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
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JFM_2015-10-21_final.stac-item
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JGL_2015-10-21_final.stac-item
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49JGM_2015-10-21_final.stac-item
2015-11-20 12:14:39	ga_s2am_ard_3-2-1_49JGL_2015-11-20_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49JGL_2015-11-30_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_49KHR_2015-12-27_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49JGM_2015-12-30_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HNG_2016-01-07_final
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49JFM_2016-01-09_final.stac-item
2016-04-08 12:14:44	ga_s2am_ard_3-2-1_49JFM_2016-04-08_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JGM_2016-11-14_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JGM_2016-11-24_final.stac-item
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_49JGJ_2016-12-21_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2017-02-02_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HNK_2017-05-24_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49KGP_2017-08-21_final.stac-item
2017-12-06 12:04:36	ga_s2am_ard_3-2-1_49JGL_2017-12-06_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGK_2017-12-16_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JGM_2018-02-17_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-02-24_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HNH_2018-03-10_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HNK_2018-03-20_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGM_2018-05-15_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HNJ_2018-07-08_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HPH_2018-07-25_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLJ_2018-07-31_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KGR_2018-08-06_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HMK_2018-08-07_final.stac-item
2018-11-11 12:03:54	ga_s2am_ard_3-2-1_49KHR_2018-11-11_final.stac-item
2018-12-04 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2018-12-04_final.stac-item
2018-12-18 11:56:46	ga_s2am_ard_3-2-1_50HLJ_2018-12-18_final.stac-item
2019-01-03 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-01-03_final.stac-item
2019-01-20 12:04:57	ga_s2am_ard_3-2-1_49JGM_2019-01-20_final.stac-item
2019-02-09 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-09_final.stac-item
2019-08-01 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-08-01_final.stac-item
2019-09-14 11:56:39	ga_s2am_ard_3-2-1_50HLK_2019-09-14_final.stac-item
2019-10-31 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-10-31_final.stac-item
2019-11-10 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-11-10_final.stac-item
2019-11-16 12:04:30	ga_s2am_ard_3-2-1_49KHP_2019-11-16_final.stac-item
2019-12-29 12:14:54	ga_s2am_ard_3-2-1_49JFM_2019-12-29_final.stac-item
2019-12-30 11:47:01	ga_s2am_ard_3-2-1_50HNH_2019-12-30_final.stac-item
2020-01-25 12:03:52	ga_s2am_ard_3-2-1_49KHR_2020-01-25_final.stac-item
2020-02-11 11:56:33	ga_s2am_ard_3-2-1_50HLK_2020-02-11_final.stac-item
2020-02-17 12:15:04	ga_s2am_ard_3-2-1_49JGL_2020-02-17_final.stac-item
2020-05-08 11:46:45	ga_s2am_ard_3-2-1_50HMK_2020-05-08_final.stac-item
2020-06-03 12:05:07	ga_s2am_ard_3-2-1_49JGM_2020-06-03_final.stac-item
2020-06-20 11:56:36	ga_s2am_ard_3-2-1_50HNK_2020-06-20_final.stac-item
2020-06-27 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-06-27_final.stac-item
2020-08-02 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-08-02_final.stac-item
2020-08-06 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-08-06_final.stac-item
2020-08-19 11:56:35	ga_s2am_ard_3-2-1_50HNK_2020-08-19_final.stac-item
2020-09-21 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-09-21_final.stac-item
2020-09-24 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-09-24_final.stac-item
2020-10-28 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-10-28_final.stac-item
2021-01-26 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2021-01-26_final.stac-item
2021-02-21 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2021-02-21_final.stac-item
2021-02-28 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-02-28_final
2021-03-03 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-03-03_final.stac-item
2021-03-04 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-03-04_final.stac-item
2021-06-28 12:04:01	ga_s2am_ard_3-2-1_49KHR_2021-06-28_final.stac-item
2021-06-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-06-28_final.stac-item
2021-09-16 12:04:33	ga_s2am_ard_3-2-1_49KGP_2021-09-16_final.stac-item
2021-10-26 12:04:36	ga_s2am_ard_3-2-1_49KGP_2021-10-26_final.stac-item
2021-11-08 12:13:58	ga_s2am_ard_3-2-1_49KHR_2021-11-08_final.stac-item
2021-11-08 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2021-11-08_final.stac-item
2021-11-19 11:47:21	ga_s2am_ard_3-2-1_50HNG_2021-11-19_final
2021-11-19 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-11-19_final
2021-11-28 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-11-28_final.stac-item
2021-12-12 11:57:08	ga_s2am_ard_3-2-1_50HLH_2021-12-12_final.stac-item
2022-01-04 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-01-04_final.stac-item
2022-01-11 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-11_final.stac-item
2022-02-13 12:05:29	ga_s2am_ard_3-2-1_49JGK_2022-02-13_final.stac-item
2022-03-08 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-03-08_final.stac-item
2022-04-07 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-04-07_final.stac-item
2022-05-04 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-05-04_final.stac-item
2022-05-18 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2022-05-18_final.stac-item
2022-06-27 11:46:50	ga_s2am_ard_3-2-1_50HNK_2022-06-27_final.stac-item
2022-09-02 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-09-02_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2022-12-03 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-12-03_final.stac-item
2022-12-13 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-12-13_final.stac-item
2023-01-09 12:04:44	ga_s2am_ard_3-2-1_49JGN_2023-01-09_final.stac-item
2023-02-01 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-02-01_final.stac-item
2023-02-18 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-18_final
2023-05-09 12:03:59	ga_s2am_ard_3-2-1_49KHR_2023-05-09_final
2023-05-09 12:05:29	ga_s2am_ard_3-2-1_49JGK_2023-05-09_final
2023-06-22 11:47:10	ga_s2am_ard_3-2-1_50HNH_2023-06-22_final
2023-09-03 11:57:05	ga_s2am_ard_3-2-1_50HLJ_2023-09-03_final
2023-10-23 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2023-10-23_final
2023-11-18 12:13:52	ga_s2am_ard_3-2-1_49KHR_2023-11-18_final
2023-11-19 11:47:12	ga_s2am_ard_3-2-1_50HLH_2023-11-19_final
2023-12-22 11:56:26	ga_s2am_ard_3-2-1_50HNK_2023-12-22_final
2024-01-07 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2024-01-07_final
2024-01-11 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2024-01-11_final
2024-01-14 12:03:53	ga_s2am_ard_3-2-1_49KHR_2024-01-14_final
2024-01-31 11:56:35	ga_s2am_ard_3-2-1_50HLK_2024-01-31_final
2024-02-06 12:13:50	ga_s2am_ard_3-2-1_49KHR_2024-02-06_final
2024-03-01 11:56:30	ga_s2am_ard_3-2-1_50HNK_2024-03-01_final
2024-04-13 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2024-04-13_final
2024-05-10 11:57:12	ga_s2am_ard_3-2-1_50HLH_2024-05-10_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