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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_50KKA_2015-11-30_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51JUF_2016-04-06_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_51KTT_2016-04-19_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHR_2016-07-14_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGL_2017-03-21_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51JWJ_2017-04-28_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JNL_2017-06-26_final.stac-item
2017-07-30 11:28:34	ga_s2am_ard_3-2-1_51JVM_2017-07-30_final.stac-item
2017-08-15 11:56:09	ga_s2am_ard_3-2-1_50JMM_2017-08-15_final.stac-item
2017-08-19 11:30:19	ga_s2am_ard_3-2-1_50JQL_2017-08-19_final.stac-item
2017-10-18 11:36:29	ga_s2am_ard_3-2-1_50HQJ_2017-10-18_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KUT_2017-10-31_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KVT_2017-10-31_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_51KTS_2018-01-19_final.stac-item
2018-03-30 11:39:33	ga_s2am_ard_3-2-1_51KUR_2018-03-30_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_51JVH_2018-04-16_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HQJ_2018-07-18_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51HUC_2018-09-20_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JKR_2018-10-02_final.stac-item
2018-11-09 11:24:59	ga_s2am_ard_3-2-1_51JVL_2018-11-09_final.stac-item
2019-01-23 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-23_final.stac-item
2019-01-27 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2019-01-27_final.stac-item
2019-01-30 12:03:34	ga_s2am_ard_3-2-1_50KMB_2019-01-30_final.stac-item
2019-02-26 11:53:06	ga_s2am_ard_3-2-1_50KRC_2019-02-26_final.stac-item
2019-04-20 12:04:02	ga_s2am_ard_3-2-1_50KKA_2019-04-20_final.stac-item
2019-04-21 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-04-21_final.stac-item
2019-06-27 11:26:48	ga_s2am_ard_3-2-1_51HVD_2019-06-27_final.stac-item
2019-06-29 12:03:24	ga_s2am_ard_3-2-1_50KNC_2019-06-29_final.stac-item
2019-08-28 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-08-28_final.stac-item
2019-10-01 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-10-01_final.stac-item
2019-10-27 12:04:31	ga_s2am_ard_3-2-1_50KKU_2019-10-27_final.stac-item
2019-11-20 11:44:14	ga_s2am_ard_3-2-1_51KUP_2019-11-20_final.stac-item
2019-11-27 11:34:32	ga_s2am_ard_3-2-1_51JUN_2019-11-27_final.stac-item
2019-12-24 11:26:48	ga_s2am_ard_3-2-1_51HUD_2019-12-24_final.stac-item
2019-12-31 11:14:18	ga_s2am_ard_3-2-1_51JZN_2019-12-31_final.stac-item
2020-02-05 11:34:06	ga_s2am_ard_3-2-1_51KVP_2020-02-05_final.stac-item
2020-02-18 11:46:30	ga_s2am_ard_3-2-1_50HNK_2020-02-18_final.stac-item
2020-03-06 11:36:06	ga_s2am_ard_3-2-1_51JVF_2020-03-06_final.stac-item
2020-04-08 11:43:16	ga_s2am_ard_3-2-1_50KRC_2020-04-08_final.stac-item
2020-04-24 12:04:29	ga_s2am_ard_3-2-1_50KKU_2020-04-24_final.stac-item
2020-05-07 12:15:14	ga_s2am_ard_3-2-1_49JGL_2020-05-07_final.stac-item
2020-07-07 11:43:48	ga_s2am_ard_3-2-1_51KUR_2020-07-07_final.stac-item
2020-08-16 11:46:14	ga_s2am_ard_3-2-1_50JNM_2020-08-16_final.stac-item
2020-08-19 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-08-19_final.stac-item
2020-08-23 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-08-23_final.stac-item
2020-10-08 11:56:28	ga_s2am_ard_3-2-1_50JML_2020-10-08_final.stac-item
2020-12-01 11:34:25	ga_s2am_ard_3-2-1_51JWN_2020-12-01_final.stac-item
2020-12-04 11:42:12	ga_s2am_ard_3-2-1_51KVB_2020-12-04_final.stac-item
2021-02-19 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2021-02-19_final.stac-item
2021-02-28 12:04:31	ga_s2am_ard_3-2-1_49KGP_2021-02-28_final.stac-item
2021-04-13 11:46:24	ga_s2am_ard_3-2-1_50HQK_2021-04-13_final.stac-item
2021-04-19 12:04:55	ga_s2am_ard_3-2-1_49JGM_2021-04-19_final.stac-item
2021-04-22 12:14:52	ga_s2am_ard_3-2-1_49JGM_2021-04-22_final.stac-item
2021-05-06 11:56:39	ga_s2am_ard_3-2-1_50HLK_2021-05-06_final.stac-item
2021-06-01 12:14:21	ga_s2am_ard_3-2-1_50KKU_2021-06-01_final.stac-item
2021-06-09 11:34:58	ga_s2am_ard_3-2-1_51JVL_2021-06-09_final.stac-item
2021-06-21 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-21_final.stac-item
2021-07-19 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2021-07-19_final.stac-item
2021-07-22 11:45:21	ga_s2am_ard_3-2-1_50JQQ_2021-07-22_final.stac-item
2021-08-10 12:15:22	ga_s2am_ard_3-2-1_49JGK_2021-08-10_final.stac-item
2021-08-27 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2021-08-27_final.stac-item
2021-09-20 11:46:03	ga_s2am_ard_3-2-1_50JQM_2021-09-20_final.stac-item
2021-09-24 11:26:50	ga_s2am_ard_3-2-1_51HUD_2021-09-24_final.stac-item
2021-10-23 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2021-10-23_final.stac-item
2021-11-03 11:26:58	ga_s2am_ard_3-2-1_51HWC_2021-11-03_final
2021-12-06 11:34:39	ga_s2am_ard_3-2-1_51JWM_2021-12-06_final.stac-item
2022-01-05 11:34:27	ga_s2am_ard_3-2-1_51JWN_2022-01-05_final.stac-item
2022-05-02 11:27:03	ga_s2am_ard_3-2-1_51HVC_2022-05-02_final.stac-item
2022-06-07 11:42:21	ga_s2am_ard_3-2-1_51KVB_2022-06-07_final.stac-item
2022-07-04 11:32:32	ga_s2am_ard_3-2-1_51KVB_2022-07-04_final.stac-item
2022-10-14 12:13:59	ga_s2am_ard_3-2-1_50KKA_2022-10-14_final.stac-item
2023-01-09 12:05:13	ga_s2am_ard_3-2-1_49JGL_2023-01-09_final.stac-item
2023-02-18 12:05:07	ga_s2am_ard_3-2-1_50JKR_2023-02-18_nrt.stac-item
2023-02-19 11:33:31	ga_s2am_ard_3-2-1_51KUS_2023-02-19_final
2023-03-13 12:14:52	ga_s2am_ard_3-2-1_49JGM_2023-03-13_final
2023-03-17 11:53:22	ga_s2am_ard_3-2-1_50KNC_2023-03-17_final
2023-03-27 11:57:07	ga_s2am_ard_3-2-1_50HLH_2023-03-27_final
2023-04-27 11:24:19	ga_s2am_ard_3-2-1_51JZN_2023-04-27_final
2023-05-09 12:03:26	ga_s2am_ard_3-2-1_50KLC_2023-05-09_final
2023-08-05 11:24:42	ga_s2am_ard_3-2-1_51JYM_2023-08-05_final
2023-08-11 11:43:05	ga_s2am_ard_3-2-1_51KUU_2023-08-11_final
2023-09-09 12:14:00	ga_s2am_ard_3-2-1_49KHR_2023-09-09_final
2023-09-17 11:36:30	ga_s2am_ard_3-2-1_50JPL_2023-09-17_final
2023-09-30 11:44:00	ga_s2am_ard_3-2-1_51KUQ_2023-09-30_final
2023-10-13 11:53:22	ga_s2am_ard_3-2-1_50KNC_2023-10-13_final
2023-10-27 11:34:15	ga_s2am_ard_3-2-1_51JXN_2023-10-27_final
2023-11-05 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-11-05_final
2023-12-16 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2023-12-16_final
2024-01-22 11:26:54	ga_s2am_ard_3-2-1_51HUC_2024-01-22_final
2024-02-06 12:14:56	ga_s2am_ard_3-2-1_49JFM_2024-02-06_final
2024-02-24 11:33:58	ga_s2am_ard_3-2-1_51KVQ_2024-02-24_final
2024-03-11 11:53:17	ga_s2am_ard_3-2-1_50KQC_2024-03-11_final
2024-03-21 11:55:47	ga_s2am_ard_3-2-1_50JKP_2024-03-21_final
2024-03-25 11:35:20	ga_s2am_ard_3-2-1_51JTK_2024-03-25_final
2024-03-31 11:53:20	ga_s2am_ard_3-2-1_50KPC_2024-03-31_final
2024-04-03 12:05:13	ga_s2am_ard_3-2-1_49JGL_2024-04-03_final
2024-04-16 12:14:01	ga_s2am_ard_3-2-1_49KGR_2024-04-16_final
2024-04-17 11:43:25	ga_s2am_ard_3-2-1_50KQC_2024-04-17_final
2024-04-30 11:55:56	ga_s2am_ard_3-2-1_50JKN_2024-04-30_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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