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
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNJ_2016-06-18_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JGM_2016-06-24_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMK_2016-07-08_final.stac-item
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_49KHR_2016-08-13_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KKB_2016-10-22_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JLL_2016-10-29_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKQ_2016-11-11_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50KNC_2017-01-07_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JMS_2017-02-16_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50JKN_2017-04-27_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JFM_2017-08-01_final.stac-item
2017-11-16 12:04:39	ga_s2am_ard_3-2-1_50JKT_2017-11-16_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2017-11-19_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JGN_2018-01-08_final.stac-item
2018-01-26 11:36:13	ga_s2am_ard_3-2-1_50JPL_2018-01-26_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HQK_2018-02-18_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KKV_2018-03-06_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HLK_2018-03-13_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGN_2018-04-05_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JLN_2018-05-12_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKS_2018-05-25_final.stac-item
2018-06-07 12:13:28	ga_s2am_ard_3-2-1_49JGK_2018-06-07_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGQ_2018-09-05_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JKN_2018-09-29_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-10-05_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JNL_2018-10-29_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_50JKQ_2018-11-01_final.stac-item
2018-11-21 12:03:37	ga_s2am_ard_3-2-1_50KKB_2018-11-21_final.stac-item
2018-11-22 11:36:41	ga_s2am_ard_3-2-1_50HQJ_2018-11-22_final.stac-item
2019-01-03 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-01-03_final.stac-item
2019-01-17 11:53:32	ga_s2am_ard_3-2-1_50KPB_2019-01-17_final.stac-item
2019-01-23 12:13:51	ga_s2am_ard_3-2-1_50KKA_2019-01-23_final.stac-item
2019-02-09 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-02-09_final.stac-item
2019-03-05 11:46:35	ga_s2am_ard_3-2-1_50HMK_2019-03-05_final.stac-item
2019-04-24 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-04-24_final.stac-item
2019-06-12 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-06-12_final.stac-item
2019-09-07 12:03:58	ga_s2am_ard_3-2-1_49KHR_2019-09-07_final.stac-item
2019-10-04 11:53:19	ga_s2am_ard_3-2-1_50KQC_2019-10-04_final.stac-item
2019-10-24 11:53:24	ga_s2am_ard_3-2-1_50KPC_2019-10-24_final.stac-item
2019-11-13 11:56:32	ga_s2am_ard_3-2-1_50HNK_2019-11-13_final.stac-item
2019-11-16 12:05:57	ga_s2am_ard_3-2-1_50JKN_2019-11-16_final.stac-item
2019-12-09 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-12-09_final.stac-item
2019-12-16 12:03:39	ga_s2am_ard_3-2-1_50KKB_2019-12-16_final.stac-item
2020-01-02 11:56:20	ga_s2am_ard_3-2-1_50JLL_2020-01-02_final.stac-item
2020-01-25 12:03:52	ga_s2am_ard_3-2-1_49KHR_2020-01-25_final.stac-item
2020-02-04 12:03:51	ga_s2am_ard_3-2-1_49KHR_2020-02-04_final.stac-item
2020-03-05 12:04:00	ga_s2am_ard_3-2-1_49KHR_2020-03-05_final.stac-item
2020-03-05 12:05:36	ga_s2am_ard_3-2-1_50JKP_2020-03-05_final.stac-item
2020-03-25 12:04:01	ga_s2am_ard_3-2-1_49KHR_2020-03-25_final.stac-item
2020-05-04 12:05:18	ga_s2am_ard_3-2-1_49JGL_2020-05-04_final.stac-item
2020-07-10 11:53:21	ga_s2am_ard_3-2-1_50KQC_2020-07-10_final.stac-item
2020-07-23 12:04:19	ga_s2am_ard_3-2-1_50KKV_2020-07-23_final.stac-item
2020-09-11 12:04:17	ga_s2am_ard_3-2-1_50KKV_2020-09-11_final.stac-item
2020-09-18 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-09-18_final.stac-item
2020-10-12 11:37:02	ga_s2am_ard_3-2-1_50HPJ_2020-10-12_final.stac-item
2020-10-21 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-10-21_final.stac-item
2020-11-23 12:15:01	ga_s2am_ard_3-2-1_49JFM_2020-11-23_final.stac-item
2021-01-12 12:13:55	ga_s2am_ard_3-2-1_50KKA_2021-01-12_final.stac-item
2021-02-21 12:13:58	ga_s2am_ard_3-2-1_49KGR_2021-02-21_final.stac-item
2021-02-28 12:05:55	ga_s2am_ard_3-2-1_50JKN_2021-02-28_final.stac-item
2021-07-08 12:05:54	ga_s2am_ard_3-2-1_50JLN_2021-07-08_final.stac-item
2021-08-11 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-08-11_final
2021-09-16 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2021-09-16_final.stac-item
2021-09-26 12:05:04	ga_s2am_ard_3-2-1_49JGM_2021-09-26_final.stac-item
2021-10-16 12:03:29	ga_s2am_ard_3-2-1_50KMC_2021-10-16_final.stac-item
2021-10-26 12:04:04	ga_s2am_ard_3-2-1_49KHR_2021-10-26_final.stac-item
2021-12-15 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-12-15_final.stac-item
2022-01-11 11:56:19	ga_s2am_ard_3-2-1_50JNL_2022-01-11_final.stac-item
2022-01-18 11:46:19	ga_s2am_ard_3-2-1_50JPL_2022-01-18_final.stac-item
2022-01-21 11:55:56	ga_s2am_ard_3-2-1_50JLN_2022-01-21_final.stac-item
2022-04-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2022-04-25_final.stac-item
2022-05-08 11:43:40	ga_s2am_ard_3-2-1_50KQB_2022-05-08_final.stac-item
2022-06-17 11:47:21	ga_s2am_ard_3-2-1_50HMH_2022-06-17_final.stac-item
2022-06-26 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-06-26_final.stac-item
2022-08-02 12:04:35	ga_s2am_ard_3-2-1_49KHP_2022-08-02_final.stac-item
2022-08-06 11:46:34	ga_s2am_ard_3-2-1_50JNL_2022-08-06_final.stac-item
2022-08-09 11:57:21	ga_s2am_ard_3-2-1_50HLH_2022-08-09_final.stac-item
2022-10-04 12:15:03	ga_s2am_ard_3-2-1_49JGM_2022-10-04_final.stac-item
2022-10-24 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2022-10-24_final.stac-item
2022-11-10 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-11-10_final.stac-item
2022-12-20 12:05:36	ga_s2am_ard_3-2-1_50JLP_2022-12-20_final.stac-item
2023-01-19 12:04:55	ga_s2am_ard_3-2-1_49JGM_2023-01-19_final.stac-item
2023-02-01 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-02-01_final.stac-item
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_nrt.stac-item
2023-03-17 11:53:33	ga_s2am_ard_3-2-1_50KPB_2023-03-17_final
2023-04-23 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-04-23_final
2023-05-13 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-05-13_final
2023-06-08 12:05:44	ga_s2am_ard_3-2-1_50JKP_2023-06-08_final
2023-07-08 12:03:46	ga_s2am_ard_3-2-1_50KLB_2023-07-08_final
2023-07-08 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2023-07-08_final
2023-07-18 12:04:44	ga_s2am_ard_3-2-1_50JLT_2023-07-18_final
2023-07-18 12:05:56	ga_s2am_ard_3-2-1_50JLN_2023-07-18_final
2023-08-01 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-01_final
2023-10-06 12:05:30	ga_s2am_ard_3-2-1_49JGK_2023-10-06_final
2023-10-06 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2023-10-06_final
2023-10-26 12:05:01	ga_s2am_ard_3-2-1_49JGM_2023-10-26_final
2023-12-09 11:44:43	ga_s2am_ard_3-2-1_50JQS_2023-12-09_final
2023-12-29 11:46:10	ga_s2am_ard_3-2-1_50JMM_2023-12-29_final
2024-01-14 12:03:52	ga_s2am_ard_3-2-1_50KKA_2024-01-14_final
2024-04-23 12:03:47	ga_s2am_ard_3-2-1_50KKB_2024-04-23_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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