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
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49JGN_2016-05-18_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KGP_2016-05-18_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHM_2016-07-24_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KGR_2016-09-25_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HQJ_2016-10-16_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HNH_2016-11-05_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2016-11-21_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HNK_2016-12-15_final.stac-item
2017-05-03 12:13:46	ga_s2am_ard_3-2-1_49KHQ_2017-05-03_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49KGP_2017-11-09_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49KGQ_2017-11-29_final.stac-item
2018-02-28 11:44:11	ga_s2am_ard_3-2-1_50HNK_2018-02-28_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50HMJ_2018-03-23_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-04-18_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50HQH_2018-05-06_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50HNK_2018-06-08_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_50HQH_2018-06-25_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-04_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-08_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HQJ_2018-07-25_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGN_2018-08-23_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KGP_2018-08-26_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKT_2018-09-02_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JKM_2018-09-09_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-09-12_final.stac-item
2018-09-15 12:14:38	ga_s2am_ard_3-2-1_49JGM_2018-09-15_final.stac-item
2018-11-21 12:05:19	ga_s2am_ard_3-2-1_50JKQ_2018-11-21_final.stac-item
2018-12-11 12:04:05	ga_s2am_ard_3-2-1_49KHQ_2018-12-11_final.stac-item
2019-01-07 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2019-01-07_final.stac-item
2019-02-06 11:56:22	ga_s2am_ard_3-2-1_50JLL_2019-02-06_final.stac-item
2019-02-23 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2019-02-23_final.stac-item
2019-03-14 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-03-14_final.stac-item
2019-03-31 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-03-31_final.stac-item
2019-03-31 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-03-31_final.stac-item
2019-06-06 11:55:44	ga_s2am_ard_3-2-1_50JKP_2019-06-06_final.stac-item
2019-06-19 12:04:50	ga_s2am_ard_3-2-1_49JGN_2019-06-19_final.stac-item
2019-07-22 12:14:46	ga_s2am_ard_3-2-1_49JGN_2019-07-22_final.stac-item
2019-08-08 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-08-08_final.stac-item
2019-08-22 11:47:04	ga_s2am_ard_3-2-1_50HPH_2019-08-22_final.stac-item
2019-08-28 12:04:00	ga_s2am_ard_3-2-1_49KHR_2019-08-28_final.stac-item
2019-11-10 11:46:36	ga_s2am_ard_3-2-1_50HPK_2019-11-10_final.stac-item
2019-11-10 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-11-10_final.stac-item
2019-12-23 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2019-12-23_final.stac-item
2020-03-08 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2020-03-08_final.stac-item
2020-03-19 11:46:37	ga_s2am_ard_3-2-1_50HMK_2020-03-19_final.stac-item
2020-04-04 12:05:22	ga_s2am_ard_3-2-1_50JKQ_2020-04-04_final.stac-item
2020-04-11 11:56:38	ga_s2am_ard_3-2-1_50HLK_2020-04-11_final.stac-item
2020-05-27 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-05-27_final.stac-item
2020-06-16 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-06-16_final.stac-item
2020-09-08 11:55:50	ga_s2am_ard_3-2-1_50JKP_2020-09-08_final.stac-item
2020-10-04 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-10-04_final.stac-item
2020-10-31 12:05:02	ga_s2am_ard_3-2-1_50JKS_2020-10-31_final.stac-item
2020-11-07 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2020-11-07_final.stac-item
2020-12-07 11:55:44	ga_s2am_ard_3-2-1_50JKP_2020-12-07_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2020-12-20 12:04:30	ga_s2am_ard_3-2-1_49KGP_2020-12-20_final.stac-item
2020-12-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-12-30_final.stac-item
2021-02-08 12:04:56	ga_s2am_ard_3-2-1_50JKS_2021-02-08_final.stac-item
2021-03-07 11:56:25	ga_s2am_ard_3-2-1_50JLL_2021-03-07_final.stac-item
2021-03-20 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-03-20_final
2021-03-20 12:05:43	ga_s2am_ard_3-2-1_50JKP_2021-03-20_final.stac-item
2021-04-23 11:46:36	ga_s2am_ard_3-2-1_50HMK_2021-04-23_final.stac-item
2021-08-07 12:06:07	ga_s2am_ard_3-2-1_50JLM_2021-08-07_final.stac-item
2021-08-11 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2021-08-11_final.stac-item
2021-10-09 12:14:00	ga_s2am_ard_3-2-1_49KHR_2021-10-09_final.stac-item
2021-10-17 11:37:12	ga_s2am_ard_3-2-1_50HPH_2021-10-17_final.stac-item
2021-12-09 11:46:32	ga_s2am_ard_3-2-1_50HMK_2021-12-09_final.stac-item
2022-01-04 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-01-04_final.stac-item
2022-01-14 12:04:47	ga_s2am_ard_3-2-1_49JGN_2022-01-14_final.stac-item
2022-02-03 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-02-03_final.stac-item
2022-02-03 12:04:42	ga_s2am_ard_3-2-1_50JKT_2022-02-03_final.stac-item
2022-02-13 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-02-13_final.stac-item
2022-02-20 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-02-20_final.stac-item
2022-04-25 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2022-04-25_final.stac-item
2022-05-08 11:46:42	ga_s2am_ard_3-2-1_50HNK_2022-05-08_final.stac-item
2022-06-06 12:14:35	ga_s2am_ard_3-2-1_49KGP_2022-06-06_final.stac-item
2022-09-14 12:14:51	ga_s2am_ard_3-2-1_49JGN_2022-09-14_final.stac-item
2022-10-01 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-10-01_final.stac-item
2022-12-20 12:03:58	ga_s2am_ard_3-2-1_49KHR_2022-12-20_final.stac-item
2023-01-19 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2023-01-19_final.stac-item
2023-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-02-05_final
2023-02-15 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-02-15_nrt.stac-item
2023-02-15 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-02-15_final
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_final
2023-02-21 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-02-21_nrt.stac-item
2023-02-21 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-02-21_final
2023-03-13 12:15:07	ga_s2am_ard_3-2-1_49JGL_2023-03-13_final
2023-04-29 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-04-29_final
2023-05-12 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-05-12_final
2023-05-16 11:57:10	ga_s2am_ard_3-2-1_50HLH_2023-05-16_final
2023-07-02 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2023-07-02_final
2023-10-06 12:05:56	ga_s2am_ard_3-2-1_50JKN_2023-10-06_final
2023-10-29 12:14:41	ga_s2am_ard_3-2-1_49JGN_2023-10-29_final
2023-11-12 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-11-12_final
2023-11-26 11:36:28	ga_s2am_ard_3-2-1_50HQK_2023-11-26_final
2024-02-20 11:56:28	ga_s2am_ard_3-2-1_50HNK_2024-02-20_final
2024-02-23 12:05:13	ga_s2am_ard_3-2-1_49JGL_2024-02-23_final
2024-03-01 11:55:46	ga_s2am_ard_3-2-1_50JKP_2024-03-01_final
2024-03-25 11:37:22	ga_s2am_ard_3-2-1_50HPG_2024-03-25_final
2024-05-03 12:04:49	ga_s2am_ard_3-2-1_49JGN_2024-05-03_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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