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
2015-12-07 10:22:23	ga_s2am_ard_3-2-1_53HPC_2015-12-07_final.stac-item
2016-04-28 10:34:09	ga_s2am_ard_3-2-1_53JQN_2016-04-28_final.stac-item
2016-06-10 10:43:11	ga_s2am_ard_3-2-1_53JNN_2016-06-10_final.stac-item
2016-06-15 11:36:06	ga_s2am_ard_3-2-1_50JPL_2016-06-15_final.stac-item
2016-12-17 10:43:37	ga_s2am_ard_3-2-1_53JNN_2016-12-17_final.stac-item
2017-03-21 10:22:59	ga_s2am_ard_3-2-1_53HQB_2017-03-21_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_51JUL_2017-04-21_final.stac-item
2017-06-20 11:28:36	ga_s2am_ard_3-2-1_51KWQ_2017-06-20_final.stac-item
2017-09-02 11:12:01	ga_s2am_ard_3-2-1_51HWD_2017-09-02_final.stac-item
2017-10-31 11:37:51	ga_s2am_ard_3-2-1_51KVB_2017-10-31_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVB_2017-11-20_final.stac-item
2018-01-10 11:12:24	ga_s2am_ard_3-2-1_51KZS_2018-01-10_final.stac-item
2018-03-18 11:05:41	ga_s2am_ard_3-2-1_52JEL_2018-03-18_final.stac-item
2018-04-21 10:37:29	ga_s2am_ard_3-2-1_53JPL_2018-04-21_final.stac-item
2018-07-07 10:27:09	ga_s2am_ard_3-2-1_53JNN_2018-07-07_final.stac-item
2018-08-23 10:17:05	ga_s2am_ard_3-2-1_53HQE_2018-08-23_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HPH_2018-09-26_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JKM_2018-09-29_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_51KVV_2018-10-06_final.stac-item
2018-10-18 10:37:24	ga_s2am_ard_3-2-1_53JNM_2018-10-18_final.stac-item
2018-11-12 11:33:37	ga_s2am_ard_3-2-1_51KWR_2018-11-12_final.stac-item
2018-11-14 10:34:20	ga_s2am_ard_3-2-1_53JNM_2018-11-14_final.stac-item
2019-01-07 11:53:19	ga_s2am_ard_3-2-1_50KNC_2019-01-07_final.stac-item
2019-03-22 11:33:25	ga_s2am_ard_3-2-1_51KWS_2019-03-22_final.stac-item
2019-03-31 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2019-03-31_final.stac-item
2019-04-14 11:42:15	ga_s2am_ard_3-2-1_51KVB_2019-04-14_final.stac-item
2019-05-03 10:34:07	ga_s2am_ard_3-2-1_53JQN_2019-05-03_final.stac-item
2019-05-11 11:33:16	ga_s2am_ard_3-2-1_51KWT_2019-05-11_final.stac-item
2019-06-10 11:33:15	ga_s2am_ard_3-2-1_51KWT_2019-06-10_final.stac-item
2019-06-10 11:33:55	ga_s2am_ard_3-2-1_51KXQ_2019-06-10_final.stac-item
2019-08-04 10:46:10	ga_s2am_ard_3-2-1_53HME_2019-08-04_final.stac-item
2019-08-11 10:34:36	ga_s2am_ard_3-2-1_53JQL_2019-08-11_final.stac-item
2019-08-22 11:43:14	ga_s2am_ard_3-2-1_51KVT_2019-08-22_final.stac-item
2019-09-21 11:43:15	ga_s2am_ard_3-2-1_51KUT_2019-09-21_final.stac-item
2019-11-09 10:34:21	ga_s2am_ard_3-2-1_53JQM_2019-11-09_final.stac-item
2019-12-09 10:35:49	ga_s2am_ard_3-2-1_53JNF_2019-12-09_final.stac-item
2019-12-30 11:42:58	ga_s2am_ard_3-2-1_51KTU_2019-12-30_final.stac-item
2020-01-09 11:42:16	ga_s2am_ard_3-2-1_51KWA_2020-01-09_final.stac-item
2020-01-10 11:16:31	ga_s2am_ard_3-2-1_51HYD_2020-01-10_final.stac-item
2020-02-02 11:23:08	ga_s2am_ard_3-2-1_52KCB_2020-02-02_final.stac-item
2020-02-12 11:23:21	ga_s2am_ard_3-2-1_51KXS_2020-02-12_final.stac-item
2020-02-29 11:16:03	ga_s2am_ard_3-2-1_51JYF_2020-02-29_final.stac-item
2020-04-25 11:36:25	ga_s2am_ard_3-2-1_51HVE_2020-04-25_final.stac-item
2020-06-11 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2020-06-11_final.stac-item
2020-06-17 11:42:15	ga_s2am_ard_3-2-1_51KWB_2020-06-17_final.stac-item
2020-07-16 12:14:23	ga_s2am_ard_3-2-1_50KKU_2020-07-16_final.stac-item
2020-08-19 11:55:48	ga_s2am_ard_3-2-1_50JLP_2020-08-19_final.stac-item
2020-10-28 11:52:43	ga_s2am_ard_3-2-1_50KPF_2020-10-28_final
2020-11-13 10:34:07	ga_s2am_ard_3-2-1_53JQN_2020-11-13_final.stac-item
2020-11-22 11:00:47	ga_s2am_ard_3-2-1_52LHM_2020-11-22_final.stac-item
2021-01-05 10:44:28	ga_s2am_ard_3-2-1_53JPL_2021-01-05_final.stac-item
2021-02-10 11:02:17	ga_s2am_ard_3-2-1_52KFF_2021-02-10_final.stac-item
2021-03-22 11:02:50	ga_s2am_ard_3-2-1_52KED_2021-03-22_final.stac-item
2021-04-11 11:06:16	ga_s2am_ard_3-2-1_52HCK_2021-04-11_final
2021-05-12 10:36:31	ga_s2am_ard_3-2-1_53HPC_2021-05-12_final.stac-item
2021-06-08 12:04:14	ga_s2am_ard_3-2-1_50KKV_2021-06-08_final.stac-item
2021-06-10 11:04:36	ga_s2am_ard_3-2-1_52JGR_2021-06-10_final.stac-item
2021-07-08 10:26:56	ga_s2am_ard_3-2-1_53HNB_2021-07-08_final.stac-item
2021-09-11 11:11:05	ga_s2am_ard_3-2-1_52LEL_2021-09-11_final
2021-10-07 11:32:24	ga_s2am_ard_3-2-1_51KVB_2021-10-07_final.stac-item
2021-11-05 10:26:57	ga_s2am_ard_3-2-1_53HNB_2021-11-05_final.stac-item
2021-11-06 11:33:27	ga_s2am_ard_3-2-1_51KXS_2021-11-06_final.stac-item
2021-11-07 11:00:48	ga_s2am_ard_3-2-1_52LHM_2021-11-07_final.stac-item
2021-11-24 10:55:35	ga_s2am_ard_3-2-1_52JEN_2021-11-24_final.stac-item
2022-04-29 11:13:47	ga_s2am_ard_3-2-1_52KBA_2022-04-29_final.stac-item
2022-06-13 12:06:05	ga_s2am_ard_3-2-1_50JKN_2022-06-13_final.stac-item
2022-07-23 12:05:19	ga_s2am_ard_3-2-1_49JFM_2022-07-23_final.stac-item
2022-08-03 11:33:23	ga_s2am_ard_3-2-1_51KWT_2022-08-03_final.stac-item
2022-10-11 10:24:57	ga_s2am_ard_3-2-1_53JQK_2022-10-11_final.stac-item
2022-10-26 11:16:20	ga_s2am_ard_3-2-1_51JYF_2022-10-26_final.stac-item
2022-11-10 10:26:50	ga_s2am_ard_3-2-1_53HQB_2022-11-10_final.stac-item
2022-11-13 10:34:25	ga_s2am_ard_3-2-1_53JPM_2022-11-13_final.stac-item
2022-12-26 10:44:08	ga_s2am_ard_3-2-1_53JMN_2022-12-26_final.stac-item
2023-01-07 11:23:15	ga_s2am_ard_3-2-1_52KCB_2023-01-07_final.stac-item
2023-01-10 11:36:50	ga_s2am_ard_3-2-1_50HPJ_2023-01-10_final.stac-item
2023-01-29 10:25:03	ga_s2am_ard_3-2-1_53JQJ_2023-01-29_final.stac-item
2023-02-12 11:42:58	ga_s2am_ard_3-2-1_51KUU_2023-02-12_final
2023-02-19 11:33:42	ga_s2am_ard_3-2-1_51KVR_2023-02-19_final
2023-03-11 11:34:01	ga_s2am_ard_3-2-1_51KXP_2023-03-11_final
2023-03-29 10:54:35	ga_s2am_ard_3-2-1_53JLL_2023-03-29_final
2023-03-31 11:33:14	ga_s2am_ard_3-2-1_51KVT_2023-03-31_final
2023-03-31 11:37:01	ga_s2am_ard_3-2-1_50HQH_2023-03-31_final
2023-04-01 11:00:29	ga_s2am_ard_3-2-1_52LHN_2023-04-01_final
2023-04-08 10:56:04	ga_s2am_ard_3-2-1_52JEL_2023-04-08_final
2023-04-14 11:15:04	ga_s2am_ard_3-2-1_52JCQ_2023-04-14_final
2023-04-22 10:34:31	ga_s2am_ard_3-2-1_53JQL_2023-04-22_final
2023-06-09 11:33:56	ga_s2am_ard_3-2-1_51KXQ_2023-06-09_final
2023-06-20 11:04:22	ga_s2am_ard_3-2-1_52JET_2023-06-20_final
2023-06-20 11:04:40	ga_s2am_ard_3-2-1_52JDS_2023-06-20_final
2023-07-19 11:33:26	ga_s2am_ard_3-2-1_51KUT_2023-07-19_final
2023-07-19 11:34:00	ga_s2am_ard_3-2-1_51KWQ_2023-07-19_final
2023-08-01 11:42:18	ga_s2am_ard_3-2-1_51KVB_2023-08-01_final
2023-10-15 10:54:20	ga_s2am_ard_3-2-1_52JFT_2023-10-15_final
2023-11-13 11:23:42	ga_s2am_ard_3-2-1_51KXR_2023-11-13_final
2023-12-10 12:50:54	ga_s2am_ard_3-2-1_48LWP_2023-12-10_final
2023-12-21 10:45:40	ga_s2am_ard_3-2-1_53JKG_2023-12-21_final
2023-12-23 11:23:21	ga_s2am_ard_3-2-1_51KYS_2023-12-23_final
2023-12-26 11:32:41	ga_s2am_ard_3-2-1_51KWV_2023-12-26_final
2024-03-23 10:52:46	ga_s2am_ard_3-2-1_52KHD_2024-03-23_final
2024-04-07 11:41:31	ga_s2am_ard_3-2-1_51LUE_2024-04-07_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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