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
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51JTG_2016-06-18_final.stac-item
2016-08-10 10:15:57	ga_s2am_ard_3-2-1_54HVF_2016-08-10_final.stac-item
2016-08-11 11:22:31	ga_s2am_ard_3-2-1_51KYT_2016-08-11_final.stac-item
2016-11-19 09:47:39	ga_s2am_ard_3-2-1_54HYB_2016-11-19_final.stac-item
2016-12-14 10:33:36	ga_s2am_ard_3-2-1_53JNM_2016-12-14_final.stac-item
2017-02-28 10:47:18	ga_s2am_ard_3-2-1_53LMG_2017-02-28_final.stac-item
2017-05-04 11:38:37	ga_s2am_ard_3-2-1_51KUT_2017-05-04_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_50KKB_2017-06-02_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_51KUT_2017-09-01_final.stac-item
2017-11-01 11:07:12	ga_s2am_ard_3-2-1_52KDG_2017-11-01_final.stac-item
2017-11-23 10:16:52	ga_s2am_ard_3-2-1_54HUF_2017-11-23_final.stac-item
2018-02-03 10:53:11	ga_s2am_ard_3-2-1_53JKH_2018-02-03_final.stac-item
2018-02-18 11:42:05	ga_s2am_ard_3-2-1_51KUP_2018-02-18_final.stac-item
2018-04-13 11:20:51	ga_s2am_ard_3-2-1_51KYT_2018-04-13_final.stac-item
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53JNM_2018-09-25_final.stac-item
2018-09-25 10:27:03	ga_s2am_ard_3-2-1_53KPP_2018-09-25_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-10-02_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_51KVV_2018-10-06_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JRM_2018-10-15_final.stac-item
2018-11-07 10:46:05	ga_s2am_ard_3-2-1_53HLE_2018-11-07_final.stac-item
2018-12-07 10:44:08	ga_s2am_ard_3-2-1_53JPM_2018-12-07_final.stac-item
2019-01-21 11:33:20	ga_s2am_ard_3-2-1_51KXS_2019-01-21_final.stac-item
2019-04-03 10:33:46	ga_s2am_ard_3-2-1_54KTU_2019-04-03_final.stac-item
2019-04-29 10:53:46	ga_s2am_ard_3-2-1_52KHV_2019-04-29_final.stac-item
2019-05-25 11:15:25	ga_s2am_ard_3-2-1_52JBP_2019-05-25_final.stac-item
2019-05-31 11:33:04	ga_s2am_ard_3-2-1_51KVU_2019-05-31_final.stac-item
2019-06-10 11:33:44	ga_s2am_ard_3-2-1_51KWR_2019-06-10_final.stac-item
2019-08-06 11:26:44	ga_s2am_ard_3-2-1_51HWD_2019-08-06_final.stac-item
2019-08-26 11:23:08	ga_s2am_ard_3-2-1_52KBC_2019-08-26_final.stac-item
2019-09-02 11:13:19	ga_s2am_ard_3-2-1_52KDB_2019-09-02_final.stac-item
2019-10-20 10:34:17	ga_s2am_ard_3-2-1_53JRM_2019-10-20_final.stac-item
2019-10-30 10:33:56	ga_s2am_ard_3-2-1_53KPP_2019-10-30_final.stac-item
2019-11-03 10:16:52	ga_s2am_ard_3-2-1_54HTG_2019-11-03_final.stac-item
2019-11-22 10:45:48	ga_s2am_ard_3-2-1_52JGM_2019-11-22_final.stac-item
2019-11-30 11:43:28	ga_s2am_ard_3-2-1_51KUS_2019-11-30_final.stac-item
2019-12-19 10:34:23	ga_s2am_ard_3-2-1_54JTR_2019-12-19_final.stac-item
2020-01-28 10:36:21	ga_s2am_ard_3-2-1_53HLD_2020-01-28_final.stac-item
2020-02-25 11:32:54	ga_s2am_ard_3-2-1_51KVU_2020-02-25_final.stac-item
2020-04-08 10:07:34	ga_s2am_ard_3-2-1_54HXC_2020-04-08_final.stac-item
2020-07-13 10:25:07	ga_s2am_ard_3-2-1_54JTP_2020-07-13_final.stac-item
2020-08-16 10:06:52	ga_s2am_ard_3-2-1_54HVG_2020-08-16_final.stac-item
2020-09-18 10:15:34	ga_s2am_ard_3-2-1_54JVM_2020-09-18_final.stac-item
2020-09-30 10:52:25	ga_s2am_ard_3-2-1_52KHF_2020-09-30_final.stac-item
2020-12-26 10:41:48	ga_s2am_ard_3-2-1_53KQB_2020-12-26_final
2021-01-27 11:24:02	ga_s2am_ard_3-2-1_51KWQ_2021-01-27_final.stac-item
2021-02-07 10:52:29	ga_s2am_ard_3-2-1_53KKV_2021-02-07_final.stac-item
2021-02-12 10:07:39	ga_s2am_ard_3-2-1_54HWC_2021-02-12_final.stac-item
2021-03-22 11:01:49	ga_s2am_ard_3-2-1_52LFH_2021-03-22_final.stac-item
2021-03-25 11:14:58	ga_s2am_ard_3-2-1_52JDQ_2021-03-25_final.stac-item
2021-06-01 12:14:19	ga_s2am_ard_3-2-1_50KKU_2021-06-01_final.stac-item
2021-06-23 11:13:34	ga_s2am_ard_3-2-1_52KDA_2021-06-23_final.stac-item
2021-07-06 11:23:13	ga_s2am_ard_3-2-1_51KYT_2021-07-06_final.stac-item
2021-07-27 10:55:25	ga_s2am_ard_3-2-1_52JEP_2021-07-27_final.stac-item
2021-08-11 11:43:14	ga_s2am_ard_3-2-1_51KVT_2021-08-11_final.stac-item
2021-08-13 10:46:08	ga_s2am_ard_3-2-1_53HME_2021-08-13_final.stac-item
2021-08-30 10:34:20	ga_s2am_ard_3-2-1_53JQM_2021-08-30_final.stac-item
2021-10-12 10:44:12	ga_s2am_ard_3-2-1_53JNN_2021-10-12_final.stac-item
2021-11-11 10:46:08	ga_s2am_ard_3-2-1_53HME_2021-11-11_final.stac-item
2021-12-04 10:55:24	ga_s2am_ard_3-2-1_53JKH_2021-12-04_final.stac-item
2021-12-31 10:43:50	ga_s2am_ard_3-2-1_53KPP_2021-12-31_final.stac-item
2022-01-01 10:15:31	ga_s2am_ard_3-2-1_54JVM_2022-01-01_final.stac-item
2022-01-29 11:13:29	ga_s2am_ard_3-2-1_51KZS_2022-01-29_final.stac-item
2022-04-15 11:36:37	ga_s2am_ard_3-2-1_50HQK_2022-04-15_final.stac-item
2022-04-18 11:43:15	ga_s2am_ard_3-2-1_51KVT_2022-04-18_final.stac-item
2022-05-09 11:13:23	ga_s2am_ard_3-2-1_52KDB_2022-05-09_final.stac-item
2022-06-02 10:53:07	ga_s2am_ard_3-2-1_52KHC_2022-06-02_final.stac-item
2022-06-27 11:43:42	ga_s2am_ard_3-2-1_51KUS_2022-06-27_final.stac-item
2022-07-16 10:34:16	ga_s2am_ard_3-2-1_53JQN_2022-07-16_final.stac-item
2022-07-21 11:26:37	ga_s2am_ard_3-2-1_51HWE_2022-07-21_final.stac-item
2022-09-02 11:33:54	ga_s2am_ard_3-2-1_51KWR_2022-09-02_final.stac-item
2022-09-14 12:15:10	ga_s2am_ard_3-2-1_49JFM_2022-09-14_final.stac-item
2022-11-22 11:01:32	ga_s2am_ard_3-2-1_52LGJ_2022-11-22_final.stac-item
2023-01-17 11:23:39	ga_s2am_ard_3-2-1_51KXR_2023-01-17_final.stac-item
2023-02-08 10:22:23	ga_s2am_ard_3-2-1_54KXD_2023-02-08_final
2023-04-07 11:23:03	ga_s2am_ard_3-2-1_52KCC_2023-04-07_final
2023-05-12 10:33:44	ga_s2am_ard_3-2-1_54KTU_2023-05-12_final
2023-05-29 12:05:55	ga_s2am_ard_3-2-1_50JLN_2023-05-29_final
2023-06-02 11:43:33	ga_s2am_ard_3-2-1_51KUS_2023-06-02_final
2023-06-12 11:42:25	ga_s2am_ard_3-2-1_51KWA_2023-06-12_final
2023-07-06 11:23:26	ga_s2am_ard_3-2-1_52KBB_2023-07-06_final
2023-07-09 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2023-07-09_final
2023-07-22 11:43:29	ga_s2am_ard_3-2-1_51KVS_2023-07-22_final
2023-08-05 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2023-08-05_final
2023-08-30 10:33:55	ga_s2am_ard_3-2-1_53KQP_2023-08-30_final
2023-09-04 11:23:12	ga_s2am_ard_3-2-1_51KZT_2023-09-04_final
2023-09-27 11:33:55	ga_s2am_ard_3-2-1_51KXQ_2023-09-27_final
2023-10-06 10:25:06	ga_s2am_ard_3-2-1_53JQJ_2023-10-06_final
2023-12-06 11:32:52	ga_s2am_ard_3-2-1_51KWU_2023-12-06_final
2023-12-24 10:52:27	ga_s2am_ard_3-2-1_52KHE_2023-12-24_final
2023-12-29 11:42:54	ga_s2am_ard_3-2-1_51KVU_2023-12-29_final
2024-01-05 11:36:20	ga_s2am_ard_3-2-1_51HVE_2024-01-05_final
2024-01-17 10:33:45	ga_s2am_ard_3-2-1_53KPP_2024-01-17_final
2024-01-31 10:13:41	ga_s2am_ard_3-2-1_54JZT_2024-01-31_final
2024-03-05 11:34:03	ga_s2am_ard_3-2-1_51KUQ_2024-03-05_final
2024-03-20 10:45:09	ga_s2am_ard_3-2-1_53JMJ_2024-03-20_final
2024-04-03 10:24:28	ga_s2am_ard_3-2-1_54JUR_2024-04-03_final
2024-04-29 10:43:54	ga_s2am_ard_3-2-1_53KNP_2024-04-29_final
2024-04-29 10:46:01	ga_s2am_ard_3-2-1_53JKF_2024-04-29_final
2024-05-18 11:16:46	ga_s2am_ard_3-2-1_51HWD_2024-05-18_final
2024-05-21 11:23:06	ga_s2am_ard_3-2-1_52KBC_2024-05-21_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

All years