Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49KHQ_2015-10-28_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGP_2015-11-30_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JKT_2015-12-17_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLM_2016-01-16_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JLQ_2016-08-13_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KGR_2016-11-14_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLK_2016-11-28_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JKT_2016-12-11_final
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KGR_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HQK_2016-12-15_final
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHP_2016-12-21_final
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2017-03-31_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JHM_2017-06-29_final
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JHN_2017-06-29_final
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JHN_2018-01-08_final
2019-01-20 12:05:19	ga_s2am_ard_3-2-1_50JLQ_2019-01-20_final
2019-01-30 12:04:25	ga_s2am_ard_3-2-1_49KHP_2019-01-30_final
2019-02-06 11:55:09	ga_s2am_ard_3-2-1_50JLR_2019-02-06_final
2019-02-19 12:04:53	ga_s2am_ard_3-2-1_49JHM_2019-02-19_final
2019-03-11 12:05:03	ga_s2am_ard_3-2-1_50JLR_2019-03-11_final
2019-03-21 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2019-03-21_final
2019-05-03 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-05-03_final
2019-05-13 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-05-13_final
2019-05-14 11:46:57	ga_s2am_ard_3-2-1_50HQH_2019-05-14_final
2019-05-14 11:47:31	ga_s2am_ard_3-2-1_50HLG_2019-05-14_final.stac-item
2019-06-02 12:14:24	ga_s2am_ard_3-2-1_49KHP_2019-06-02_final
2019-07-13 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-13_final
2019-09-30 12:14:22	ga_s2am_ard_3-2-1_49KHP_2019-09-30_final
2019-11-03 11:56:08	ga_s2am_ard_3-2-1_50JLN_2019-11-03_final
2019-11-26 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2019-11-26_final
2019-12-16 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2019-12-16_final
2019-12-16 12:04:37	ga_s2am_ard_3-2-1_50JKT_2019-12-16_final
2020-01-22 11:55:06	ga_s2am_ard_3-2-1_50JLR_2020-01-22_final
2020-01-25 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2020-01-25_final
2020-02-01 11:55:20	ga_s2am_ard_3-2-1_50JLQ_2020-02-01_final
2020-02-27 12:14:16	ga_s2am_ard_3-2-1_49KHP_2020-02-27_final
2020-06-20 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-06-20_final
2020-08-22 12:05:14	ga_s2am_ard_3-2-1_50JLR_2020-08-22_final
2020-09-14 12:14:25	ga_s2am_ard_3-2-1_49KHP_2020-09-14_final
2020-10-01 12:04:33	ga_s2am_ard_3-2-1_49KHP_2020-10-01_final
2020-10-04 12:14:27	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final
2020-12-10 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-12-10_final
2021-01-29 12:05:08	ga_s2am_ard_3-2-1_50JLR_2021-01-29_final
2021-08-24 11:55:15	ga_s2am_ard_3-2-1_50JLR_2021-08-24_final
2021-08-24 11:56:13	ga_s2am_ard_3-2-1_50JLM_2021-08-24_final
2021-09-23 11:56:14	ga_s2am_ard_3-2-1_50JLM_2021-09-23_final
2021-10-13 11:55:18	ga_s2am_ard_3-2-1_50JLR_2021-10-13_final
2021-11-29 11:46:53	ga_s2am_ard_3-2-1_50HQH_2021-11-29_final
2022-01-01 11:56:42	ga_s2am_ard_3-2-1_50HLK_2022-01-01_final
2022-01-01 11:57:25	ga_s2am_ard_3-2-1_50HLG_2022-01-01_final.stac-item
2022-01-05 11:36:35	ga_s2am_ard_3-2-1_50HQK_2022-01-05_final
2022-01-08 11:47:29	ga_s2am_ard_3-2-1_50HLG_2022-01-08_final.stac-item
2022-01-15 11:36:35	ga_s2am_ard_3-2-1_50HQK_2022-01-15_final
2022-02-03 12:05:08	ga_s2am_ard_3-2-1_50JLR_2022-02-03_final
2022-02-20 11:55:14	ga_s2am_ard_3-2-1_50JLR_2022-02-20_final
2022-03-05 12:05:01	ga_s2am_ard_3-2-1_50JKS_2022-03-05_final
2022-03-05 12:05:08	ga_s2am_ard_3-2-1_50JKS_2022-03-05_final
2022-03-09 11:46:34	ga_s2am_ard_3-2-1_50HQK_2022-03-09_final
2022-03-09 11:47:32	ga_s2am_ard_3-2-1_50HLG_2022-03-09_final.stac-item
2022-04-11 11:55:14	ga_s2am_ard_3-2-1_50JLR_2022-04-11_final
2022-04-14 12:04:59	ga_s2am_ard_3-2-1_49JHM_2022-04-14_final
2022-04-14 12:05:15	ga_s2am_ard_3-2-1_50JKR_2022-04-14_final.stac-item
2022-05-04 12:05:10	ga_s2am_ard_3-2-1_49JGL_2022-05-04_final
2022-05-07 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-05-07_final
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final
2022-06-06 12:14:16	ga_s2am_ard_3-2-1_49KHQ_2022-06-06_final
2022-06-06 12:14:29	ga_s2am_ard_3-2-1_49KHP_2022-06-06_final
2022-06-20 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-06-20_final
2022-06-26 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-06-26_final
2022-07-03 12:05:21	ga_s2am_ard_3-2-1_50JLR_2022-07-03_final
2022-08-15 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-15_final
2022-08-15 12:14:33	ga_s2am_ard_3-2-1_49KHP_2022-08-15_final
2022-09-28 11:55:35	ga_s2am_ard_3-2-1_50JLQ_2022-09-28_final.stac-item
2022-11-10 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2022-11-10_final.stac-item
2022-11-13 12:14:24	ga_s2am_ard_3-2-1_49KHP_2022-11-13_final.stac-item
2022-12-13 12:14:07	ga_s2am_ard_3-2-1_49KHQ_2022-12-13_final.stac-item
2023-01-12 12:14:19	ga_s2am_ard_3-2-1_49KHP_2023-01-12_final.stac-item
2023-02-21 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-02-21_final.stac-item
2023-03-03 12:14:18	ga_s2am_ard_3-2-1_49KHP_2023-03-03_final.stac-item
2023-04-12 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-04-12_final.stac-item
2023-05-16 11:57:10	ga_s2am_ard_3-2-1_50HLH_2023-05-16_final.stac-item
2023-07-01 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-07-01_final.stac-item
2023-08-24 11:56:42	ga_s2am_ard_3-2-1_50HMK_2023-08-24_final.stac-item
2023-08-28 11:36:40	ga_s2am_ard_3-2-1_50HQK_2023-08-28_final.stac-item
2023-09-06 12:05:14	ga_s2am_ard_3-2-1_49JFM_2023-09-06_final.stac-item
2023-10-29 12:14:21	ga_s2am_ard_3-2-1_49KHP_2023-10-29_final.stac-item
2023-11-22 11:55:09	ga_s2am_ard_3-2-1_50JLR_2023-11-22_final.stac-item
2023-12-02 11:56:32	ga_s2am_ard_3-2-1_50HLK_2023-12-02_final.stac-item
2023-12-06 11:36:27	ga_s2am_ard_3-2-1_50HQK_2023-12-06_final.stac-item
2023-12-12 11:57:17	ga_s2am_ard_3-2-1_50HLG_2023-12-12_final.stac-item
2023-12-18 12:14:17	ga_s2am_ard_3-2-1_49KHP_2023-12-18_final.stac-item
2024-01-04 12:05:19	ga_s2am_ard_3-2-1_50JLQ_2024-01-04_final.stac-item
2024-01-07 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2024-01-07_final.stac-item
2024-01-17 12:14:01	ga_s2am_ard_3-2-1_49KHQ_2024-01-17_final.stac-item
2024-01-25 11:36:28	ga_s2am_ard_3-2-1_50HQK_2024-01-25_final.stac-item
2024-01-25 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2024-01-25_final.stac-item
2024-03-07 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-07_final.stac-item
2024-03-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2024-03-21_final.stac-item
2024-03-31 11:55:26	ga_s2am_ard_3-2-1_50JLQ_2024-03-31_final.stac-item
2024-04-07 11:46:52	ga_s2am_ard_3-2-1_50HQH_2024-04-07_final.stac-item

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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