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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JHN_2015-10-28_final.stac-item
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHS_2015-10-28_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49KGQ_2015-12-17_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50JKM_2016-02-15_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNG_2016-03-20_final
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JGL_2016-07-07_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-08-26_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-02_final
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGN_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JKQ_2016-10-22_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JLP_2016-11-01_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_50JKQ_2017-03-21_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HMJ_2017-03-25_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JKQ_2017-05-10_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49JGL_2017-05-13_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50HNK_2017-06-26_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50HPJ_2017-11-07_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HMK_2018-01-19_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HLH_2018-02-18_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HNJ_2018-02-28_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49KGR_2018-03-29_final.stac-item
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_50HQJ_2018-04-26_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HPH_2018-05-19_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JLP_2018-06-24_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HLH_2018-07-11_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HQK_2018-07-25_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKS_2018-08-13_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50HMK_2018-09-09_final.stac-item
2018-12-31 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2018-12-31_final.stac-item
2019-01-20 12:04:24	ga_s2am_ard_3-2-1_49KHP_2019-01-20_final.stac-item
2019-02-03 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2019-02-03_final.stac-item
2019-02-09 12:04:25	ga_s2am_ard_3-2-1_49KHP_2019-02-09_final.stac-item
2019-03-18 11:55:39	ga_s2am_ard_3-2-1_50JLP_2019-03-18_final.stac-item
2019-03-24 12:14:07	ga_s2am_ard_3-2-1_49KHQ_2019-03-24_final.stac-item
2019-06-03 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2019-06-03_final.stac-item
2019-10-24 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-10-24_final.stac-item
2019-11-23 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2019-11-23_final.stac-item
2019-12-19 12:14:03	ga_s2am_ard_3-2-1_49KHQ_2019-12-19_final.stac-item
2020-01-05 12:04:37	ga_s2am_ard_3-2-1_50JKT_2020-01-05_final.stac-item
2020-02-14 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2020-02-14_final.stac-item
2020-02-27 12:14:04	ga_s2am_ard_3-2-1_49KHQ_2020-02-27_final.stac-item
2020-05-11 11:57:10	ga_s2am_ard_3-2-1_50HMH_2020-05-11_final.stac-item
2020-06-23 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-06-23_final.stac-item
2020-07-03 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-07-03_final.stac-item
2020-07-10 11:57:13	ga_s2am_ard_3-2-1_50HLH_2020-07-10_final.stac-item
2020-07-27 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-07-27_final.stac-item
2020-10-18 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-10-18_final.stac-item
2020-10-18 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-10-18_final.stac-item
2021-02-05 11:56:36	ga_s2am_ard_3-2-1_50HMK_2021-02-05_final.stac-item
2021-03-07 11:56:06	ga_s2am_ard_3-2-1_50JLM_2021-03-07_final.stac-item
2021-04-26 11:55:38	ga_s2am_ard_3-2-1_50JLP_2021-04-26_final.stac-item
2021-04-29 12:05:26	ga_s2am_ard_3-2-1_49JGK_2021-04-29_final.stac-item
2021-05-13 11:46:40	ga_s2am_ard_3-2-1_50HMK_2021-05-13_final.stac-item
2021-05-20 11:36:34	ga_s2am_ard_3-2-1_50HQK_2021-05-20_final.stac-item
2021-05-20 11:37:27	ga_s2am_ard_3-2-1_50HNG_2021-05-20_final
2021-06-15 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-06-15_final.stac-item
2021-06-22 11:47:11	ga_s2am_ard_3-2-1_50HMH_2021-06-22_final.stac-item
2021-07-02 11:46:43	ga_s2am_ard_3-2-1_50HMK_2021-07-02_final.stac-item
2021-10-06 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2021-10-06_final.stac-item
2021-10-16 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2021-10-16_final.stac-item
2021-10-16 12:04:48	ga_s2am_ard_3-2-1_50JKT_2021-10-16_final.stac-item
2021-10-26 12:05:17	ga_s2am_ard_3-2-1_50JKR_2021-10-26_final.stac-item
2021-12-09 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2021-12-09_final.stac-item
2021-12-19 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-12-19_final.stac-item
2022-01-01 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-01-01_final.stac-item
2022-01-14 12:04:29	ga_s2am_ard_3-2-1_49KHP_2022-01-14_final.stac-item
2022-02-16 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-02-16_final.stac-item
2022-03-05 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2022-03-05_final.stac-item
2022-04-14 12:05:40	ga_s2am_ard_3-2-1_50JLP_2022-04-14_final.stac-item
2022-05-14 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2022-05-14_final.stac-item
2022-06-20 11:55:54	ga_s2am_ard_3-2-1_50JLP_2022-06-20_final.stac-item
2022-10-08 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-10-08_final.stac-item
2022-10-18 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-10-18_final.stac-item
2022-12-24 11:47:12	ga_s2am_ard_3-2-1_50HLH_2022-12-24_final.stac-item
2023-01-03 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2023-01-03_final.stac-item
2023-01-13 11:46:38	ga_s2am_ard_3-2-1_50HMK_2023-01-13_final.stac-item
2023-02-12 11:46:39	ga_s2am_ard_3-2-1_50HMK_2023-02-12_nrt.stac-item
2023-02-12 11:46:39	ga_s2am_ard_3-2-1_50HMK_2023-02-12_final
2023-02-22 11:47:04	ga_s2am_ard_3-2-1_50HNH_2023-02-22_nrt.stac-item
2023-02-22 11:47:04	ga_s2am_ard_3-2-1_50HNH_2023-02-22_final
2023-03-04 11:46:37	ga_s2am_ard_3-2-1_50HMK_2023-03-04_final
2023-04-10 11:36:34	ga_s2am_ard_3-2-1_50HQK_2023-04-10_final
2023-04-16 11:55:41	ga_s2am_ard_3-2-1_50JLP_2023-04-16_final
2023-04-19 12:05:36	ga_s2am_ard_3-2-1_50JLP_2023-04-19_final
2023-04-23 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-04-23_final
2023-05-03 11:47:10	ga_s2am_ard_3-2-1_50HMH_2023-05-03_final
2023-07-12 11:47:26	ga_s2am_ard_3-2-1_50HNG_2023-07-12_final
2023-07-15 11:57:25	ga_s2am_ard_3-2-1_50HMG_2023-07-15_final
2023-09-26 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2023-09-26_final
2023-10-06 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-10-06_final
2023-10-13 11:57:04	ga_s2am_ard_3-2-1_50HMH_2023-10-13_final
2023-10-16 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-10-16_final
2023-10-20 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2023-10-20_final
2023-11-25 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-11-25_final
2023-12-15 12:04:38	ga_s2am_ard_3-2-1_50JKT_2023-12-15_final
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_50JKT_2023-12-25_final
2024-01-15 11:36:31	ga_s2am_ard_3-2-1_50HPK_2024-01-15_final
2024-01-18 11:47:12	ga_s2am_ard_3-2-1_50HNG_2024-01-18_final
2024-01-25 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2024-01-25_final
2024-02-17 11:47:24	ga_s2am_ard_3-2-1_50HLG_2024-02-17_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