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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JLM_2015-11-14_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HLK_2016-01-03_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HQK_2016-05-09_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JKR_2016-06-24_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50HLK_2016-08-30_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49JFM_2016-09-15_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHQ_2016-11-01_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JKN_2016-11-18_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2016-12-11_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HMG_2016-12-25_final
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49JGJ_2017-03-11_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLN_2017-03-18_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_49JGL_2017-04-30_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KHR_2017-05-13_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49KGP_2017-06-02_final.stac-item
2017-07-16 11:56:34	ga_s2am_ard_3-2-1_50HLH_2017-07-16_final.stac-item
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50HQK_2017-07-23_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49KGP_2017-08-18_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50HQK_2017-09-21_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49JFM_2017-10-10_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49KGP_2017-10-20_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JLL_2017-10-24_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KGP_2017-12-16_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50JLP_2018-01-05_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HLH_2018-03-20_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2018-04-25_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49JGM_2018-05-18_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKR_2018-05-25_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HPH_2018-07-15_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-09-12_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLM_2018-09-29_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNH_2018-10-16_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49KGP_2018-11-04_final.stac-item
2018-12-14 12:14:33	ga_s2am_ard_3-2-1_49JGN_2018-12-14_final.stac-item
2018-12-31 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2018-12-31_final.stac-item
2019-01-30 12:05:48	ga_s2am_ard_3-2-1_50JLN_2019-01-30_final.stac-item
2019-02-09 12:05:43	ga_s2am_ard_3-2-1_50JLN_2019-02-09_final.stac-item
2019-03-11 12:05:36	ga_s2am_ard_3-2-1_50JKP_2019-03-11_final.stac-item
2019-03-31 12:04:43	ga_s2am_ard_3-2-1_50JKT_2019-03-31_final.stac-item
2019-04-03 12:14:57	ga_s2am_ard_3-2-1_49JGM_2019-04-03_final.stac-item
2019-04-20 12:05:18	ga_s2am_ard_3-2-1_49JGL_2019-04-20_final.stac-item
2019-05-10 12:05:55	ga_s2am_ard_3-2-1_50JLN_2019-05-10_final.stac-item
2019-05-30 12:04:07	ga_s2am_ard_3-2-1_49KHR_2019-05-30_final.stac-item
2019-06-16 11:56:40	ga_s2am_ard_3-2-1_50HMK_2019-06-16_final.stac-item
2019-06-30 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-06-30_final.stac-item
2019-07-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-07-02_final.stac-item
2019-07-13 11:46:42	ga_s2am_ard_3-2-1_50HNK_2019-07-13_final.stac-item
2019-09-30 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2019-09-30_final.stac-item
2019-10-24 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-10-24_final.stac-item
2019-11-26 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-11-26_final.stac-item
2020-03-02 11:56:25	ga_s2am_ard_3-2-1_50HNK_2020-03-02_final.stac-item
2020-03-05 12:06:00	ga_s2am_ard_3-2-1_50JLM_2020-03-05_final.stac-item
2020-04-04 12:04:14	ga_s2am_ard_3-2-1_49KGQ_2020-04-04_final.stac-item
2020-04-28 11:46:32	ga_s2am_ard_3-2-1_50HQK_2020-04-28_final.stac-item
2020-05-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-05-04_final.stac-item
2020-05-07 12:14:02	ga_s2am_ard_3-2-1_49KGR_2020-05-07_final.stac-item
2020-06-06 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-06-06_final.stac-item
2020-06-07 11:46:49	ga_s2am_ard_3-2-1_50HQJ_2020-06-07_final.stac-item
2020-06-20 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-06-20_final.stac-item
2020-10-18 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-10-18_final.stac-item
2020-11-21 11:36:42	ga_s2am_ard_3-2-1_50HQK_2020-11-21_final.stac-item
2020-12-20 12:04:55	ga_s2am_ard_3-2-1_50JKS_2020-12-20_final.stac-item
2021-03-17 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-03-17_final
2021-03-20 12:04:30	ga_s2am_ard_3-2-1_49KGP_2021-03-20_final.stac-item
2021-04-03 11:46:37	ga_s2am_ard_3-2-1_50HMK_2021-04-03_final.stac-item
2021-04-19 12:05:46	ga_s2am_ard_3-2-1_50JLN_2021-04-19_final.stac-item
2021-05-20 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-05-20_final.stac-item
2021-05-23 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-05-23_final.stac-item
2021-06-15 11:56:30	ga_s2am_ard_3-2-1_50HNK_2021-06-15_final.stac-item
2021-08-11 11:46:32	ga_s2am_ard_3-2-1_50HQK_2021-08-11_final.stac-item
2022-01-04 12:05:53	ga_s2am_ard_3-2-1_50JLN_2022-01-04_final.stac-item
2022-02-23 12:05:54	ga_s2am_ard_3-2-1_50JLN_2022-02-23_final.stac-item
2022-04-11 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-04-11_final.stac-item
2022-06-23 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-06-23_final.stac-item
2022-07-13 12:04:39	ga_s2am_ard_3-2-1_49KHP_2022-07-13_final.stac-item
2022-08-22 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-08-22_final.stac-item
2022-08-25 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-08-25_final.stac-item
2022-11-13 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-11-13_final.stac-item
2022-11-21 11:37:03	ga_s2am_ard_3-2-1_50HQH_2022-11-21_final.stac-item
2022-12-13 12:13:58	ga_s2am_ard_3-2-1_49KGR_2022-12-13_final.stac-item
2023-01-09 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-01-09_final.stac-item
2023-01-09 12:05:10	ga_s2am_ard_3-2-1_50JKR_2023-01-09_final.stac-item
2023-03-01 11:37:18	ga_s2am_ard_3-2-1_50HPG_2023-03-01_final
2023-03-04 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-03-04_final
2023-03-27 11:55:54	ga_s2am_ard_3-2-1_50JLN_2023-03-27_final
2023-05-23 11:47:05	ga_s2am_ard_3-2-1_50HPH_2023-05-23_final
2023-06-08 12:04:49	ga_s2am_ard_3-2-1_49JGN_2023-06-08_final
2023-08-20 12:14:04	ga_s2am_ard_3-2-1_49KGR_2023-08-20_final
2023-08-27 12:04:37	ga_s2am_ard_3-2-1_49KGP_2023-08-27_final
2023-10-06 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2023-10-06_final
2023-11-09 11:46:40	ga_s2am_ard_3-2-1_50HMK_2023-11-09_final
2023-11-19 11:47:04	ga_s2am_ard_3-2-1_50HNH_2023-11-19_final
2023-11-22 11:55:52	ga_s2am_ard_3-2-1_50JLN_2023-11-22_final
2023-12-02 11:56:03	ga_s2am_ard_3-2-1_50JLM_2023-12-02_final
2023-12-02 11:56:17	ga_s2am_ard_3-2-1_50JLL_2023-12-02_final
2023-12-06 11:37:15	ga_s2am_ard_3-2-1_50HPG_2023-12-06_final
2023-12-15 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2023-12-15_final
2023-12-28 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2023-12-28_final
2024-01-04 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2024-01-04_final
2024-02-17 11:46:41	ga_s2am_ard_3-2-1_50HQJ_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