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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGL_2016-01-16_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HMG_2016-02-19_final
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51JTJ_2016-04-06_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGM_2016-04-15_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JNM_2016-04-19_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50JPL_2016-05-06_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JML_2016-05-09_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51JTG_2016-08-24_final.stac-item
2017-04-01 11:34:45	ga_s2am_ard_3-2-1_51HUC_2017-04-01_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HMJ_2017-04-07_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51JVF_2017-04-28_final.stac-item
2017-06-07 11:23:45	ga_s2am_ard_3-2-1_51HUC_2017-06-07_final.stac-item
2017-06-12 12:14:42	ga_s2am_ard_3-2-1_49JGM_2017-06-12_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HMJ_2017-11-13_final.stac-item
2017-12-04 11:22:04	ga_s2am_ard_3-2-1_51JYJ_2017-12-04_final.stac-item
2018-01-13 11:25:27	ga_s2am_ard_3-2-1_51JWH_2018-01-13_final.stac-item
2018-01-15 12:03:40	ga_s2am_ard_3-2-1_50KKA_2018-01-15_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_51HTD_2018-03-17_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JKP_2018-03-23_final.stac-item
2018-04-12 11:47:43	ga_s2am_ard_3-2-1_50KQC_2018-04-12_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51HVC_2018-04-23_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49KHR_2018-04-28_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50KRB_2018-07-18_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-28_final.stac-item
2018-08-03 12:02:50	ga_s2am_ard_3-2-1_50KMC_2018-08-03_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HTD_2018-08-04_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49JHN_2018-08-13_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKM_2018-09-02_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50KLB_2018-10-02_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-11-01_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51HTC_2018-11-02_final.stac-item
2018-12-11 12:03:51	ga_s2am_ard_3-2-1_49KHR_2018-12-11_final.stac-item
2019-01-23 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-01-23_final.stac-item
2019-02-09 12:05:45	ga_s2am_ard_3-2-1_50JKN_2019-02-09_final.stac-item
2019-05-28 11:25:12	ga_s2am_ard_3-2-1_51JXK_2019-05-28_final.stac-item
2019-06-20 11:36:30	ga_s2am_ard_3-2-1_50JPL_2019-06-20_final.stac-item
2019-06-29 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-06-29_final.stac-item
2019-09-18 11:36:42	ga_s2am_ard_3-2-1_51HUD_2019-09-18_final.stac-item
2019-10-05 11:26:20	ga_s2am_ard_3-2-1_51JUF_2019-10-05_final.stac-item
2019-11-06 12:03:26	ga_s2am_ard_3-2-1_50KMC_2019-11-06_final.stac-item
2019-12-06 12:03:57	ga_s2am_ard_3-2-1_49KHR_2019-12-06_final.stac-item
2019-12-26 12:05:50	ga_s2am_ard_3-2-1_50JKN_2019-12-26_final.stac-item
2020-01-15 12:03:32	ga_s2am_ard_3-2-1_50KMB_2020-01-15_final.stac-item
2020-03-13 11:24:19	ga_s2am_ard_3-2-1_51JYN_2020-03-13_final.stac-item
2020-03-19 11:46:34	ga_s2am_ard_3-2-1_50HNK_2020-03-19_final.stac-item
2020-04-05 11:35:56	ga_s2am_ard_3-2-1_51JUG_2020-04-05_final.stac-item
2020-04-12 11:26:57	ga_s2am_ard_3-2-1_51HVC_2020-04-12_final.stac-item
2020-05-31 11:52:44	ga_s2am_ard_3-2-1_50KPF_2020-05-31_final
2020-06-14 11:34:54	ga_s2am_ard_3-2-1_51JVL_2020-06-14_final.stac-item
2020-08-13 11:36:25	ga_s2am_ard_3-2-1_50JQL_2020-08-13_final.stac-item
2020-11-20 12:04:48	ga_s2am_ard_3-2-1_49JGN_2020-11-20_final.stac-item
2020-12-04 11:44:22	ga_s2am_ard_3-2-1_50KPU_2020-12-04_final.stac-item
2021-01-03 11:43:04	ga_s2am_ard_3-2-1_50KRD_2021-01-03_final.stac-item
2021-02-08 12:03:22	ga_s2am_ard_3-2-1_50KMC_2021-02-08_final.stac-item
2021-02-08 12:03:58	ga_s2am_ard_3-2-1_50KKA_2021-02-08_final.stac-item
2021-04-02 12:13:51	ga_s2am_ard_3-2-1_50KKA_2021-04-02_final.stac-item
2021-05-03 11:47:22	ga_s2am_ard_3-2-1_50HMG_2021-05-03_final
2021-05-06 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2021-05-06_final.stac-item
2021-05-13 11:46:19	ga_s2am_ard_3-2-1_50JPL_2021-05-13_final.stac-item
2021-05-23 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-05-23_final.stac-item
2021-06-08 12:05:38	ga_s2am_ard_3-2-1_50JLP_2021-06-08_final.stac-item
2021-06-19 11:36:58	ga_s2am_ard_3-2-1_51HUC_2021-06-19_final.stac-item
2021-06-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-06-28_final.stac-item
2021-07-28 12:03:23	ga_s2am_ard_3-2-1_50KNC_2021-07-28_final.stac-item
2021-08-21 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-08-21_final
2021-09-26 12:03:48	ga_s2am_ard_3-2-1_50KKB_2021-09-26_final.stac-item
2021-11-19 11:44:52	ga_s2am_ard_3-2-1_50JPS_2021-11-19_final.stac-item
2021-12-30 11:14:39	ga_s2am_ard_3-2-1_51JZM_2021-12-30_final.stac-item
2022-02-23 12:04:01	ga_s2am_ard_3-2-1_49KHR_2022-02-23_final.stac-item
2022-03-16 11:34:43	ga_s2am_ard_3-2-1_51JWM_2022-03-16_final.stac-item
2022-04-05 11:36:21	ga_s2am_ard_3-2-1_50JQL_2022-04-05_final.stac-item
2022-04-21 11:53:29	ga_s2am_ard_3-2-1_50KNC_2022-04-21_final.stac-item
2022-05-02 11:25:00	ga_s2am_ard_3-2-1_51JXL_2022-05-02_final.stac-item
2022-06-03 12:04:39	ga_s2am_ard_3-2-1_49KGP_2022-06-03_final.stac-item
2022-06-06 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-06-06_final.stac-item
2022-06-21 11:25:36	ga_s2am_ard_3-2-1_51JXJ_2022-06-21_final.stac-item
2022-07-01 11:26:59	ga_s2am_ard_3-2-1_51HVD_2022-07-01_final.stac-item
2022-08-03 11:35:55	ga_s2am_ard_3-2-1_51JUH_2022-08-03_final.stac-item
2022-09-08 11:56:15	ga_s2am_ard_3-2-1_50JNM_2022-09-08_final.stac-item
2022-10-12 11:36:19	ga_s2am_ard_3-2-1_51JUF_2022-10-12_final.stac-item
2022-12-01 11:34:36	ga_s2am_ard_3-2-1_51JTN_2022-12-01_final.stac-item
2022-12-10 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-12-10_final.stac-item
2022-12-11 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2022-12-11_final.stac-item
2023-01-19 12:05:10	ga_s2am_ard_3-2-1_49JGL_2023-01-19_final.stac-item
2023-01-22 12:13:50	ga_s2am_ard_3-2-1_50KKA_2023-01-22_final.stac-item
2023-03-01 11:36:44	ga_s2am_ard_3-2-1_51HTD_2023-03-01_final
2023-03-10 12:05:36	ga_s2am_ard_3-2-1_50JKP_2023-03-10_final
2023-03-17 11:56:27	ga_s2am_ard_3-2-1_50HNK_2023-03-17_final
2023-03-28 11:24:53	ga_s2am_ard_3-2-1_51JXL_2023-03-28_final
2023-07-18 12:05:45	ga_s2am_ard_3-2-1_50JKP_2023-07-18_final
2023-09-07 11:36:37	ga_s2am_ard_3-2-1_51HTE_2023-09-07_final
2023-10-04 11:26:37	ga_s2am_ard_3-2-1_51HXD_2023-10-04_final
2023-12-03 11:26:54	ga_s2am_ard_3-2-1_51HUC_2023-12-03_final
2023-12-15 12:03:40	ga_s2am_ard_3-2-1_50KKB_2023-12-15_final
2024-01-22 11:24:22	ga_s2am_ard_3-2-1_51JWN_2024-01-22_final
2024-02-06 12:13:36	ga_s2am_ard_3-2-1_49KHS_2024-02-06_final
2024-03-01 11:53:24	ga_s2am_ard_3-2-1_50KNC_2024-03-01_final
2024-03-02 11:24:26	ga_s2am_ard_3-2-1_51JXN_2024-03-02_final
2024-05-03 12:03:47	ga_s2am_ard_3-2-1_50KKB_2024-05-03_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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