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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KHR_2015-11-30_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLN_2015-12-17_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HMH_2015-12-21_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HLH_2016-01-03_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49JHM_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JLQ_2016-03-16_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_50JLQ_2016-08-03_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_50JKQ_2016-09-22_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQK_2016-10-23_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_50JKS_2016-12-01_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMK_2016-12-05_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLK_2016-12-08_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHP_2016-12-31_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HMH_2017-02-26_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGL_2017-04-03_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLP_2017-04-07_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50JKP_2017-04-27_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50HMK_2017-05-27_final.stac-item
2017-11-23 11:56:04	ga_s2am_ard_3-2-1_50HMK_2017-11-23_final.stac-item
2017-11-23 11:56:04	ga_s2am_ard_3-2-1_50JLL_2017-11-23_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_50JKS_2017-12-26_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JKS_2018-01-25_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-02-14_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-02-17_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGL_2018-03-09_final.stac-item
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-04-08_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HQK_2018-05-19_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50HMH_2018-06-28_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQK_2018-07-15_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HMK_2018-07-31_final.stac-item
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_50JLM_2018-08-13_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHM_2018-08-23_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JLR_2018-09-09_final.stac-item
2018-11-08 11:55:23	ga_s2am_ard_3-2-1_50JLQ_2018-11-08_final.stac-item
2018-11-08 11:56:36	ga_s2am_ard_3-2-1_50HLK_2018-11-08_final.stac-item
2018-11-24 12:14:05	ga_s2am_ard_3-2-1_49KGQ_2018-11-24_final.stac-item
2018-12-18 11:56:02	ga_s2am_ard_3-2-1_50JLM_2018-12-18_final.stac-item
2018-12-21 12:04:48	ga_s2am_ard_3-2-1_49JHM_2018-12-21_final.stac-item
2019-02-06 11:56:37	ga_s2am_ard_3-2-1_50HLK_2019-02-06_final.stac-item
2019-04-07 11:56:41	ga_s2am_ard_3-2-1_50HLK_2019-04-07_final.stac-item
2019-07-02 12:14:13	ga_s2am_ard_3-2-1_49KHQ_2019-07-02_final.stac-item
2019-07-16 11:56:45	ga_s2am_ard_3-2-1_50HLK_2019-07-16_final.stac-item
2019-07-26 11:55:03	ga_s2am_ard_3-2-1_50JLS_2019-07-26_final.stac-item
2019-07-29 12:05:42	ga_s2am_ard_3-2-1_50JLP_2019-07-29_final.stac-item
2019-09-17 12:04:45	ga_s2am_ard_3-2-1_49JGN_2019-09-17_final.stac-item
2019-09-27 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2019-09-27_final.stac-item
2020-02-08 11:46:33	ga_s2am_ard_3-2-1_50HMK_2020-02-08_final.stac-item
2020-03-02 11:56:36	ga_s2am_ard_3-2-1_50HLK_2020-03-02_final.stac-item
2020-03-08 12:15:06	ga_s2am_ard_3-2-1_49JGL_2020-03-08_final.stac-item
2020-04-11 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2020-04-11_final.stac-item
2020-05-01 11:56:39	ga_s2am_ard_3-2-1_50HMK_2020-05-01_final.stac-item
2020-05-04 12:04:31	ga_s2am_ard_3-2-1_49KHP_2020-05-04_final.stac-item
2020-06-16 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-06-16_final.stac-item
2020-09-18 11:56:16	ga_s2am_ard_3-2-1_50JLM_2020-09-18_final.stac-item
2020-09-21 12:05:02	ga_s2am_ard_3-2-1_50JKS_2020-09-21_final.stac-item
2020-10-18 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-10-18_final.stac-item
2020-11-13 12:14:49	ga_s2am_ard_3-2-1_49JFN_2020-11-13_final.stac-item
2020-11-20 12:04:59	ga_s2am_ard_3-2-1_49JHM_2020-11-20_final.stac-item
2020-12-21 11:36:32	ga_s2am_ard_3-2-1_50HQK_2020-12-21_final.stac-item
2021-01-13 11:46:41	ga_s2am_ard_3-2-1_50HMK_2021-01-13_final.stac-item
2021-03-13 12:15:10	ga_s2am_ard_3-2-1_49JGL_2021-03-13_final.stac-item
2021-04-19 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2021-04-19_final.stac-item
2021-05-20 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-05-20_final
2021-06-01 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-06-01_final.stac-item
2021-08-24 11:55:15	ga_s2am_ard_3-2-1_50JLR_2021-08-24_final.stac-item
2021-10-03 11:55:02	ga_s2am_ard_3-2-1_50JLS_2021-10-03_final.stac-item
2021-10-29 12:13:45	ga_s2am_ard_3-2-1_49KHS_2021-10-29_final
2021-11-02 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2021-11-02_final.stac-item
2021-12-18 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-12-18_final.stac-item
2022-01-18 11:47:15	ga_s2am_ard_3-2-1_50HLH_2022-01-18_final.stac-item
2022-02-03 12:04:57	ga_s2am_ard_3-2-1_50JKS_2022-02-03_final.stac-item
2022-02-10 11:56:35	ga_s2am_ard_3-2-1_50HMK_2022-02-10_final.stac-item
2022-03-12 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2022-03-12_final.stac-item
2022-03-12 11:57:10	ga_s2am_ard_3-2-1_50HMH_2022-03-12_final.stac-item
2022-04-04 12:05:06	ga_s2am_ard_3-2-1_50JKS_2022-04-04_final.stac-item
2022-04-11 11:57:16	ga_s2am_ard_3-2-1_50HMH_2022-04-11_final.stac-item
2022-04-14 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-04-14_final.stac-item
2022-07-23 12:04:29	ga_s2am_ard_3-2-1_49KGQ_2022-07-23_final.stac-item
2022-08-12 12:05:09	ga_s2am_ard_3-2-1_50JKS_2022-08-12_final.stac-item
2023-01-29 12:04:26	ga_s2am_ard_3-2-1_49KHP_2023-01-29_final.stac-item
2023-02-28 12:03:42	ga_s2am_ard_3-2-1_49KHS_2023-02-28_final
2023-03-10 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2023-03-10_final
2023-04-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-29_final
2023-05-02 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-05-02_final
2023-05-22 12:15:02	ga_s2am_ard_3-2-1_49JFM_2023-05-22_final
2023-07-31 12:13:45	ga_s2am_ard_3-2-1_49KHS_2023-07-31_final
2023-08-28 11:36:43	ga_s2am_ard_3-2-1_50HPK_2023-08-28_final
2023-09-29 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2023-09-29_final
2023-10-19 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-10-19_final
2023-11-22 11:54:54	ga_s2am_ard_3-2-1_50JLS_2023-11-22_final
2024-01-18 11:46:32	ga_s2am_ard_3-2-1_50HMK_2024-01-18_final
2024-03-01 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2024-03-01_final
2024-03-04 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2024-03-04_final
2024-03-04 12:04:57	ga_s2am_ard_3-2-1_49JHM_2024-03-04_final
2024-03-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2024-03-21_final
2024-03-24 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2024-03-24_final
2024-03-31 11:56:29	ga_s2am_ard_3-2-1_50HNK_2024-03-31_final
2024-04-10 11:56:28	ga_s2am_ard_3-2-1_50HNK_2024-04-10_final
2024-04-10 11:56:29	ga_s2am_ard_3-2-1_50HMK_2024-04-10_final
2024-04-20 11:57:25	ga_s2am_ard_3-2-1_50HLG_2024-04-20_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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