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_50HNK_2015-11-14_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49KGP_2016-02-15_final.stac-item
2016-04-29 11:47:17	ga_s2am_ard_3-2-1_50HNG_2016-04-29_final
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49JFM_2016-06-27_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JKN_2016-08-10_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKS_2016-11-11_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHS_2016-12-21_final
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KHR_2017-02-02_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JLL_2017-02-16_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HMH_2017-03-25_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGL_2017-04-03_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50HLK_2017-05-17_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HLK_2017-05-27_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKS_2017-07-29_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_50HPH_2018-01-06_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HLJ_2018-02-11_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49KHP_2018-03-16_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGK_2018-04-05_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_50HQK_2018-04-16_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50HQK_2018-05-06_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50HLJ_2018-06-01_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50HPK_2018-06-15_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HPK_2018-07-25_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-10-02_final.stac-item
2018-11-14 12:14:25	ga_s2am_ard_3-2-1_49KGP_2018-11-14_final.stac-item
2018-11-21 12:04:11	ga_s2am_ard_3-2-1_49KGQ_2018-11-21_final.stac-item
2018-12-08 11:56:22	ga_s2am_ard_3-2-1_50HNK_2018-12-08_final.stac-item
2018-12-24 12:15:03	ga_s2am_ard_3-2-1_49JGL_2018-12-24_final.stac-item
2018-12-28 11:56:05	ga_s2am_ard_3-2-1_50JLM_2018-12-28_final.stac-item
2019-01-04 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2019-01-04_final.stac-item
2019-01-17 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-01-17_final.stac-item
2019-01-30 12:04:39	ga_s2am_ard_3-2-1_50JKT_2019-01-30_final.stac-item
2019-01-31 11:36:45	ga_s2am_ard_3-2-1_50HQJ_2019-01-31_final.stac-item
2019-02-13 11:46:37	ga_s2am_ard_3-2-1_50HMK_2019-02-13_final.stac-item
2019-02-16 11:55:53	ga_s2am_ard_3-2-1_50JLN_2019-02-16_final.stac-item
2019-03-22 11:36:36	ga_s2am_ard_3-2-1_50HPK_2019-03-22_final.stac-item
2019-04-17 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-04-17_final.stac-item
2019-05-23 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-05-23_final.stac-item
2019-07-29 12:04:36	ga_s2am_ard_3-2-1_49KGP_2019-07-29_final.stac-item
2019-09-07 12:05:40	ga_s2am_ard_3-2-1_50JKP_2019-09-07_final.stac-item
2019-10-10 12:13:57	ga_s2am_ard_3-2-1_49KHR_2019-10-10_final.stac-item
2019-10-10 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-10-10_final.stac-item
2019-11-30 11:46:36	ga_s2am_ard_3-2-1_50HNK_2019-11-30_final.stac-item
2019-12-17 11:37:01	ga_s2am_ard_3-2-1_50HPH_2019-12-17_final.stac-item
2019-12-26 12:04:40	ga_s2am_ard_3-2-1_49JGN_2019-12-26_final.stac-item
2020-04-01 11:56:26	ga_s2am_ard_3-2-1_50HNK_2020-04-01_final.stac-item
2020-04-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-04-04_final.stac-item
2020-07-03 12:04:11	ga_s2am_ard_3-2-1_49KHR_2020-07-03_final.stac-item
2020-07-17 11:47:15	ga_s2am_ard_3-2-1_50HMH_2020-07-17_final.stac-item
2020-09-05 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2020-09-05_final.stac-item
2020-09-21 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2020-09-21_final.stac-item
2020-09-22 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2020-09-22_final.stac-item
2020-09-22 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-09-22_final.stac-item
2020-10-24 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-24_final.stac-item
2020-11-17 11:56:14	ga_s2am_ard_3-2-1_50JLM_2020-11-17_final.stac-item
2020-12-17 11:56:12	ga_s2am_ard_3-2-1_50JKM_2020-12-17_final.stac-item
2020-12-24 11:47:05	ga_s2am_ard_3-2-1_50HNH_2020-12-24_final.stac-item
2020-12-27 11:57:09	ga_s2am_ard_3-2-1_50HLH_2020-12-27_final.stac-item
2021-01-03 11:46:30	ga_s2am_ard_3-2-1_50HQK_2021-01-03_final.stac-item
2021-03-07 11:55:56	ga_s2am_ard_3-2-1_50JLN_2021-03-07_final.stac-item
2021-03-17 11:55:46	ga_s2am_ard_3-2-1_50JKP_2021-03-17_final.stac-item
2021-03-21 11:36:47	ga_s2am_ard_3-2-1_50HQJ_2021-03-21_final.stac-item
2021-03-27 11:56:23	ga_s2am_ard_3-2-1_50JLL_2021-03-27_final.stac-item
2021-03-27 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-03-27_final.stac-item
2021-04-26 11:56:10	ga_s2am_ard_3-2-1_50JKM_2021-04-26_final.stac-item
2021-05-20 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-05-20_final
2021-06-18 12:05:10	ga_s2am_ard_3-2-1_49JGL_2021-06-18_final.stac-item
2021-06-25 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2021-06-25_final.stac-item
2021-07-28 12:05:44	ga_s2am_ard_3-2-1_50JKP_2021-07-28_final.stac-item
2021-09-03 11:56:14	ga_s2am_ard_3-2-1_50JLM_2021-09-03_final.stac-item
2021-09-26 12:05:00	ga_s2am_ard_3-2-1_49JHM_2021-09-26_final.stac-item
2021-11-26 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2021-11-26_final.stac-item
2022-01-14 12:05:52	ga_s2am_ard_3-2-1_50JLN_2022-01-14_final.stac-item
2022-02-04 11:37:03	ga_s2am_ard_3-2-1_50HQH_2022-02-04_final.stac-item
2022-03-15 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-15_final.stac-item
2022-04-25 11:36:41	ga_s2am_ard_3-2-1_50HQK_2022-04-25_final.stac-item
2022-06-03 12:04:36	ga_s2am_ard_3-2-1_49KHP_2022-06-03_final.stac-item
2022-06-13 12:05:18	ga_s2am_ard_3-2-1_49JFM_2022-06-13_final.stac-item
2022-07-03 12:04:31	ga_s2am_ard_3-2-1_49KGQ_2022-07-03_final.stac-item
2022-07-10 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-07-10_final.stac-item
2022-09-01 12:05:53	ga_s2am_ard_3-2-1_50JKP_2022-09-01_final.stac-item
2022-09-21 12:05:45	ga_s2am_ard_3-2-1_50JLP_2022-09-21_final.stac-item
2022-11-04 11:46:41	ga_s2am_ard_3-2-1_50HNK_2022-11-04_final.stac-item
2023-02-28 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-28_final
2023-03-04 11:46:34	ga_s2am_ard_3-2-1_50HNK_2023-03-04_final
2023-06-09 11:37:10	ga_s2am_ard_3-2-1_50HPH_2023-06-09_final
2023-06-15 11:55:50	ga_s2am_ard_3-2-1_50JKP_2023-06-15_final
2023-06-21 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-06-21_final
2023-07-21 12:13:58	ga_s2am_ard_3-2-1_49KHR_2023-07-21_final
2023-07-22 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-07-22_final
2023-08-30 12:14:47	ga_s2am_ard_3-2-1_49JGN_2023-08-30_final
2023-10-13 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-10-13_final
2023-10-23 11:56:29	ga_s2am_ard_3-2-1_50JLL_2023-10-23_final
2023-12-02 11:56:43	ga_s2am_ard_3-2-1_50HMJ_2023-12-02_final
2023-12-15 12:04:42	ga_s2am_ard_3-2-1_49JGN_2023-12-15_final
2023-12-19 11:47:03	ga_s2am_ard_3-2-1_50HNH_2023-12-19_final
2024-02-27 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2024-02-27_final
2024-03-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2024-03-18_final
2024-03-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2024-03-21_final
2024-04-07 11:46:57	ga_s2am_ard_3-2-1_50HNH_2024-04-07_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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