06-21_final
2023-06-25 11:56:39	ga_s2am_ard_3-2-1_50HMK_2023-06-25_final
2023-08-20 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-08-20_final
2023-10-03 11:56:20	ga_s2am_ard_3-2-1_50JNL_2023-10-03_final
2023-10-13 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-10-13_final
2023-10-19 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-10-19_final
2023-11-25 12:04:22	ga_s2am_ard_3-2-1_49KHP_2023-11-25_final
2023-12-08 12:15:05	ga_s2am_ard_3-2-1_49JGL_2023-12-08_final
2023-12-09 11:47:01	ga_s2am_ard_3-2-1_50HNH_2023-12-09_final
2024-01-04 12:04:28	ga_s2am_ard_3-2-1_49KGP_2024-01-04_final
2024-01-15 11:36:41	ga_s2am_ard_3-2-1_50HQJ_2024-01-15_final
2024-03-04 12:04:32	ga_s2am_ard_3-2-1_49KGP_2024-03-04_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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