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
2016-01-13 11:56:42	ga_s2am_ard_3-2-1_50HNK_2016-01-13_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HPJ_2016-02-06_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49KHS_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JKR_2016-03-16_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JLP_2016-06-24_final.stac-item
2016-07-11 11:56:11	ga_s2am_ard_3-2-1_50HLK_2016-07-11_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_50HQK_2016-08-17_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HPJ_2016-11-05_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JKP_2016-11-18_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HNK_2016-12-05_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HMH_2016-12-08_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HQJ_2017-01-01_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KGR_2017-02-02_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGL_2017-03-01_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49KHP_2017-05-30_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHQ_2017-10-07_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGR_2017-12-19_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50JKT_2018-01-05_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HMH_2018-02-28_final.stac-item
2018-04-28 12:13:23	ga_s2am_ard_3-2-1_49JGM_2018-04-28_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNJ_2018-05-09_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-04_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JKT_2018-08-13_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-09-12_final.stac-item
2018-11-21 12:04:07	ga_s2am_ard_3-2-1_49KHQ_2018-11-21_final.stac-item
2018-11-21 12:05:31	ga_s2am_ard_3-2-1_50JLP_2018-11-21_final.stac-item
2019-02-03 11:47:03	ga_s2am_ard_3-2-1_50HNH_2019-02-03_final.stac-item
2019-03-01 12:05:47	ga_s2am_ard_3-2-1_50JLN_2019-03-01_final.stac-item
2019-03-21 12:04:29	ga_s2am_ard_3-2-1_49KGP_2019-03-21_final.stac-item
2019-04-07 11:56:15	ga_s2am_ard_3-2-1_50JKM_2019-04-07_final.stac-item
2019-07-19 12:05:57	ga_s2am_ard_3-2-1_50JLN_2019-07-19_final.stac-item
2019-08-02 11:47:07	ga_s2am_ard_3-2-1_50HPH_2019-08-02_final.stac-item
2019-08-12 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2019-08-12_final.stac-item
2019-11-13 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2019-11-13_final.stac-item
2019-11-23 11:56:26	ga_s2am_ard_3-2-1_50JLL_2019-11-23_final.stac-item
2019-12-03 11:56:09	ga_s2am_ard_3-2-1_50JLM_2019-12-03_final.stac-item
2020-02-15 11:37:00	ga_s2am_ard_3-2-1_50HPH_2020-02-15_final.stac-item
2020-02-24 12:04:41	ga_s2am_ard_3-2-1_49JGN_2020-02-24_final.stac-item
2020-02-24 12:05:32	ga_s2am_ard_3-2-1_50JLP_2020-02-24_final.stac-item
2020-03-05 12:03:59	ga_s2am_ard_3-2-1_49KHQ_2020-03-05_final.stac-item
2020-03-15 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-15_final.stac-item
2020-04-07 12:14:38	ga_s2am_ard_3-2-1_49JGN_2020-04-07_final.stac-item
2020-04-15 11:36:37	ga_s2am_ard_3-2-1_50HPK_2020-04-15_final.stac-item
2020-05-14 12:05:56	ga_s2am_ard_3-2-1_50JLN_2020-05-14_final.stac-item
2020-05-28 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-05-28_final.stac-item
2020-07-20 11:56:31	ga_s2am_ard_3-2-1_50JLL_2020-07-20_final.stac-item
2020-08-05 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-08-05_final.stac-item
2020-09-11 12:06:08	ga_s2am_ard_3-2-1_50JLM_2020-09-11_final.stac-item
2020-09-18 11:56:01	ga_s2am_ard_3-2-1_50JLN_2020-09-18_final.stac-item
2020-10-18 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-10-18_final.stac-item
2020-10-24 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-10-24_final.stac-item
2020-11-03 12:14:46	ga_s2am_ard_3-2-1_49JGN_2020-11-03_final.stac-item
2020-11-20 12:04:59	ga_s2am_ard_3-2-1_50JKS_2020-11-20_final.stac-item
2020-11-20 12:05:40	ga_s2am_ard_3-2-1_50JLP_2020-11-20_final.stac-item
2020-11-24 11:47:08	ga_s2am_ard_3-2-1_50HNH_2020-11-24_final.stac-item
2021-01-19 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2021-01-19_final.stac-item
2021-01-26 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-01-26_final.stac-item
2021-02-22 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2021-02-22_final.stac-item
2021-03-13 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-03-13_final.stac-item
2021-03-21 11:37:25	ga_s2am_ard_3-2-1_50HNG_2021-03-21_final
2021-04-06 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2021-04-06_final.stac-item
2021-07-09 11:37:24	ga_s2am_ard_3-2-1_50HPG_2021-07-09_final
2021-10-30 11:46:42	ga_s2am_ard_3-2-1_50HNK_2021-10-30_final.stac-item
2021-10-30 11:47:25	ga_s2am_ard_3-2-1_50HNG_2021-10-30_final
2021-11-16 11:37:07	ga_s2am_ard_3-2-1_50HPH_2021-11-16_final.stac-item
2021-12-06 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2021-12-06_final.stac-item
2021-12-19 11:46:31	ga_s2am_ard_3-2-1_50HNK_2021-12-19_final.stac-item
2021-12-29 11:46:35	ga_s2am_ard_3-2-1_50HPK_2021-12-29_final.stac-item
2022-01-15 11:37:07	ga_s2am_ard_3-2-1_50HPH_2022-01-15_final.stac-item
2022-01-28 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2022-01-28_final.stac-item
2022-05-31 11:55:50	ga_s2am_ard_3-2-1_50JLP_2022-05-31_final.stac-item
2022-05-31 11:55:54	ga_s2am_ard_3-2-1_50JKP_2022-05-31_final.stac-item
2022-06-30 11:56:42	ga_s2am_ard_3-2-1_50HNK_2022-06-30_final.stac-item
2022-07-03 12:05:28	ga_s2am_ard_3-2-1_49JGL_2022-07-03_final.stac-item
2022-09-01 12:04:58	ga_s2am_ard_3-2-1_49JGN_2022-09-01_final.stac-item
2022-09-02 11:37:15	ga_s2am_ard_3-2-1_50HQH_2022-09-02_final.stac-item
2022-09-12 11:37:17	ga_s2am_ard_3-2-1_50HPH_2022-09-12_final.stac-item
2022-10-01 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-10-01_final.stac-item
2022-10-21 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-10-21_final.stac-item
2022-11-27 11:56:11	ga_s2am_ard_3-2-1_50JLM_2022-11-27_final.stac-item
2022-12-10 12:06:04	ga_s2am_ard_3-2-1_50JLM_2022-12-10_final.stac-item
2022-12-14 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-12-14_final.stac-item
2022-12-20 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2022-12-20_final.stac-item
2023-02-12 11:46:32	ga_s2am_ard_3-2-1_50HPK_2023-02-12_final
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_50JKT_2023-02-18_final
2023-02-18 12:05:34	ga_s2am_ard_3-2-1_50JLP_2023-02-18_nrt.stac-item
2023-02-18 12:05:34	ga_s2am_ard_3-2-1_50JLP_2023-02-18_final
2023-03-01 11:37:04	ga_s2am_ard_3-2-1_50HPH_2023-03-01_final
2023-07-05 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-05_final
2023-07-28 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2023-07-28_final
2023-08-01 11:47:08	ga_s2am_ard_3-2-1_50HPH_2023-08-01_final
2023-08-04 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2023-08-04_final
2023-11-09 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-11-09_final
2023-12-02 11:55:34	ga_s2am_ard_3-2-1_50JLP_2023-12-02_final
2024-01-08 11:47:13	ga_s2am_ard_3-2-1_50HPG_2024-01-08_final
2024-02-03 12:05:33	ga_s2am_ard_3-2-1_50JLP_2024-02-03_final
2024-02-13 12:03:42	ga_s2am_ard_3-2-1_49KHS_2024-02-13_final
2024-03-28 11:47:24	ga_s2am_ard_3-2-1_50HMG_2024-03-28_final
2024-04-03 12:03:49	ga_s2am_ard_3-2-1_49KHS_2024-04-03_final
2024-04-23 12:04:45	ga_s2am_ard_3-2-1_50JKT_2024-04-23_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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