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
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50JML_2015-10-22_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_50JKR_2016-01-06_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JHN_2016-02-15_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HMG_2016-02-19_final
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HPH_2016-03-20_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMH_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMJ_2016-05-09_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50JKP_2016-08-23_final.stac-item
2016-09-29 11:56:03	ga_s2am_ard_3-2-1_50JML_2016-09-29_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHS_2016-10-22_final
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JLP_2016-12-08_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HMH_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HNJ_2016-12-15_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_49JHN_2017-01-30_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JLP_2017-02-19_final.stac-item
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGL_2017-03-01_final.stac-item
2017-03-05 11:44:15	ga_s2am_ard_3-2-1_50HNH_2017-03-05_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JLP_2017-11-06_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMH_2017-12-03_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGR_2017-12-19_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HPH_2017-12-30_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HNK_2018-01-12_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-02-14_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-02-24_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50JLP_2018-03-06_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGL_2018-03-09_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGL_2018-06-14_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JML_2018-07-01_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JGL_2018-09-25_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLJ_2018-10-09_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HLH_2018-10-26_final.stac-item
2018-12-01 12:05:29	ga_s2am_ard_3-2-1_50JLP_2018-12-01_final.stac-item
2018-12-18 11:56:13	ga_s2am_ard_3-2-1_50JML_2018-12-18_final.stac-item
2018-12-18 11:56:31	ga_s2am_ard_3-2-1_50HLK_2018-12-18_final.stac-item
2019-01-14 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2019-01-14_final.stac-item
2019-03-08 11:54:39	ga_s2am_ard_3-2-1_50JLT_2019-03-08_final.stac-item
2019-04-10 12:05:53	ga_s2am_ard_3-2-1_50JLN_2019-04-10_final.stac-item
2019-05-21 11:36:37	ga_s2am_ard_3-2-1_50HQK_2019-05-21_final.stac-item
2019-05-30 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-05-30_final.stac-item
2019-07-09 12:04:59	ga_s2am_ard_3-2-1_50JLS_2019-07-09_final.stac-item
2019-08-02 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2019-08-02_final.stac-item
2019-08-18 12:04:45	ga_s2am_ard_3-2-1_50JKT_2019-08-18_final.stac-item
2019-09-14 11:56:10	ga_s2am_ard_3-2-1_50JLM_2019-09-14_final.stac-item
2019-09-17 12:05:40	ga_s2am_ard_3-2-1_50JKP_2019-09-17_final.stac-item
2019-09-28 11:36:53	ga_s2am_ard_3-2-1_50HPJ_2019-09-28_final.stac-item
2019-11-16 12:05:53	ga_s2am_ard_3-2-1_50JLN_2019-11-16_final.stac-item
2019-11-30 11:46:29	ga_s2am_ard_3-2-1_50HQK_2019-11-30_final.stac-item
2019-12-13 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-12-13_final.stac-item
2019-12-17 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2019-12-17_final.stac-item
2020-02-18 11:47:00	ga_s2am_ard_3-2-1_50HNH_2020-02-18_final.stac-item
2020-03-26 11:37:03	ga_s2am_ard_3-2-1_50HPH_2020-03-26_final.stac-item
2020-04-21 11:55:47	ga_s2am_ard_3-2-1_50JKP_2020-04-21_final.stac-item
2020-05-14 12:05:56	ga_s2am_ard_3-2-1_50JLN_2020-05-14_final.stac-item
2020-06-27 11:46:35	ga_s2am_ard_3-2-1_50HQK_2020-06-27_final.stac-item
2020-08-02 12:05:47	ga_s2am_ard_3-2-1_50JKP_2020-08-02_final.stac-item
2020-10-14 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-10-14_final.stac-item
2020-10-24 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-10-24_final.stac-item
2020-10-28 11:56:42	ga_s2am_ard_3-2-1_50HMK_2020-10-28_final.stac-item
2020-10-31 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-10-31_final.stac-item
2020-12-10 12:04:15	ga_s2am_ard_3-2-1_49KGQ_2020-12-10_final.stac-item
2020-12-23 12:14:20	ga_s2am_ard_3-2-1_49KHP_2020-12-23_final.stac-item
2020-12-24 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2020-12-24_final.stac-item
2021-02-12 11:46:25	ga_s2am_ard_3-2-1_50JML_2021-02-12_final.stac-item
2021-02-12 11:47:05	ga_s2am_ard_3-2-1_50HNH_2021-02-12_final.stac-item
2021-02-28 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-02-28_final.stac-item
2021-03-10 12:04:39	ga_s2am_ard_3-2-1_50JLT_2021-03-10_final.stac-item
2021-03-20 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-03-20_final.stac-item
2021-05-23 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-05-23_final.stac-item
2021-06-25 11:56:15	ga_s2am_ard_3-2-1_50JKM_2021-06-25_final.stac-item
2021-07-08 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2021-07-08_final.stac-item
2021-08-11 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2021-08-11_final.stac-item
2021-08-17 12:04:59	ga_s2am_ard_3-2-1_50JKS_2021-08-17_final.stac-item
2021-09-06 12:05:38	ga_s2am_ard_3-2-1_50JLP_2021-09-06_final.stac-item
2021-09-19 12:14:00	ga_s2am_ard_3-2-1_49KGR_2021-09-19_final.stac-item
2021-09-26 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-09-26_final.stac-item
2021-10-03 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2021-10-03_final.stac-item
2021-10-07 11:37:08	ga_s2am_ard_3-2-1_50HQH_2021-10-07_final.stac-item
2021-11-02 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2021-11-02_final.stac-item
2022-01-11 11:56:23	ga_s2am_ard_3-2-1_50JML_2022-01-11_final.stac-item
2022-02-20 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-02-20_final.stac-item
2022-02-23 12:04:24	ga_s2am_ard_3-2-1_49KHP_2022-02-23_final.stac-item
2022-03-09 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2022-03-09_final.stac-item
2022-09-24 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-09-24_final.stac-item
2022-10-11 12:04:19	ga_s2am_ard_3-2-1_49KHQ_2022-10-11_final.stac-item
2022-12-23 12:13:56	ga_s2am_ard_3-2-1_49KGR_2022-12-23_final.stac-item
2023-01-13 11:46:10	ga_s2am_ard_3-2-1_50JMM_2023-01-13_final.stac-item
2023-02-28 12:04:30	ga_s2am_ard_3-2-1_50JLT_2023-02-28_final
2023-03-10 12:05:32	ga_s2am_ard_3-2-1_50JLP_2023-03-10_final
2023-04-06 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-04-06_final
2023-04-19 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-04-19_final
2023-05-29 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-05-29_final
2023-05-29 12:05:15	ga_s2am_ard_3-2-1_50JKR_2023-05-29_final
2023-07-12 11:46:35	ga_s2am_ard_3-2-1_50HQK_2023-07-12_final
2023-08-04 11:55:51	ga_s2am_ard_3-2-1_50JKP_2023-08-04_final
2023-09-17 11:37:21	ga_s2am_ard_3-2-1_50HQG_2023-09-17_final
2023-12-05 12:04:36	ga_s2am_ard_3-2-1_50JKT_2023-12-05_final
2023-12-09 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2023-12-09_final
2024-01-08 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2024-01-08_final
2024-03-24 12:05:30	ga_s2am_ard_3-2-1_49JGK_2024-03-24_final
2024-04-07 11:46:32	ga_s2am_ard_3-2-1_50HPK_2024-04-07_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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