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
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLR_2016-04-02_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51JUF_2016-04-23_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HQK_2016-05-29_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51JTF_2016-09-13_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KKB_2016-10-22_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50KRC_2017-02-16_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50HMJ_2017-09-01_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HMJ_2017-10-24_final.stac-item
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JGM_2017-10-30_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JML_2018-07-18_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNM_2018-07-21_final.stac-item
2018-09-27 11:12:40	ga_s2am_ard_3-2-1_51HXD_2018-09-27_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-10-12_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HNJ_2018-10-26_final.stac-item
2018-11-08 11:53:06	ga_s2am_ard_3-2-1_50KRC_2018-11-08_final.stac-item
2018-12-11 12:04:52	ga_s2am_ard_3-2-1_49JGM_2018-12-11_final.stac-item
2018-12-21 12:05:32	ga_s2am_ard_3-2-1_50JKP_2018-12-21_final.stac-item
2018-12-31 12:03:38	ga_s2am_ard_3-2-1_50KKB_2018-12-31_final.stac-item
2019-04-17 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-04-17_final.stac-item
2019-04-23 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-04-23_final.stac-item
2019-05-08 11:27:02	ga_s2am_ard_3-2-1_51HVC_2019-05-08_final.stac-item
2019-06-12 12:13:57	ga_s2am_ard_3-2-1_50KKA_2019-06-12_final.stac-item
2019-06-27 11:26:45	ga_s2am_ard_3-2-1_51HWD_2019-06-27_final.stac-item
2019-07-09 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-07-20 11:36:37	ga_s2am_ard_3-2-1_51HTE_2019-07-20_final.stac-item
2019-09-04 11:56:14	ga_s2am_ard_3-2-1_50JKM_2019-09-04_final.stac-item
2019-10-31 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-10-31_final.stac-item
2019-12-04 11:26:56	ga_s2am_ard_3-2-1_51HVC_2019-12-04_final.stac-item
2019-12-31 11:16:31	ga_s2am_ard_3-2-1_51HYD_2019-12-31_final.stac-item
2020-01-09 11:45:26	ga_s2am_ard_3-2-1_50JQP_2020-01-09_final.stac-item
2020-01-12 11:55:54	ga_s2am_ard_3-2-1_50JKN_2020-01-12_final.stac-item
2020-04-14 12:03:43	ga_s2am_ard_3-2-1_50KKB_2020-04-14_final.stac-item
2020-04-25 11:35:00	ga_s2am_ard_3-2-1_51JVL_2020-04-25_final.stac-item
2020-06-21 11:27:04	ga_s2am_ard_3-2-1_51HVC_2020-06-21_final.stac-item
2020-06-24 11:36:52	ga_s2am_ard_3-2-1_51HTD_2020-06-24_final.stac-item
2020-07-24 11:36:43	ga_s2am_ard_3-2-1_50HPK_2020-07-24_final.stac-item
2020-08-06 11:46:00	ga_s2am_ard_3-2-1_50JNN_2020-08-06_final.stac-item
2020-08-10 11:26:53	ga_s2am_ard_3-2-1_51HUD_2020-08-10_final.stac-item
2020-08-25 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-08-25_final.stac-item
2020-09-12 11:37:01	ga_s2am_ard_3-2-1_51HUC_2020-09-12_final.stac-item
2020-09-25 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-09-25_final.stac-item
2020-11-07 11:52:24	ga_s2am_ard_3-2-1_50KQG_2020-11-07_final
2021-01-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-01-02_final.stac-item
2021-01-09 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2021-01-09_final.stac-item
2021-01-10 11:35:48	ga_s2am_ard_3-2-1_51JTH_2021-01-10_final.stac-item
2021-01-24 11:16:37	ga_s2am_ard_3-2-1_51HYD_2021-01-24_final.stac-item
2021-02-02 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-02-02_final.stac-item
2021-03-01 11:34:36	ga_s2am_ard_3-2-1_50JRT_2021-03-01_final.stac-item
2021-03-04 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-03-04_final.stac-item
2021-04-06 11:53:13	ga_s2am_ard_3-2-1_50KQC_2021-04-06_final.stac-item
2021-04-13 11:43:45	ga_s2am_ard_3-2-1_50KQA_2021-04-13_final.stac-item
2021-05-26 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-05-26_final
2021-06-09 11:35:34	ga_s2am_ard_3-2-1_51JTJ_2021-06-09_final.stac-item
2021-06-22 11:44:46	ga_s2am_ard_3-2-1_50JRS_2021-06-22_final.stac-item
2021-08-17 12:03:26	ga_s2am_ard_3-2-1_50KMC_2021-08-17_final.stac-item
2021-08-20 12:15:13	ga_s2am_ard_3-2-1_49JGL_2021-08-20_final.stac-item
2021-09-27 11:36:32	ga_s2am_ard_3-2-1_51HUE_2021-09-27_final.stac-item
2021-10-01 11:16:45	ga_s2am_ard_3-2-1_51HXD_2021-10-01_final.stac-item
2021-10-03 11:56:09	ga_s2am_ard_3-2-1_50JNM_2021-10-03_final.stac-item
2021-12-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-12-18_final.stac-item
2022-01-15 11:34:33	ga_s2am_ard_3-2-1_51JUN_2022-01-15_final.stac-item
2022-01-15 11:34:44	ga_s2am_ard_3-2-1_51JVM_2022-01-15_final.stac-item
2022-01-24 12:03:59	ga_s2am_ard_3-2-1_49KHR_2022-01-24_final.stac-item
2022-01-27 12:13:54	ga_s2am_ard_3-2-1_50KKA_2022-01-27_final.stac-item
2022-02-24 11:36:45	ga_s2am_ard_3-2-1_51HUD_2022-02-24_final.stac-item
2022-02-27 11:46:44	ga_s2am_ard_3-2-1_50HMK_2022-02-27_final.stac-item
2022-03-02 11:53:24	ga_s2am_ard_3-2-1_50KPC_2022-03-02_final.stac-item
2022-05-18 11:46:31	ga_s2am_ard_3-2-1_50JML_2022-05-18_final.stac-item
2022-05-24 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-05-24_final.stac-item
2022-05-28 11:43:59	ga_s2am_ard_3-2-1_50KQA_2022-05-28_final.stac-item
2022-06-26 12:14:07	ga_s2am_ard_3-2-1_50KKA_2022-06-26_final.stac-item
2022-08-02 12:04:09	ga_s2am_ard_3-2-1_49KHR_2022-08-02_final.stac-item
2022-08-25 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-08-25_final.stac-item
2022-09-01 12:03:35	ga_s2am_ard_3-2-1_50KMC_2022-09-01_final.stac-item
2022-09-05 11:45:17	ga_s2am_ard_3-2-1_50JQR_2022-09-05_final.stac-item
2022-09-08 11:55:46	ga_s2am_ard_3-2-1_50JNP_2022-09-08_final.stac-item
2022-09-16 11:16:32	ga_s2am_ard_3-2-1_51HYE_2022-09-16_final.stac-item
2022-10-01 12:03:27	ga_s2am_ard_3-2-1_50KNC_2022-10-01_final.stac-item
2022-10-25 11:43:24	ga_s2am_ard_3-2-1_50KQC_2022-10-25_final.stac-item
2022-12-23 12:13:37	ga_s2am_ard_3-2-1_50KKB_2022-12-23_final.stac-item
2023-01-06 11:53:16	ga_s2am_ard_3-2-1_50KQC_2023-01-06_final.stac-item
2023-01-10 11:36:41	ga_s2am_ard_3-2-1_51HUD_2023-01-10_final.stac-item
2023-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-02-05_final
2023-02-13 11:16:57	ga_s2am_ard_3-2-1_51HWC_2023-02-13_final
2023-02-28 12:03:57	ga_s2am_ard_3-2-1_49KHR_2023-02-28_final
2023-03-27 11:53:34	ga_s2am_ard_3-2-1_50KPB_2023-03-27_final
2023-03-27 11:55:51	ga_s2am_ard_3-2-1_50JMN_2023-03-27_final
2023-04-09 12:04:33	ga_s2am_ard_3-2-1_50KLU_2023-04-09_final
2023-05-19 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-05-19_final
2023-06-05 11:53:25	ga_s2am_ard_3-2-1_50KPC_2023-06-05_final
2023-06-11 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-11_final
2023-07-28 12:05:43	ga_s2am_ard_3-2-1_50JLP_2023-07-28_final
2023-08-28 11:37:06	ga_s2am_ard_3-2-1_51HTC_2023-08-28_final
2023-09-06 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-09-06_final
2023-10-13 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-10-13_final
2023-11-05 12:03:22	ga_s2am_ard_3-2-1_50KMC_2023-11-05_final
2024-01-11 11:55:59	ga_s2am_ard_3-2-1_50JNM_2024-01-11_final
2024-01-11 11:56:13	ga_s2am_ard_3-2-1_50JNL_2024-01-11_final
2024-01-24 12:03:53	ga_s2am_ard_3-2-1_49KHR_2024-01-24_final
2024-02-10 11:53:07	ga_s2am_ard_3-2-1_50KRC_2024-02-10_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