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
2015-11-27 12:04:51	ga_s2am_ard_3-2-1_49JGL_2015-11-27_final.stac-item
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_53HLD_2015-11-30_final.stac-item
2016-03-11 11:07:04	ga_s2am_ard_3-2-1_52LHM_2016-03-11_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KVT_2016-04-06_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_51KTT_2016-04-29_final.stac-item
2016-05-07 11:02:16	ga_s2am_ard_3-2-1_52KHA_2016-05-07_final.stac-item
2016-05-08 10:34:29	ga_s2am_ard_3-2-1_53HLE_2016-05-08_final.stac-item
2016-05-26 11:36:09	ga_s2am_ard_3-2-1_50JQL_2016-05-26_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50JRT_2016-11-02_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HPK_2016-12-05_final.stac-item
2016-12-23 10:57:35	ga_s2am_ard_3-2-1_52LGH_2016-12-23_final.stac-item
2017-05-05 11:07:15	ga_s2am_ard_3-2-1_52LHN_2017-05-05_final.stac-item
2017-06-28 10:53:13	ga_s2am_ard_3-2-1_53JLL_2017-06-28_final.stac-item
2017-07-10 11:28:37	ga_s2am_ard_3-2-1_51KWS_2017-07-10_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_52LBK_2017-07-17_final.stac-item
2017-10-12 11:07:11	ga_s2am_ard_3-2-1_52KEG_2017-10-12_final.stac-item
2017-12-04 11:22:04	ga_s2am_ard_3-2-1_51KYB_2017-12-04_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_50JRT_2017-12-17_final.stac-item
2018-03-14 11:21:15	ga_s2am_ard_3-2-1_51HVC_2018-03-14_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_52KBF_2018-04-23_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JLT_2018-05-12_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52JBL_2018-07-26_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_49KHP_2018-11-11_final.stac-item
2019-01-10 10:26:31	ga_s2am_ard_3-2-1_53HPC_2019-01-10_final.stac-item
2019-02-07 11:25:00	ga_s2am_ard_3-2-1_51JVL_2019-02-07_final.stac-item
2019-03-11 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-03-11_final.stac-item
2019-04-06 10:44:29	ga_s2am_ard_3-2-1_53JPL_2019-04-06_final.stac-item
2019-05-31 11:33:26	ga_s2am_ard_3-2-1_51KXS_2019-05-31_final.stac-item
2019-06-20 11:36:50	ga_s2am_ard_3-2-1_51HTD_2019-06-20_final.stac-item
2019-06-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-06-30_final.stac-item
2019-07-30 11:33:32	ga_s2am_ard_3-2-1_51KWS_2019-07-30_final.stac-item
2019-08-10 11:03:38	ga_s2am_ard_3-2-1_52KEA_2019-08-10_final.stac-item
2019-09-17 10:25:05	ga_s2am_ard_3-2-1_53JQJ_2019-09-17_final.stac-item
2020-01-08 10:35:10	ga_s2am_ard_3-2-1_53JQH_2020-01-08_final.stac-item
2020-02-11 11:56:06	ga_s2am_ard_3-2-1_50JKM_2020-02-11_final.stac-item
2020-02-15 11:33:32	ga_s2am_ard_3-2-1_51KXR_2020-02-15_final.stac-item
2020-05-14 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-05-14_final.stac-item
2020-05-30 10:45:20	ga_s2am_ard_3-2-1_53JKJ_2020-05-30_final.stac-item
2020-06-23 10:27:11	ga_s2am_ard_3-2-1_53HPA_2020-06-23_final.stac-item
2020-07-23 12:04:04	ga_s2am_ard_3-2-1_50KKA_2020-07-23_final.stac-item
2020-09-12 11:33:44	ga_s2am_ard_3-2-1_51KXR_2020-09-12_final.stac-item
2020-09-22 11:33:27	ga_s2am_ard_3-2-1_51KUT_2020-09-22_final.stac-item
2020-09-27 10:45:05	ga_s2am_ard_3-2-1_53JKK_2020-09-27_final.stac-item
2020-10-13 11:04:49	ga_s2am_ard_3-2-1_52JFR_2020-10-13_final.stac-item
2020-11-01 11:33:53	ga_s2am_ard_3-2-1_51KUR_2020-11-01_final.stac-item
2020-11-05 11:13:59	ga_s2am_ard_3-2-1_52KBV_2020-11-05_final.stac-item
2020-11-06 10:46:00	ga_s2am_ard_3-2-1_53JLF_2020-11-06_final.stac-item
2020-11-19 10:55:45	ga_s2am_ard_3-2-1_52JGM_2020-11-19_final.stac-item
2020-11-27 10:17:05	ga_s2am_ard_3-2-1_53HQA_2020-11-27_final.stac-item
2020-12-01 11:34:05	ga_s2am_ard_3-2-1_51KXP_2020-12-01_final.stac-item
2021-03-08 11:26:18	ga_s2am_ard_3-2-1_51JUF_2021-03-08_final.stac-item
2021-05-03 11:45:27	ga_s2am_ard_3-2-1_51JTJ_2021-05-03_final.stac-item
2021-06-21 12:13:55	ga_s2am_ard_3-2-1_50KKA_2021-06-21_final.stac-item
2021-09-07 11:33:53	ga_s2am_ard_3-2-1_51KXQ_2021-09-07_final.stac-item
2021-09-16 10:26:37	ga_s2am_ard_3-2-1_53HPC_2021-09-16_final.stac-item
2021-09-24 11:27:05	ga_s2am_ard_3-2-1_51HUC_2021-09-24_final.stac-item
2021-11-15 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2021-11-15_final.stac-item
2022-01-02 11:27:03	ga_s2am_ard_3-2-1_51HUC_2022-01-02_final.stac-item
2022-01-25 11:35:50	ga_s2am_ard_3-2-1_50JQN_2022-01-25_final.stac-item
2022-02-07 11:46:40	ga_s2am_ard_3-2-1_50HMK_2022-02-07_final.stac-item
2022-02-24 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2022-02-24_final.stac-item
2022-04-07 10:35:02	ga_s2am_ard_3-2-1_53JQJ_2022-04-07_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 11:23:18	ga_s2am_ard_3-2-1_51KXT_2022-05-02_final.stac-item
2022-05-20 10:45:35	ga_s2am_ard_3-2-1_53JKH_2022-05-20_final.stac-item
2022-05-24 10:26:10	ga_s2am_ard_3-2-1_53HPE_2022-05-24_final.stac-item
2022-06-04 11:33:21	ga_s2am_ard_3-2-1_51KWT_2022-06-04_final.stac-item
2022-06-14 11:34:07	ga_s2am_ard_3-2-1_51KWQ_2022-06-14_final.stac-item
2022-07-06 10:35:00	ga_s2am_ard_3-2-1_53JQK_2022-07-06_final.stac-item
2022-07-18 11:16:25	ga_s2am_ard_3-2-1_52HBK_2022-07-18_final.stac-item
2022-07-26 12:14:04	ga_s2am_ard_3-2-1_50KKA_2022-07-26_final.stac-item
2022-08-03 11:35:58	ga_s2am_ard_3-2-1_51JTH_2022-08-03_final.stac-item
2022-08-21 10:54:34	ga_s2am_ard_3-2-1_52JFT_2022-08-21_final.stac-item
2022-08-31 10:53:40	ga_s2am_ard_3-2-1_53KKR_2022-08-31_final.stac-item
2022-09-10 10:54:37	ga_s2am_ard_3-2-1_53JKM_2022-09-10_final.stac-item
2022-10-10 10:55:55	ga_s2am_ard_3-2-1_52JEM_2022-10-10_final.stac-item
2022-10-26 11:16:00	ga_s2am_ard_3-2-1_51JXG_2022-10-26_final.stac-item
2022-11-19 10:55:43	ga_s2am_ard_3-2-1_52JGM_2022-11-19_final.stac-item
2022-11-28 11:23:28	ga_s2am_ard_3-2-1_51KXS_2022-11-28_final.stac-item
2023-01-20 11:33:17	ga_s2am_ard_3-2-1_51KUT_2023-01-20_final.stac-item
2023-01-27 11:24:16	ga_s2am_ard_3-2-1_51JZN_2023-01-27_final.stac-item
2023-02-07 10:55:04	ga_s2am_ard_3-2-1_52JGP_2023-02-07_final
2023-02-08 10:24:20	ga_s2am_ard_3-2-1_53JRM_2023-02-08_final
2023-02-22 11:46:35	ga_s2am_ard_3-2-1_50HNK_2023-02-22_final
2023-04-19 10:26:53	ga_s2am_ard_3-2-1_53HNB_2023-04-19_final
2023-05-15 10:45:47	ga_s2am_ard_3-2-1_52JGM_2023-05-15_final
2023-05-17 11:27:00	ga_s2am_ard_3-2-1_51HVC_2023-05-17_final
2023-06-25 11:56:07	ga_s2am_ard_3-2-1_50JNM_2023-06-25_final
2023-07-27 10:53:37	ga_s2am_ard_3-2-1_52KGA_2023-07-27_final
2023-08-08 11:32:30	ga_s2am_ard_3-2-1_51KXA_2023-08-08_final
2023-09-20 11:43:02	ga_s2am_ard_3-2-1_51KUU_2023-09-20_final
2023-11-06 11:33:44	ga_s2am_ard_3-2-1_51KVR_2023-11-06_final
2023-11-12 11:53:17	ga_s2am_ard_3-2-1_50KQC_2023-11-12_final
2023-11-27 11:06:04	ga_s2am_ard_3-2-1_52JBL_2023-11-27_final
2024-01-09 11:10:13	ga_s2am_ard_3-2-1_52LFP_2024-01-09_final
2024-02-04 11:31:44	ga_s2am_ard_3-2-1_51LZC_2024-02-04_final
2024-02-06 12:13:50	ga_s2am_ard_3-2-1_49KHR_2024-02-06_final
2024-03-11 11:55:56	ga_s2am_ard_3-2-1_50JLN_2024-03-11_final
2024-04-19 10:46:03	ga_s2am_ard_3-2-1_52JGL_2024-04-19_final
2024-04-27 11:43:02	ga_s2am_ard_3-2-1_51KUU_2024-04-27_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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