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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50JKN_2015-11-14_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50HMK_2015-12-04_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HNH_2015-12-21_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49JFM_2016-02-08_final.stac-item
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHQ_2016-03-06_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JQP_2016-03-20_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HNJ_2016-05-09_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLN_2016-05-22_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HPK_2016-10-16_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50JKR_2017-02-09_final
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50JQP_2017-02-13_final
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49JGK_2017-03-11_final
2017-05-20 12:03:50	ga_s2am_ard_3-2-1_49KHR_2017-05-20_final
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGR_2017-07-12_final
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLL_2017-08-05_final
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50HPG_2017-09-01_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50JLP_2017-09-07_final
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-10-10_final
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HMJ_2017-11-13_final
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50JNM_2017-11-13_final
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HMJ_2018-02-11_final
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HPK_2018-03-20_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKP_2018-03-26_final
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HPK_2018-03-30_final
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HPJ_2018-05-16_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JKN_2018-07-11_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JNN_2018-07-18_final
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HMG_2018-07-31_final.stac-item
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KHR_2018-08-26_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKN_2018-09-02_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQN_2018-09-26_final
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HNG_2018-10-16_final.stac-item
2018-12-05 11:46:29	ga_s2am_ard_3-2-1_50HNK_2018-12-05_final
2018-12-05 11:46:54	ga_s2am_ard_3-2-1_50HPH_2018-12-05_final
2018-12-22 11:35:42	ga_s2am_ard_3-2-1_50JQN_2018-12-22_final
2019-01-01 11:37:15	ga_s2am_ard_3-2-1_50HPG_2019-01-01_final.stac-item
2019-02-23 11:46:18	ga_s2am_ard_3-2-1_50JNL_2019-02-23_final
2019-05-17 11:56:08	ga_s2am_ard_3-2-1_50JNM_2019-05-17_final
2019-08-18 12:05:58	ga_s2am_ard_3-2-1_50JKN_2019-08-18_final
2019-09-01 11:46:09	ga_s2am_ard_3-2-1_50JNM_2019-09-01_final
2019-10-07 12:05:54	ga_s2am_ard_3-2-1_50JLN_2019-10-07_final
2019-12-10 11:46:40	ga_s2am_ard_3-2-1_50HQJ_2019-12-10_final
2020-02-01 11:55:48	ga_s2am_ard_3-2-1_50JLN_2020-02-01_final
2020-02-05 11:36:40	ga_s2am_ard_3-2-1_50HQJ_2020-02-05_final
2020-02-14 12:05:34	ga_s2am_ard_3-2-1_50JKP_2020-02-14_final
2020-06-13 12:05:58	ga_s2am_ard_3-2-1_50JLN_2020-06-13_final
2020-07-03 12:05:46	ga_s2am_ard_3-2-1_50JKP_2020-07-03_final
2020-07-07 11:47:21	ga_s2am_ard_3-2-1_50HPG_2020-07-07_final.stac-item
2020-07-20 11:55:51	ga_s2am_ard_3-2-1_50JKP_2020-07-20_final
2020-07-24 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-07-24_final
2020-11-04 11:46:42	ga_s2am_ard_3-2-1_50HNK_2020-11-04_final
2020-11-07 11:56:15	ga_s2am_ard_3-2-1_50JLM_2020-11-07_final
2020-12-07 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2020-12-07_final
2020-12-13 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2020-12-13_final
2020-12-21 11:36:25	ga_s2am_ard_3-2-1_50JPL_2020-12-21_final
2020-12-27 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2020-12-27_final
2021-01-09 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-01-09_final
2021-01-10 11:36:20	ga_s2am_ard_3-2-1_50JQL_2021-01-10_final
2021-04-29 12:03:56	ga_s2am_ard_3-2-1_49KHR_2021-04-29_final
2021-05-06 11:55:01	ga_s2am_ard_3-2-1_50JPR_2021-05-06_final
2021-06-02 11:45:47	ga_s2am_ard_3-2-1_50JQN_2021-06-02_final
2021-06-25 11:55:43	ga_s2am_ard_3-2-1_50JLP_2021-06-25_final
2021-06-25 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-06-25_final
2022-01-08 11:46:35	ga_s2am_ard_3-2-1_50HPK_2022-01-08_final
2022-01-24 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-01-24_final
2022-02-13 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-13_final
2022-02-20 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-02-20_final
2022-04-21 11:56:30	ga_s2am_ard_3-2-1_50JLL_2022-04-21_final
2022-05-21 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-05-21_final
2022-05-28 11:46:45	ga_s2am_ard_3-2-1_50HNK_2022-05-28_final
2022-06-26 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-06-26_final
2022-11-13 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-11-13_final.stac-item
2022-11-30 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-11-30_final.stac-item
2022-12-20 12:04:41	ga_s2am_ard_3-2-1_49JHN_2022-12-20_final.stac-item
2022-12-21 11:37:19	ga_s2am_ard_3-2-1_50HPG_2022-12-21_final.stac-item
2023-01-02 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-01-02_final.stac-item
2023-01-22 12:14:37	ga_s2am_ard_3-2-1_49JGN_2023-01-22_final.stac-item
2023-02-05 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-02-05_final.stac-item
2023-02-21 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-02-21_final.stac-item
2023-03-04 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2023-03-04_final.stac-item
2023-03-07 11:56:26	ga_s2am_ard_3-2-1_50HNK_2023-03-07_final.stac-item
2023-04-06 11:57:06	ga_s2am_ard_3-2-1_50HMH_2023-04-06_final.stac-item
2023-06-15 11:56:12	ga_s2am_ard_3-2-1_50JMM_2023-06-15_final.stac-item
2023-06-15 11:56:26	ga_s2am_ard_3-2-1_50JML_2023-06-15_final.stac-item
2023-06-15 11:56:41	ga_s2am_ard_3-2-1_50HMK_2023-06-15_final.stac-item
2023-06-28 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-06-28_final.stac-item
2023-07-02 11:46:34	ga_s2am_ard_3-2-1_50HQK_2023-07-02_final.stac-item
2023-07-05 11:55:11	ga_s2am_ard_3-2-1_50JNR_2023-07-05_final.stac-item
2023-07-15 11:56:16	ga_s2am_ard_3-2-1_50JLM_2023-07-15_final.stac-item
2023-07-22 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-07-22_final.stac-item
2023-09-17 11:36:41	ga_s2am_ard_3-2-1_50HPK_2023-09-17_final.stac-item
2023-10-06 12:04:32	ga_s2am_ard_3-2-1_49KGP_2023-10-06_final.stac-item
2023-10-13 11:55:54	ga_s2am_ard_3-2-1_50JLN_2023-10-13_final.stac-item
2023-10-16 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-10-16_final.stac-item
2023-11-18 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-11-18_final.stac-item
2023-11-25 12:05:35	ga_s2am_ard_3-2-1_50JKP_2023-11-25_final.stac-item
2024-01-07 12:15:06	ga_s2am_ard_3-2-1_49JGL_2024-01-07_final.stac-item
2024-02-03 12:04:27	ga_s2am_ard_3-2-1_49KGP_2024-02-03_final.stac-item
2024-02-27 11:46:14	ga_s2am_ard_3-2-1_50JQL_2024-02-27_final.stac-item
2024-04-10 11:56:31	ga_s2am_ard_3-2-1_50JLL_2024-04-10_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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