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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPJ_2015-12-21_final.stac-item
2016-02-05 12:04:38	ga_s2am_ard_3-2-1_49JGK_2016-02-05_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50HMK_2016-03-03_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HPK_2016-05-16_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50HMK_2016-08-30_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50HLK_2016-09-19_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQJ_2016-10-23_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49JGL_2016-11-04_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HMJ_2017-01-24_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50HLK_2017-04-07_final.stac-item
2017-04-27 11:56:35	ga_s2am_ard_3-2-1_50HLJ_2017-04-27_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JGK_2017-05-10_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGR_2017-07-12_final.stac-item
2017-08-31 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-08-31_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGL_2017-09-17_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50HLK_2017-10-24_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HLJ_2017-12-23_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HNH_2017-12-30_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HMJ_2018-02-18_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNH_2018-02-18_final.stac-item
2018-03-07 11:36:09	ga_s2am_ard_3-2-1_50HPJ_2018-03-07_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HNH_2018-03-30_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HPH_2018-05-29_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49KHQ_2018-06-14_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HLH_2018-06-28_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2018-07-14_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-07-17_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2018-08-16_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMK_2018-09-19_final.stac-item
2018-11-08 11:57:01	ga_s2am_ard_3-2-1_50HMH_2018-11-08_final.stac-item
2018-11-21 12:06:03	ga_s2am_ard_3-2-1_50JKM_2018-11-21_final.stac-item
2018-12-24 12:15:03	ga_s2am_ard_3-2-1_49JGL_2018-12-24_final.stac-item
2019-01-01 11:37:00	ga_s2am_ard_3-2-1_50HPH_2019-01-01_final.stac-item
2019-01-27 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-01-27_final.stac-item
2019-02-03 11:46:49	ga_s2am_ard_3-2-1_50HNJ_2019-02-03_final.stac-item
2019-02-03 11:47:07	ga_s2am_ard_3-2-1_50HMH_2019-02-03_final.stac-item
2019-02-06 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-02-06_final.stac-item
2019-05-03 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-05-03_final.stac-item
2019-05-17 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-05-17_final.stac-item
2019-05-27 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-05-27_final.stac-item
2019-09-04 11:57:06	ga_s2am_ard_3-2-1_50HMH_2019-09-04_final.stac-item
2019-11-13 11:56:39	ga_s2am_ard_3-2-1_50HMK_2019-11-13_final.stac-item
2019-11-26 12:04:46	ga_s2am_ard_3-2-1_49JGN_2019-11-26_final.stac-item
2019-11-30 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2019-11-30_final.stac-item
2019-12-27 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-12-27_final.stac-item
2020-01-19 11:47:04	ga_s2am_ard_3-2-1_50HMH_2020-01-19_final.stac-item
2020-02-07 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2020-02-07_final.stac-item
2020-02-08 11:47:02	ga_s2am_ard_3-2-1_50HMH_2020-02-08_final.stac-item
2020-03-12 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-03-12_final.stac-item
2020-05-11 11:57:10	ga_s2am_ard_3-2-1_50HMH_2020-05-11_final.stac-item
2020-05-17 12:14:26	ga_s2am_ard_3-2-1_49KHP_2020-05-17_final.stac-item
2020-07-30 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-07-30_final.stac-item
2020-08-25 12:15:05	ga_s2am_ard_3-2-1_49JFM_2020-08-25_final.stac-item
2020-10-14 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-10-14_final.stac-item
2020-10-31 12:04:51	ga_s2am_ard_3-2-1_49JGN_2020-10-31_final.stac-item
2020-11-03 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-11-03_final.stac-item
2020-11-03 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-11-03_final.stac-item
2020-12-20 12:04:44	ga_s2am_ard_3-2-1_49JGN_2020-12-20_final.stac-item
2020-12-27 11:56:40	ga_s2am_ard_3-2-1_50HLK_2020-12-27_final.stac-item
2021-01-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-01-29_final
2021-03-30 12:03:42	ga_s2am_ard_3-2-1_49KHS_2021-03-30_final
2021-07-28 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2021-07-28_final.stac-item
2021-08-20 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-08-20_final.stac-item
2021-09-13 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-13_final.stac-item
2021-09-17 11:37:23	ga_s2am_ard_3-2-1_50HPG_2021-09-17_final
2021-12-09 11:46:40	ga_s2am_ard_3-2-1_50HMK_2021-12-09_final.stac-item
2021-12-09 11:47:19	ga_s2am_ard_3-2-1_50HNG_2021-12-09_final
2021-12-19 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-12-19_final.stac-item
2021-12-29 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-12-29_final
2022-03-09 11:47:14	ga_s2am_ard_3-2-1_50HMH_2022-03-09_final.stac-item
2022-05-07 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2022-05-07_final.stac-item
2022-09-28 11:57:13	ga_s2am_ard_3-2-1_50HMH_2022-09-28_final.stac-item
2023-01-13 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2023-01-13_final.stac-item
2023-01-20 11:36:47	ga_s2am_ard_3-2-1_50HPJ_2023-01-20_final.stac-item
2023-02-02 11:47:10	ga_s2am_ard_3-2-1_50HLH_2023-02-02_final
2023-02-08 12:05:11	ga_s2am_ard_3-2-1_50JKR_2023-02-08_final
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_49KHP_2023-02-18_nrt.stac-item
2023-03-04 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-03-04_final
2023-03-07 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-03-07_final
2023-03-10 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-03-10_final
2023-04-06 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-04-06_final
2023-04-16 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-04-16_final
2023-04-20 11:36:36	ga_s2am_ard_3-2-1_50HPK_2023-04-20_final
2023-05-03 11:47:14	ga_s2am_ard_3-2-1_50HLH_2023-05-03_final
2023-06-28 12:04:54	ga_s2am_ard_3-2-1_49JGN_2023-06-28_final
2023-07-02 11:47:19	ga_s2am_ard_3-2-1_50HLH_2023-07-02_final
2023-07-08 12:05:02	ga_s2am_ard_3-2-1_49JHM_2023-07-08_final
2023-07-15 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-15_final
2023-07-18 12:03:49	ga_s2am_ard_3-2-1_49KHS_2023-07-18_final
2023-08-21 11:47:27	ga_s2am_ard_3-2-1_50HNG_2023-08-21_final
2023-09-16 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-09-16_final
2023-10-13 11:56:28	ga_s2am_ard_3-2-1_50HNK_2023-10-13_final
2023-10-16 12:04:27	ga_s2am_ard_3-2-1_49KHP_2023-10-16_final
2023-10-20 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2023-10-20_final
2023-11-02 11:57:04	ga_s2am_ard_3-2-1_50HMH_2023-11-02_final
2024-01-15 11:36:27	ga_s2am_ard_3-2-1_50HQK_2024-01-15_final
2024-02-10 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2024-02-10_final
2024-03-21 11:57:21	ga_s2am_ard_3-2-1_50HMG_2024-03-21_final
2024-04-14 11:37:28	ga_s2am_ard_3-2-1_50HNG_2024-04-14_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

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