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
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGQ_2015-11-30_final.stac-item
2015-12-27 12:05:00	ga_s2am_ard_3-2-1_49JHM_2015-12-27_final.stac-item
2016-04-08 12:14:44	ga_s2am_ard_3-2-1_49JGM_2016-04-08_final.stac-item
2016-07-07 12:14:44	ga_s2am_ard_3-2-1_49JGL_2016-07-07_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49JGN_2016-09-12_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2016-10-05_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JHN_2016-10-25_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49KGQ_2017-02-22_final
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGM_2017-03-01_final
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_49JHM_2017-05-20_final
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_49JHN_2017-05-20_final
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2017-07-29_final
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_49JHM_2017-08-28_final
2017-09-10 12:13:33	ga_s2am_ard_3-2-1_49KGQ_2017-09-10_final
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JHN_2017-10-17_final
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49KGP_2017-10-17_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-11-19_final
2018-01-15 12:04:34	ga_s2am_ard_3-2-1_49JGM_2018-01-15_final
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGJ_2018-06-24_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHM_2018-07-14_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JHN_2018-07-14_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JFN_2018-09-05_final
2018-11-21 12:04:49	ga_s2am_ard_3-2-1_49JGM_2018-11-21_final
2018-11-24 12:15:03	ga_s2am_ard_3-2-1_49JGL_2018-11-24_final
2019-01-10 12:04:52	ga_s2am_ard_3-2-1_49JHM_2019-01-10_final
2019-01-20 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-20_final
2019-01-30 12:04:43	ga_s2am_ard_3-2-1_49JGN_2019-01-30_final
2019-03-11 12:04:41	ga_s2am_ard_3-2-1_49JGN_2019-03-11_final
2019-04-10 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-04-10_final
2019-04-23 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-04-23_final
2019-04-30 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2019-04-30_final
2019-06-09 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-06-09_final
2019-06-09 12:04:48	ga_s2am_ard_3-2-1_49JGN_2019-06-09_final
2019-06-29 12:05:19	ga_s2am_ard_3-2-1_49JGL_2019-06-29_final
2020-01-15 12:05:09	ga_s2am_ard_3-2-1_49JGL_2020-01-15_final
2020-01-25 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2020-01-25_final
2020-01-28 12:14:52	ga_s2am_ard_3-2-1_49JFM_2020-01-28_final
2020-03-08 12:15:06	ga_s2am_ard_3-2-1_49JGL_2020-03-08_final
2020-04-24 12:04:58	ga_s2am_ard_3-2-1_49JHM_2020-04-24_final
2020-04-27 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2020-04-27_final
2020-09-04 12:14:50	ga_s2am_ard_3-2-1_49JFN_2020-09-04_final
2020-09-11 12:04:35	ga_s2am_ard_3-2-1_49KGP_2020-09-11_final
2020-09-21 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2020-09-21_final
2020-10-24 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-10-24_final
2020-11-13 12:14:45	ga_s2am_ard_3-2-1_49JGN_2020-11-13_final
2020-11-30 12:04:42	ga_s2am_ard_3-2-1_49JHN_2020-11-30_final
2021-01-12 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-01-12_final
2021-02-11 12:14:55	ga_s2am_ard_3-2-1_49JGM_2021-02-11_final
2021-05-12 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-05-12_final
2021-05-19 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-05-19_final
2021-09-16 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-09-16_final
2021-10-06 12:05:05	ga_s2am_ard_3-2-1_49JGM_2021-10-06_final
2021-11-08 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-11-08_final
2021-11-08 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-11-08_final
2021-12-18 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-12-18_final
2021-12-25 12:04:44	ga_s2am_ard_3-2-1_49JHN_2021-12-25_final
2022-01-14 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-01-14_final
2022-01-17 12:14:42	ga_s2am_ard_3-2-1_49JGN_2022-01-17_final
2022-01-24 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-01-24_final
2022-02-03 12:04:42	ga_s2am_ard_3-2-1_49JHN_2022-02-03_final
2022-03-08 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-03-08_final
2022-03-18 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-03-18_final
2022-04-14 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final
2022-05-07 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-05-07_final
2022-05-14 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-05-14_final
2022-05-14 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-05-14_final
2022-07-26 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2022-07-26_final
2022-08-02 12:04:53	ga_s2am_ard_3-2-1_49JHN_2022-08-02_final
2022-10-04 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-10-04_final.stac-item
2022-10-21 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-10-21_final.stac-item
2022-11-13 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-11-13_final.stac-item
2022-11-20 12:04:58	ga_s2am_ard_3-2-1_49JHM_2022-11-20_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2022-12-20 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-12-20_final.stac-item
2022-12-23 12:14:54	ga_s2am_ard_3-2-1_49JGM_2022-12-23_final.stac-item
2023-01-02 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-01-02_final.stac-item
2023-02-28 12:04:40	ga_s2am_ard_3-2-1_49JHN_2023-02-28_final.stac-item
2023-03-10 12:04:51	ga_s2am_ard_3-2-1_49JHM_2023-03-10_final.stac-item
2023-03-20 12:04:55	ga_s2am_ard_3-2-1_49JHM_2023-03-20_final.stac-item
2023-04-02 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-04-02_final.stac-item
2023-04-19 12:04:41	ga_s2am_ard_3-2-1_49JHN_2023-04-19_final.stac-item
2023-05-09 12:04:25	ga_s2am_ard_3-2-1_49KGP_2023-05-09_final.stac-item
2023-06-08 12:05:00	ga_s2am_ard_3-2-1_49JHM_2023-06-08_final.stac-item
2023-06-21 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2023-06-21_final.stac-item
2023-06-28 12:05:01	ga_s2am_ard_3-2-1_49JHM_2023-06-28_final.stac-item
2023-07-21 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-07-21_final.stac-item
2023-07-31 12:14:47	ga_s2am_ard_3-2-1_49JGN_2023-07-31_final.stac-item
2023-08-10 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-08-10_final.stac-item
2023-08-27 12:04:48	ga_s2am_ard_3-2-1_49JHN_2023-08-27_final.stac-item
2023-10-06 12:05:01	ga_s2am_ard_3-2-1_49JGM_2023-10-06_final.stac-item
2023-10-19 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-10-19_final.stac-item
2023-10-26 12:04:42	ga_s2am_ard_3-2-1_49JHN_2023-10-26_final.stac-item
2023-11-05 12:04:56	ga_s2am_ard_3-2-1_49JHM_2023-11-05_final.stac-item
2023-11-08 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-11-08_final.stac-item
2023-11-15 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-11-15_final.stac-item
2023-12-25 12:04:53	ga_s2am_ard_3-2-1_49JHM_2023-12-25_final.stac-item
2024-01-04 12:05:11	ga_s2am_ard_3-2-1_49JGL_2024-01-04_final.stac-item
2024-01-17 12:14:33	ga_s2am_ard_3-2-1_49JGN_2024-01-17_final.stac-item
2024-01-27 12:14:21	ga_s2am_ard_3-2-1_49KGP_2024-01-27_final.stac-item
2024-02-13 12:04:54	ga_s2am_ard_3-2-1_49JHM_2024-02-13_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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