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_50JLN_2015-11-14_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JLP_2016-10-29_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JKP_2017-02-16_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HLH_2017-02-26_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HQK_2017-03-05_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50JLM_2017-03-08_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JML_2017-06-13_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HLJ_2017-12-03_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_50HNK_2017-12-30_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNK_2018-02-18_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HLK_2018-04-02_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-04-08_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JML_2018-04-29_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49JGN_2018-05-08_final.stac-item
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGM_2018-06-17_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HPH_2018-07-08_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HLJ_2018-07-11_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JLR_2018-07-14_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KGP_2018-07-17_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KGP_2018-07-27_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50JML_2018-08-27_final.stac-item
2018-11-21 12:04:21	ga_s2am_ard_3-2-1_49KHP_2018-11-21_final.stac-item
2018-12-22 11:36:56	ga_s2am_ard_3-2-1_50HPH_2018-12-22_final.stac-item
2019-01-14 11:46:22	ga_s2am_ard_3-2-1_50JML_2019-01-14_final.stac-item
2019-02-20 11:36:34	ga_s2am_ard_3-2-1_50HPK_2019-02-20_final.stac-item
2019-02-23 11:46:22	ga_s2am_ard_3-2-1_50JML_2019-02-23_final.stac-item
2019-03-25 11:46:36	ga_s2am_ard_3-2-1_50HNK_2019-03-25_final.stac-item
2019-04-17 11:56:28	ga_s2am_ard_3-2-1_50JLL_2019-04-17_final.stac-item
2019-05-20 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2019-05-20_final.stac-item
2019-06-02 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-06-02_final.stac-item
2019-06-02 12:14:44	ga_s2am_ard_3-2-1_49JGN_2019-06-02_final.stac-item
2019-07-26 11:56:16	ga_s2am_ard_3-2-1_50JLM_2019-07-26_final.stac-item
2019-08-21 12:14:01	ga_s2am_ard_3-2-1_49KGR_2019-08-21_final.stac-item
2019-09-17 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-09-17_final.stac-item
2019-09-20 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-09-20_final.stac-item
2019-10-20 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-10-20_final.stac-item
2019-10-21 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-10-21_final.stac-item
2019-12-06 12:04:37	ga_s2am_ard_3-2-1_50JLT_2019-12-06_final.stac-item
2019-12-23 11:55:50	ga_s2am_ard_3-2-1_50JLN_2019-12-23_final.stac-item
2019-12-30 11:46:43	ga_s2am_ard_3-2-1_50HPJ_2019-12-30_final.stac-item
2019-12-30 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2019-12-30_final.stac-item
2020-01-19 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2020-01-19_final.stac-item
2020-03-18 12:13:54	ga_s2am_ard_3-2-1_49KGR_2020-03-18_final.stac-item
2020-04-01 11:56:21	ga_s2am_ard_3-2-1_50JLL_2020-04-01_final.stac-item
2020-04-04 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-04-04_final.stac-item
2020-04-07 12:14:53	ga_s2am_ard_3-2-1_49JGM_2020-04-07_final.stac-item
2020-04-24 12:04:44	ga_s2am_ard_3-2-1_49JHN_2020-04-24_final.stac-item
2020-06-30 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-06-30_final.stac-item
2020-08-19 11:54:50	ga_s2am_ard_3-2-1_50JLT_2020-08-19_final.stac-item
2020-08-22 12:05:17	ga_s2am_ard_3-2-1_50JKR_2020-08-22_final.stac-item
2020-08-29 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-08-29_final.stac-item
2020-10-28 11:55:51	ga_s2am_ard_3-2-1_50JKP_2020-10-28_final.stac-item
2020-12-20 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2020-12-20_final.stac-item
2021-01-22 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-01-22_final.stac-item
2021-02-12 11:47:01	ga_s2am_ard_3-2-1_50HPH_2021-02-12_final.stac-item
2021-04-29 12:05:35	ga_s2am_ard_3-2-1_50JLP_2021-04-29_final.stac-item
2021-08-17 12:05:13	ga_s2am_ard_3-2-1_49JGL_2021-08-17_final.stac-item
2021-10-23 11:57:28	ga_s2am_ard_3-2-1_50HLG_2021-10-23_final
2021-10-30 11:47:21	ga_s2am_ard_3-2-1_50HPG_2021-10-30_final
2021-11-25 12:04:57	ga_s2am_ard_3-2-1_49JHM_2021-11-25_final.stac-item
2022-01-28 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2022-01-28_final.stac-item
2022-02-20 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-02-20_final.stac-item
2022-02-23 12:05:17	ga_s2am_ard_3-2-1_49JGL_2022-02-23_final.stac-item
2022-03-12 11:56:15	ga_s2am_ard_3-2-1_50JLM_2022-03-12_final.stac-item
2022-05-04 12:05:17	ga_s2am_ard_3-2-1_50JKR_2022-05-04_final.stac-item
2022-05-05 11:36:43	ga_s2am_ard_3-2-1_50HPK_2022-05-05_final.stac-item
2022-06-13 12:05:48	ga_s2am_ard_3-2-1_50JLP_2022-06-13_final.stac-item
2022-07-23 12:04:24	ga_s2am_ard_3-2-1_49KHQ_2022-07-23_final.stac-item
2022-08-22 12:04:31	ga_s2am_ard_3-2-1_49KGQ_2022-08-22_final.stac-item
2022-08-29 11:57:07	ga_s2am_ard_3-2-1_50HLJ_2022-08-29_final.stac-item
2022-09-12 11:37:13	ga_s2am_ard_3-2-1_50HQH_2022-09-12_final.stac-item
2022-10-08 11:57:16	ga_s2am_ard_3-2-1_50HLH_2022-10-08_final.stac-item
2022-12-21 11:37:05	ga_s2am_ard_3-2-1_50HPH_2022-12-21_final.stac-item
2022-12-24 11:47:04	ga_s2am_ard_3-2-1_50HNH_2022-12-24_final.stac-item
2023-02-12 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2023-02-12_final
2023-02-18 12:05:34	ga_s2am_ard_3-2-1_50JLP_2023-02-18_final
2023-02-18 12:05:48	ga_s2am_ard_3-2-1_50JLN_2023-02-18_final
2023-03-04 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-03-04_final
2023-04-03 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-04-03_final
2023-04-06 11:56:36	ga_s2am_ard_3-2-1_50HMK_2023-04-06_final
2023-04-13 11:47:21	ga_s2am_ard_3-2-1_50HNG_2023-04-13_final
2023-04-22 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-04-22_final
2023-05-19 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2023-05-19_final
2023-07-21 12:14:45	ga_s2am_ard_3-2-1_49JGN_2023-07-21_final
2023-08-11 11:47:14	ga_s2am_ard_3-2-1_50HMH_2023-08-11_final
2023-08-21 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2023-08-21_final
2023-08-27 12:05:57	ga_s2am_ard_3-2-1_50JLN_2023-08-27_final
2023-10-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-29_final
2023-12-22 11:56:18	ga_s2am_ard_3-2-1_50JML_2023-12-22_final
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_50JKT_2023-12-25_final
2024-01-01 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2024-01-01_final
2024-02-07 11:46:25	ga_s2am_ard_3-2-1_50HQK_2024-02-07_final
2024-02-07 11:46:34	ga_s2am_ard_3-2-1_50HPK_2024-02-07_final
2024-02-17 11:47:08	ga_s2am_ard_3-2-1_50HMH_2024-02-17_final
2024-03-04 12:04:46	ga_s2am_ard_3-2-1_49JGN_2024-03-04_final
2024-04-20 11:56:14	ga_s2am_ard_3-2-1_50JLM_2024-04-20_final
2024-05-03 12:04:49	ga_s2am_ard_3-2-1_49JGN_2024-05-03_final
2024-05-06 12:14:59	ga_s2am_ard_3-2-1_49JGM_2024-05-06_final
2024-05-13 12:05:15	ga_s2am_ard_3-2-1_50JKR_2024-05-13_nrt

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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