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_50HLJ_2015-11-14_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_49JGL_2016-01-06_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGK_2016-01-26_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HMH_2016-04-19_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HMJ_2016-05-22_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49KGP_2016-06-24_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JKP_2016-09-19_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JKP_2016-12-11_final
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HPG_2017-01-01_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGL_2017-03-21_final
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JKN_2017-03-31_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HNK_2017-04-14_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KGP_2017-09-27_final
2018-04-19 11:46:08	ga_s2am_ard_3-2-1_50JMM_2018-04-19_final
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HLJ_2018-05-02_final
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JLN_2018-07-21_final
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50HLJ_2018-08-20_final
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGM_2018-08-23_final
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_50JPL_2018-08-24_final
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_50KKA_2018-09-15_final
2018-11-24 12:15:03	ga_s2am_ard_3-2-1_49JGL_2018-11-24_final
2019-02-02 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-02-02_final
2019-02-06 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2019-02-06_final
2019-02-12 12:13:55	ga_s2am_ard_3-2-1_49KGR_2019-02-12_final
2019-04-14 11:46:43	ga_s2am_ard_3-2-1_50HPJ_2019-04-14_final
2019-04-20 12:05:03	ga_s2am_ard_3-2-1_49JGM_2019-04-20_final
2019-05-23 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-05-23_final
2019-06-09 12:05:17	ga_s2am_ard_3-2-1_49JGL_2019-06-09_final
2019-06-19 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-06-19_final
2019-07-06 11:56:19	ga_s2am_ard_3-2-1_50JKM_2019-07-06_final
2019-08-18 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-08-18_final
2019-10-14 11:56:39	ga_s2am_ard_3-2-1_50HMK_2019-10-14_final
2020-02-11 11:56:44	ga_s2am_ard_3-2-1_50HMJ_2020-02-11_final
2020-05-04 12:04:08	ga_s2am_ard_3-2-1_49KHR_2020-05-04_final
2020-06-10 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-06-10_final
2020-06-14 11:37:27	ga_s2am_ard_3-2-1_50HPG_2020-06-14_final.stac-item
2020-06-24 11:37:23	ga_s2am_ard_3-2-1_50HQG_2020-06-24_final.stac-item
2020-07-16 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-07-16_final
2020-08-06 11:46:00	ga_s2am_ard_3-2-1_50JNN_2020-08-06_final
2020-09-28 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-09-28_final
2020-10-08 11:56:31	ga_s2am_ard_3-2-1_50JLL_2020-10-08_final
2020-10-21 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2020-10-21_final
2020-10-24 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-10-24_final
2020-10-28 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-10-28_final
2020-11-04 11:46:38	ga_s2am_ard_3-2-1_50HPK_2020-11-04_final
2020-11-30 12:03:44	ga_s2am_ard_3-2-1_50KKB_2020-11-30_final
2020-11-30 12:05:38	ga_s2am_ard_3-2-1_50JLP_2020-11-30_final
2020-12-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2020-12-30_final
2021-01-09 12:05:30	ga_s2am_ard_3-2-1_49JGK_2021-01-09_final
2021-02-08 12:03:58	ga_s2am_ard_3-2-1_50KKA_2021-02-08_final
2021-03-04 11:46:12	ga_s2am_ard_3-2-1_50JMM_2021-03-04_final
2021-03-11 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-03-11_final
2021-03-20 12:03:58	ga_s2am_ard_3-2-1_50KKA_2021-03-20_final
2021-05-06 11:56:39	ga_s2am_ard_3-2-1_50HLK_2021-05-06_final
2021-05-22 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-05-22_final
2021-06-15 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-06-15_final
2021-06-18 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-06-18_final
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final.stac-item
2021-09-03 11:56:26	ga_s2am_ard_3-2-1_50JLL_2021-09-03_final
2021-09-03 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2021-09-03_final
2021-09-06 12:05:52	ga_s2am_ard_3-2-1_50JLN_2021-09-06_final
2021-09-23 11:56:17	ga_s2am_ard_3-2-1_50JKM_2021-09-23_final
2021-10-20 11:46:06	ga_s2am_ard_3-2-1_50JQM_2021-10-20_final
2021-11-05 12:05:04	ga_s2am_ard_3-2-1_49JGM_2021-11-05_final
2021-11-08 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2021-11-08_final
2021-11-25 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-11-25_final
2021-12-05 12:05:55	ga_s2am_ard_3-2-1_50JKN_2021-12-05_final
2021-12-16 11:37:11	ga_s2am_ard_3-2-1_50HQH_2021-12-16_final
2021-12-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-12-18_final
2022-02-13 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2022-02-13_final
2022-05-31 11:56:15	ga_s2am_ard_3-2-1_50JMM_2022-05-31_final
2022-06-17 11:46:37	ga_s2am_ard_3-2-1_50JML_2022-06-17_final
2022-10-04 12:15:17	ga_s2am_ard_3-2-1_49JGL_2022-10-04_final.stac-item
2022-10-28 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-10-28_final.stac-item
2022-11-17 11:56:13	ga_s2am_ard_3-2-1_50JLM_2022-11-17_final.stac-item
2023-01-06 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2023-01-06_final.stac-item
2023-01-19 12:05:10	ga_s2am_ard_3-2-1_49JGL_2023-01-19_final.stac-item
2023-02-01 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-02-01_final.stac-item
2023-02-02 11:47:14	ga_s2am_ard_3-2-1_50HMH_2023-02-02_final.stac-item
2023-02-12 11:47:15	ga_s2am_ard_3-2-1_50HPG_2023-02-12_final.stac-item
2023-03-10 12:05:46	ga_s2am_ard_3-2-1_50JLN_2023-03-10_final.stac-item
2023-04-09 12:05:38	ga_s2am_ard_3-2-1_50JLP_2023-04-09_final.stac-item
2023-04-20 11:37:23	ga_s2am_ard_3-2-1_50HPG_2023-04-20_final.stac-item
2023-04-26 11:56:22	ga_s2am_ard_3-2-1_50JML_2023-04-26_final.stac-item
2023-04-29 12:03:59	ga_s2am_ard_3-2-1_49KHR_2023-04-29_final.stac-item
2023-06-01 12:14:45	ga_s2am_ard_3-2-1_49JGN_2023-06-01_final.stac-item
2023-06-12 11:46:41	ga_s2am_ard_3-2-1_50HNK_2023-06-12_final.stac-item
2023-07-28 12:03:49	ga_s2am_ard_3-2-1_50KKB_2023-07-28_final.stac-item
2023-08-11 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-08-11_final.stac-item
2023-11-18 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-11-18_final.stac-item
2023-11-28 12:14:20	ga_s2am_ard_3-2-1_49KGP_2023-11-28_final.stac-item
2023-12-05 12:05:08	ga_s2am_ard_3-2-1_49JGL_2023-12-05_final.stac-item
2024-01-01 11:55:56	ga_s2am_ard_3-2-1_50JKN_2024-01-01_final.stac-item
2024-01-11 11:55:51	ga_s2am_ard_3-2-1_50JLN_2024-01-11_final.stac-item
2024-01-21 11:56:44	ga_s2am_ard_3-2-1_50HLJ_2024-01-21_final.stac-item
2024-04-14 11:37:09	ga_s2am_ard_3-2-1_50HPH_2024-04-14_final.stac-item
2024-05-07 11:46:45	ga_s2am_ard_3-2-1_50HQJ_2024-05-07_final.stac-item
2024-05-10 11:56:28	ga_s2am_ard_3-2-1_50JLL_2024-05-10_final.stac-item
2024-05-10 11:56:32	ga_s2am_ard_3-2-1_50HNK_2024-05-10_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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