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
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_49JGM_2016-01-06_final.stac-item
2016-01-12 10:44:10	ga_s2am_ard_3-2-1_53KNP_2016-01-12_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXP_2016-01-24_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KYQ_2016-01-24_final.stac-item
2016-07-27 10:28:06	ga_s2am_ard_3-2-1_53JNM_2016-07-27_final.stac-item
2016-08-09 10:43:11	ga_s2am_ard_3-2-1_53KNP_2016-08-09_final.stac-item
2016-09-17 11:12:10	ga_s2am_ard_3-2-1_52KEV_2016-09-17_final.stac-item
2016-10-12 10:25:59	ga_s2am_ard_3-2-1_54HTF_2016-10-12_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51KWB_2016-12-12_final.stac-item
2016-12-27 10:38:37	ga_s2am_ard_3-2-1_53LND_2016-12-27_final.stac-item
2017-01-08 11:18:08	ga_s2am_ard_3-2-1_51KXQ_2017-01-08_final.stac-item
2017-04-13 10:32:10	ga_s2am_ard_3-2-1_53JQN_2017-04-13_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JRM_2017-07-22_final.stac-item
2017-10-05 11:21:56	ga_s2am_ard_3-2-1_51KWP_2017-10-05_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53KPP_2017-11-19_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JGM_2017-12-26_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KRU_2018-01-18_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_52LDJ_2018-02-02_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51KWU_2018-04-26_final.stac-item
2018-08-13 10:17:05	ga_s2am_ard_3-2-1_53HPD_2018-08-13_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JKN_2018-09-09_final.stac-item
2018-10-12 10:17:03	ga_s2am_ard_3-2-1_53JRM_2018-10-12_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-11-01_final.stac-item
2018-11-07 10:46:05	ga_s2am_ard_3-2-1_53HLE_2018-11-07_final.stac-item
2018-12-27 10:44:14	ga_s2am_ard_3-2-1_53JNM_2018-12-27_final.stac-item
2019-01-19 10:50:38	ga_s2am_ard_3-2-1_53LMG_2019-01-19_final.stac-item
2019-01-21 11:32:29	ga_s2am_ard_3-2-1_51KVA_2019-01-21_final.stac-item
2019-01-30 12:06:07	ga_s2am_ard_3-2-1_50JKM_2019-01-30_final.stac-item
2019-02-04 11:11:31	ga_s2am_ard_3-2-1_52LEJ_2019-02-04_final.stac-item
2019-03-04 10:34:20	ga_s2am_ard_3-2-1_53JNM_2019-03-04_final.stac-item
2019-03-16 11:12:43	ga_s2am_ard_3-2-1_52KED_2019-03-16_final.stac-item
2019-05-01 11:33:16	ga_s2am_ard_3-2-1_51KWT_2019-05-01_final.stac-item
2019-05-06 10:46:10	ga_s2am_ard_3-2-1_53HME_2019-05-06_final.stac-item
2019-08-16 11:21:35	ga_s2am_ard_3-2-1_52LDJ_2019-08-16_final.stac-item
2019-08-16 11:24:22	ga_s2am_ard_3-2-1_51JZN_2019-08-16_final.stac-item
2019-09-11 11:41:31	ga_s2am_ard_3-2-1_51LUE_2019-09-11_final.stac-item
2019-09-15 11:21:31	ga_s2am_ard_3-2-1_52LDJ_2019-09-15_final.stac-item
2019-09-17 10:24:39	ga_s2am_ard_3-2-1_53JQL_2019-09-17_final.stac-item
2019-09-30 10:33:54	ga_s2am_ard_3-2-1_53KPP_2019-09-30_final.stac-item
2019-10-21 11:42:49	ga_s2am_ard_3-2-1_51KUV_2019-10-21_final.stac-item
2019-11-07 11:33:33	ga_s2am_ard_3-2-1_51KVS_2019-11-07_final.stac-item
2019-11-09 10:34:16	ga_s2am_ard_3-2-1_53JNN_2019-11-09_final.stac-item
2019-12-24 11:23:19	ga_s2am_ard_3-2-1_51KYS_2019-12-24_final.stac-item
2020-02-07 10:33:55	ga_s2am_ard_3-2-1_53JQN_2020-02-07_final.stac-item
2020-05-08 11:42:13	ga_s2am_ard_3-2-1_51KWB_2020-05-08_final.stac-item
2020-05-29 11:14:59	ga_s2am_ard_3-2-1_52JBR_2020-05-29_final.stac-item
2020-06-16 10:36:16	ga_s2am_ard_3-2-1_53HME_2020-06-16_final.stac-item
2020-06-26 10:36:37	ga_s2am_ard_3-2-1_53HPC_2020-06-26_final.stac-item
2020-07-04 11:33:21	ga_s2am_ard_3-2-1_51KVT_2020-07-04_final.stac-item
2020-07-11 11:26:48	ga_s2am_ard_3-2-1_51HVD_2020-07-11_final.stac-item
2020-10-24 10:35:54	ga_s2am_ard_3-2-1_53JPF_2020-10-24_final.stac-item
2020-11-22 11:00:47	ga_s2am_ard_3-2-1_52LHM_2020-11-22_final.stac-item
2020-12-16 10:41:46	ga_s2am_ard_3-2-1_53KQB_2020-12-16_final
2021-01-07 11:22:49	ga_s2am_ard_3-2-1_51KZU_2021-01-07_final.stac-item
2021-02-01 10:33:49	ga_s2am_ard_3-2-1_53KQP_2021-02-01_final.stac-item
2021-02-06 11:24:55	ga_s2am_ard_3-2-1_51JXL_2021-02-06_final.stac-item
2021-03-01 11:36:34	ga_s2am_ard_3-2-1_50HQK_2021-03-01_final.stac-item
2021-05-03 11:46:03	ga_s2am_ard_3-2-1_50JPM_2021-05-03_final.stac-item
2021-06-19 11:33:28	ga_s2am_ard_3-2-1_51KWS_2021-06-19_final.stac-item
2021-06-29 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2021-06-29_final.stac-item
2021-07-14 10:46:09	ga_s2am_ard_3-2-1_53HME_2021-07-14_final.stac-item
2021-07-15 10:17:32	ga_s2am_ard_3-2-1_54HUD_2021-07-15_final
2021-08-27 10:24:20	ga_s2am_ard_3-2-1_53JRM_2021-08-27_final.stac-item
2021-10-19 10:34:09	ga_s2am_ard_3-2-1_53JQN_2021-10-19_final.stac-item
2021-10-19 10:34:56	ga_s2am_ard_3-2-1_53JPK_2021-10-19_final.stac-item
2021-11-08 10:34:07	ga_s2am_ard_3-2-1_53JQN_2021-11-08_final.stac-item
2021-12-26 11:33:35	ga_s2am_ard_3-2-1_51KUS_2021-12-26_final.stac-item
2022-02-03 12:05:55	ga_s2am_ard_3-2-1_50JKN_2022-02-03_final.stac-item
2022-03-12 11:52:24	ga_s2am_ard_3-2-1_50KQG_2022-03-12_final
2022-05-05 11:33:21	ga_s2am_ard_3-2-1_51KVT_2022-05-05_final.stac-item
2022-06-13 10:26:55	ga_s2am_ard_3-2-1_54HTG_2022-06-13_final.stac-item
2022-08-09 11:56:11	ga_s2am_ard_3-2-1_50JKN_2022-08-09_final.stac-item
2022-08-15 10:34:45	ga_s2am_ard_3-2-1_53JQL_2022-08-15_final.stac-item
2022-08-26 11:42:58	ga_s2am_ard_3-2-1_51KUV_2022-08-26_final
2022-09-11 10:27:12	ga_s2am_ard_3-2-1_53HQA_2022-09-11_final.stac-item
2022-09-22 11:34:00	ga_s2am_ard_3-2-1_51KXQ_2022-09-22_final.stac-item
2022-11-17 11:53:24	ga_s2am_ard_3-2-1_50KPC_2022-11-17_final.stac-item
2022-12-30 10:25:04	ga_s2am_ard_3-2-1_53JQJ_2022-12-30_final.stac-item
2023-01-14 11:11:13	ga_s2am_ard_3-2-1_52LFK_2023-01-14_final.stac-item
2023-02-10 11:01:59	ga_s2am_ard_3-2-1_52KGG_2023-02-10_final.stac-item
2023-04-03 11:43:35	ga_s2am_ard_3-2-1_50KQB_2023-04-03_final
2023-04-10 11:33:45	ga_s2am_ard_3-2-1_51KVR_2023-04-10_final
2023-06-28 10:25:56	ga_s2am_ard_3-2-1_53JPF_2023-06-28_final
2023-07-21 10:34:18	ga_s2am_ard_3-2-1_53JRM_2023-07-21_final
2023-07-27 10:54:28	ga_s2am_ard_3-2-1_53JLM_2023-07-27_final
2023-08-07 10:24:23	ga_s2am_ard_3-2-1_53JRM_2023-08-07_final
2023-08-07 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-08-07_final
2023-09-02 10:44:26	ga_s2am_ard_3-2-1_53JNM_2023-09-02_final
2023-09-16 12:05:59	ga_s2am_ard_3-2-1_50JKN_2023-09-16_final
2023-10-12 10:46:04	ga_s2am_ard_3-2-1_53HME_2023-10-12_final
2023-12-18 10:33:45	ga_s2am_ard_3-2-1_53KPP_2023-12-18_final
2023-12-18 10:33:52	ga_s2am_ard_3-2-1_53KPP_2023-12-18_final
2024-01-02 11:23:25	ga_s2am_ard_3-2-1_51KXS_2024-01-02_final
2024-01-18 11:43:02	ga_s2am_ard_3-2-1_51KVT_2024-01-18_final
2024-01-22 11:24:01	ga_s2am_ard_3-2-1_51KYP_2024-01-22_final
2024-01-29 11:12:01	ga_s2am_ard_3-2-1_52KDG_2024-01-29_final
2024-01-29 11:14:18	ga_s2am_ard_3-2-1_52JBT_2024-01-29_final
2024-01-30 10:45:42	ga_s2am_ard_3-2-1_52JGM_2024-01-30_final
2024-02-06 10:34:10	ga_s2am_ard_3-2-1_53JRM_2024-02-06_final
2024-02-16 10:34:30	ga_s2am_ard_3-2-1_53JQL_2024-02-16_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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