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
2015-10-21 12:09:42	ga_s2am_ard_3-2-1_49KGP_2015-10-21_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49JGK_2016-07-14_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HQH_2016-07-15_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-10-25_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HPG_2016-11-05_final
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KGQ_2016-12-01_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HMJ_2017-01-07_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HMJ_2017-01-14_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HPH_2017-03-05_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HLK_2017-04-07_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49KHQ_2017-04-20_final.stac-item
2017-05-07 11:56:10	ga_s2am_ard_3-2-1_50HNK_2017-05-07_final.stac-item
2017-05-07 11:56:10	ga_s2am_ard_3-2-1_50JLL_2017-05-07_final.stac-item
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49JGN_2017-05-13_final.stac-item
2017-06-16 11:56:08	ga_s2am_ard_3-2-1_50JLL_2017-06-16_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49JGN_2017-07-12_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2017-09-27_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50HNK_2017-10-31_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HNK_2017-12-30_final.stac-item
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HLH_2018-02-01_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKQ_2018-03-26_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50JKM_2018-04-02_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KGP_2018-08-23_final.stac-item
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KGR_2018-09-15_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JKP_2018-10-09_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HMH_2018-10-16_final.stac-item
2018-11-15 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2018-11-15_final.stac-item
2018-11-21 12:04:54	ga_s2am_ard_3-2-1_50JKS_2018-11-21_final.stac-item
2018-12-08 11:56:03	ga_s2am_ard_3-2-1_50JLM_2018-12-08_final.stac-item
2019-01-04 11:46:49	ga_s2am_ard_3-2-1_50HPH_2019-01-04_final.stac-item
2019-01-10 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2019-01-10_final.stac-item
2019-01-31 11:36:31	ga_s2am_ard_3-2-1_50HQK_2019-01-31_final.stac-item
2019-02-03 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2019-02-03_final.stac-item
2019-02-13 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2019-02-13_final.stac-item
2019-03-04 12:14:16	ga_s2am_ard_3-2-1_49KHP_2019-03-04_final.stac-item
2019-06-03 11:47:04	ga_s2am_ard_3-2-1_50HPH_2019-06-03_final.stac-item
2019-08-15 11:57:12	ga_s2am_ard_3-2-1_50HLH_2019-08-15_final.stac-item
2019-09-07 12:05:28	ga_s2am_ard_3-2-1_49JGK_2019-09-07_final.stac-item
2019-09-10 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-09-10_final.stac-item
2019-10-01 11:46:35	ga_s2am_ard_3-2-1_50HPK_2019-10-01_final.stac-item
2019-11-06 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-11-06_final.stac-item
2019-11-30 11:47:01	ga_s2am_ard_3-2-1_50HPH_2019-11-30_final.stac-item
2019-12-13 11:56:26	ga_s2am_ard_3-2-1_50HNK_2019-12-13_final.stac-item
2019-12-17 11:36:57	ga_s2am_ard_3-2-1_50HQH_2019-12-17_final.stac-item
2019-12-27 11:36:32	ga_s2am_ard_3-2-1_50HPK_2019-12-27_final.stac-item
2020-02-07 12:14:04	ga_s2am_ard_3-2-1_49KGQ_2020-02-07_final.stac-item
2020-05-18 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2020-05-18_final.stac-item
2020-06-13 12:04:20	ga_s2am_ard_3-2-1_49KHQ_2020-06-13_final.stac-item
2020-06-23 12:06:10	ga_s2am_ard_3-2-1_50JLM_2020-06-23_final.stac-item
2020-06-30 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-06-30_final.stac-item
2020-07-10 11:56:15	ga_s2am_ard_3-2-1_50JLM_2020-07-10_final.stac-item
2020-09-05 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-09-05_final.stac-item
2020-09-15 11:46:34	ga_s2am_ard_3-2-1_50HQK_2020-09-15_final.stac-item
2020-12-20 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2020-12-20_final.stac-item
2021-03-30 12:05:12	ga_s2am_ard_3-2-1_49JGL_2021-03-30_final.stac-item
2021-05-03 11:47:22	ga_s2am_ard_3-2-1_50HMG_2021-05-03_final
2021-07-18 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-07-18_final.stac-item
2021-07-25 11:57:17	ga_s2am_ard_3-2-1_50HLH_2021-07-25_final.stac-item
2021-08-04 11:56:28	ga_s2am_ard_3-2-1_50JLL_2021-08-04_final.stac-item
2021-10-30 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2021-10-30_final.stac-item
2022-01-18 11:46:30	ga_s2am_ard_3-2-1_50HQK_2022-01-18_final.stac-item
2022-01-31 11:57:09	ga_s2am_ard_3-2-1_50HLH_2022-01-31_final.stac-item
2022-02-04 11:36:38	ga_s2am_ard_3-2-1_50HPK_2022-02-04_final.stac-item
2022-04-18 11:46:41	ga_s2am_ard_3-2-1_50HNK_2022-04-18_final.stac-item
2022-05-04 12:05:34	ga_s2am_ard_3-2-1_49JGK_2022-05-04_final.stac-item
2022-05-25 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-05-25_final.stac-item
2022-06-20 11:57:21	ga_s2am_ard_3-2-1_50HLH_2022-06-20_final.stac-item
2022-06-23 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-06-23_final.stac-item
2022-07-03 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-07-03_final.stac-item
2022-07-04 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-07-04_final.stac-item
2022-08-19 11:56:53	ga_s2am_ard_3-2-1_50HLK_2022-08-19_final.stac-item
2022-12-30 12:05:50	ga_s2am_ard_3-2-1_50JLN_2022-12-30_final.stac-item
2023-01-20 11:36:33	ga_s2am_ard_3-2-1_50HPK_2023-01-20_final.stac-item
2023-02-22 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-02-22_nrt.stac-item
2023-02-22 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2023-02-22_final
2023-02-25 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-02-25_final
2023-03-07 11:55:42	ga_s2am_ard_3-2-1_50JKP_2023-03-07_final
2023-03-10 12:04:23	ga_s2am_ard_3-2-1_49KGP_2023-03-10_final
2023-03-10 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-03-10_final
2023-04-03 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-04-03_final
2023-04-10 11:37:07	ga_s2am_ard_3-2-1_50HPH_2023-04-10_final
2023-04-23 11:46:33	ga_s2am_ard_3-2-1_50HPK_2023-04-23_final
2023-04-23 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-04-23_final
2023-05-16 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2023-05-16_final
2023-06-22 11:46:33	ga_s2am_ard_3-2-1_50HQK_2023-06-22_final
2023-08-14 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-08-14_final
2023-08-21 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2023-08-21_final
2023-09-17 11:37:06	ga_s2am_ard_3-2-1_50HQH_2023-09-17_final
2023-10-13 11:56:09	ga_s2am_ard_3-2-1_50JLM_2023-10-13_final
2023-10-17 11:37:06	ga_s2am_ard_3-2-1_50HPH_2023-10-17_final
2023-11-19 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-11-19_final
2023-11-22 11:57:02	ga_s2am_ard_3-2-1_50HMH_2023-11-22_final
2024-01-27 12:14:36	ga_s2am_ard_3-2-1_49JGN_2024-01-27_final
2024-01-28 11:46:57	ga_s2am_ard_3-2-1_50HPH_2024-01-28_final
2024-02-10 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-02-10_final
2024-02-17 11:46:28	ga_s2am_ard_3-2-1_50HQK_2024-02-17_final
2024-03-14 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2024-03-14_final
2024-03-17 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2024-03-17_final
2024-04-10 11:57:13	ga_s2am_ard_3-2-1_50HKH_2024-04-10_nrt
2024-04-27 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2024-04-27_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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