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
2015-09-04 10:45:31	ga_s2am_ard_3-2-1_53HLD_2015-09-04_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JGM_2015-12-27_final.stac-item
2016-03-21 11:12:12	ga_s2am_ard_3-2-1_52KCE_2016-03-21_final.stac-item
2016-05-02 10:16:17	ga_s2am_ard_3-2-1_54HTH_2016-05-02_final.stac-item
2016-07-23 10:48:23	ga_s2am_ard_3-2-1_52JFT_2016-07-23_final.stac-item
2016-08-29 10:43:08	ga_s2am_ard_3-2-1_53KPP_2016-08-29_final.stac-item
2016-09-21 10:55:09	ga_s2am_ard_3-2-1_53JKH_2016-09-21_final.stac-item
2016-11-02 11:26:18	ga_s2am_ard_3-2-1_51KXU_2016-11-02_final.stac-item
2016-11-09 11:26:07	ga_s2am_ard_3-2-1_51JVF_2016-11-09_final.stac-item
2017-02-07 11:26:03	ga_s2am_ard_3-2-1_51JVF_2017-02-07_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYM_2017-06-27_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JGM_2017-08-01_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JQL_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JTN_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KVP_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KWQ_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KWU_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51LXD_2017-09-28_final.stac-item
2017-09-29 11:02:55	ga_s2am_ard_3-2-1_52JCR_2017-09-29_final.stac-item
2017-10-08 11:36:06	ga_s2am_ard_3-2-1_51HUE_2017-10-08_final.stac-item
2017-10-10 10:32:09	ga_s2am_ard_3-2-1_53JNH_2017-10-10_final.stac-item
2017-10-28 11:36:03	ga_s2am_ard_3-2-1_51JTG_2017-10-28_final.stac-item
2018-01-28 10:31:56	ga_s2am_ard_3-2-1_53KQA_2018-01-28_final.stac-item
2018-02-27 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-02-27_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_51HTD_2018-03-17_final.stac-item
2018-04-03 11:16:59	ga_s2am_ard_3-2-1_52LDJ_2018-04-03_final.stac-item
2018-04-11 10:37:28	ga_s2am_ard_3-2-1_53JNN_2018-04-11_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51LUE_2018-04-29_final.stac-item
2018-05-15 10:17:08	ga_s2am_ard_3-2-1_53HPD_2018-05-15_final.stac-item
2018-05-25 12:02:51	ga_s2am_ard_3-2-1_50KMB_2018-05-25_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_51KXS_2018-05-26_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKS_2018-07-04_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51KUT_2018-07-15_final.stac-item
2018-08-06 10:27:08	ga_s2am_ard_3-2-1_53JPN_2018-08-06_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51LYE_2018-11-02_final.stac-item
2019-01-03 10:34:30	ga_s2am_ard_3-2-1_53JPL_2019-01-03_final.stac-item
2019-01-07 11:55:54	ga_s2am_ard_3-2-1_50JKN_2019-01-07_final.stac-item
2019-01-31 11:31:21	ga_s2am_ard_3-2-1_51LYE_2019-01-31_final.stac-item
2019-02-28 10:50:30	ga_s2am_ard_3-2-1_53LPG_2019-02-28_final.stac-item
2019-03-23 11:05:11	ga_s2am_ard_3-2-1_52JFP_2019-03-23_final.stac-item
2019-04-23 10:36:31	ga_s2am_ard_3-2-1_53HLD_2019-04-23_final.stac-item
2019-05-04 11:43:15	ga_s2am_ard_3-2-1_51KVT_2019-05-04_final.stac-item
2019-07-14 11:13:35	ga_s2am_ard_3-2-1_52KEA_2019-07-14_final.stac-item
2019-08-18 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-08-18_final.stac-item
2019-12-30 10:07:24	ga_s2am_ard_3-2-1_54HVD_2019-12-30_final.stac-item
2020-03-21 10:44:13	ga_s2am_ard_3-2-1_53JPM_2020-03-21_final.stac-item
2020-03-29 11:42:38	ga_s2am_ard_3-2-1_51KVV_2020-03-29_final.stac-item
2020-06-14 11:33:59	ga_s2am_ard_3-2-1_51KXQ_2020-06-14_final.stac-item
2020-08-10 11:25:30	ga_s2am_ard_3-2-1_51JXJ_2020-08-10_final.stac-item
2020-08-20 11:23:12	ga_s2am_ard_3-2-1_52KBC_2020-08-20_final.stac-item
2020-08-27 11:13:19	ga_s2am_ard_3-2-1_52KBC_2020-08-27_final.stac-item
2020-11-04 11:43:16	ga_s2am_ard_3-2-1_51KVT_2020-11-04_final.stac-item
2020-12-27 10:16:20	ga_s2am_ard_3-2-1_54HTJ_2020-12-27_final.stac-item
2021-02-04 10:40:53	ga_s2am_ard_3-2-1_53LPF_2021-02-04_final.stac-item
2021-03-05 11:10:32	ga_s2am_ard_3-2-1_52LFN_2021-03-05_final
2021-03-08 11:23:28	ga_s2am_ard_3-2-1_51KXS_2021-03-08_final.stac-item
2021-03-17 10:17:29	ga_s2am_ard_3-2-1_54HUD_2021-03-17_final
2021-03-24 11:42:15	ga_s2am_ard_3-2-1_51KUB_2021-03-24_final
2021-04-14 11:10:59	ga_s2am_ard_3-2-1_52LEL_2021-04-14_final
2021-05-08 10:50:23	ga_s2am_ard_3-2-1_53LNH_2021-05-08_final
2021-05-25 10:43:49	ga_s2am_ard_3-2-1_53KPP_2021-05-25_final.stac-item
2021-06-15 11:53:03	ga_s2am_ard_3-2-1_50KQD_2021-06-15_final
2021-06-16 11:26:59	ga_s2am_ard_3-2-1_51HVC_2021-06-16_final.stac-item
2021-07-04 10:46:15	ga_s2am_ard_3-2-1_53HKE_2021-07-04_final
2021-07-11 10:36:42	ga_s2am_ard_3-2-1_53HMC_2021-07-11_final
2021-08-21 11:42:38	ga_s2am_ard_3-2-1_51KVA_2021-08-21_final.stac-item
2021-08-21 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-08-21_final
2021-08-31 11:47:11	ga_s2am_ard_3-2-1_50HMH_2021-08-31_final.stac-item
2021-09-10 11:43:15	ga_s2am_ard_3-2-1_51KUT_2021-09-10_final.stac-item
2021-10-13 10:17:05	ga_s2am_ard_3-2-1_54HUF_2021-10-13_final.stac-item
2021-10-17 11:33:36	ga_s2am_ard_3-2-1_51KVS_2021-10-17_final.stac-item
2021-10-29 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-29_final
2021-12-02 11:53:31	ga_s2am_ard_3-2-1_50KQB_2021-12-02_final.stac-item
2021-12-20 11:11:17	ga_s2am_ard_3-2-1_52LFK_2021-12-20_final.stac-item
2022-01-11 11:53:12	ga_s2am_ard_3-2-1_50KRC_2022-01-11_final.stac-item
2022-01-20 10:44:06	ga_s2am_ard_3-2-1_53JNN_2022-01-20_final.stac-item
2022-02-03 10:27:00	ga_s2am_ard_3-2-1_53HNB_2022-02-03_final.stac-item
2022-03-30 11:14:40	ga_s2am_ard_3-2-1_52JBS_2022-03-30_final.stac-item
2022-04-27 10:36:51	ga_s2am_ard_3-2-1_53HPB_2022-04-27_final.stac-item
2022-05-05 11:36:47	ga_s2am_ard_3-2-1_51HUD_2022-05-05_final.stac-item
2022-05-10 10:46:28	ga_s2am_ard_3-2-1_53HLD_2022-05-10_final.stac-item
2022-06-17 11:41:44	ga_s2am_ard_3-2-1_51LUE_2022-06-17_final.stac-item
2022-06-24 11:33:43	ga_s2am_ard_3-2-1_51KVS_2022-06-24_final.stac-item
2022-08-01 10:55:56	ga_s2am_ard_3-2-1_52JFM_2022-08-01_final.stac-item
2022-11-15 11:11:15	ga_s2am_ard_3-2-1_52LGK_2022-11-15_final.stac-item
2022-11-25 11:13:18	ga_s2am_ard_3-2-1_52KDB_2022-11-25_final.stac-item
2023-01-28 10:52:31	ga_s2am_ard_3-2-1_53KNU_2023-01-28_final.stac-item
2023-01-31 11:01:44	ga_s2am_ard_3-2-1_52LGH_2023-01-31_final.stac-item
2023-02-24 10:44:00	ga_s2am_ard_3-2-1_53JPN_2023-02-24_final
2023-02-25 10:17:27	ga_s2am_ard_3-2-1_54HUD_2023-02-25_final
2023-03-04 11:40:54	ga_s2am_ard_3-2-1_51LWG_2023-03-04_final
2023-04-01 11:06:13	ga_s2am_ard_3-2-1_52HEK_2023-04-01_final
2023-06-06 11:23:24	ga_s2am_ard_3-2-1_52KBB_2023-06-06_final
2023-07-18 10:23:44	ga_s2am_ard_3-2-1_53KRQ_2023-07-18_final
2023-07-18 10:26:35	ga_s2am_ard_3-2-1_54HTH_2023-07-18_final
2023-09-03 11:53:04	ga_s2am_ard_3-2-1_50KRD_2023-09-03_final
2023-09-10 11:44:34	ga_s2am_ard_3-2-1_50JRT_2023-09-10_final
2023-10-16 10:26:23	ga_s2am_ard_3-2-1_54HTJ_2023-10-16_final
2024-01-19 11:13:20	ga_s2am_ard_3-2-1_51KZS_2024-01-19_final
2024-02-14 11:33:39	ga_s2am_ard_3-2-1_51KWR_2024-02-14_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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