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
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_49JHN_2016-07-24_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JHN_2016-08-23_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JGM_2016-09-02_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KGR_2016-09-15_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JGN_2016-12-01_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KGP_2016-12-01_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49JGM_2016-12-21_final
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JHN_2017-02-22_final
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49JGM_2017-04-20_final.stac-item
2017-06-09 12:04:43	ga_s2am_ard_3-2-1_49JGN_2017-06-09_final
2017-08-11 12:14:43	ga_s2am_ard_3-2-1_49JGM_2017-08-11_final
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGM_2017-09-17_final
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-24_final
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_49JHN_2018-03-16_final
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_49KGP_2018-05-08_final
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JHN_2018-05-15_final
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_49JGJ_2018-06-04_final
2018-06-17 12:13:21	ga_s2am_ard_3-2-1_49JGN_2018-06-17_final
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JFM_2018-07-17_final
2018-08-26 12:13:20	ga_s2am_ard_3-2-1_49KGQ_2018-08-26_final
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGP_2018-09-05_final
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_final
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-10-25_final
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-11-01_final
2018-12-31 12:04:50	ga_s2am_ard_3-2-1_49JHM_2018-12-31_final
2019-01-03 12:14:21	ga_s2am_ard_3-2-1_49KGP_2019-01-03_final
2019-02-02 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-02-02_final
2019-02-19 12:05:25	ga_s2am_ard_3-2-1_49JGK_2019-02-19_final
2019-02-22 12:15:06	ga_s2am_ard_3-2-1_49JGL_2019-02-22_final
2019-05-20 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-05-20_final
2019-07-02 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-07-02_final
2019-07-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2019-07-02_final
2019-07-19 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2019-07-19_final
2019-08-21 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-08-21_final
2019-08-28 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-08-28_final
2019-09-07 12:05:00	ga_s2am_ard_3-2-1_49JGM_2019-09-07_final
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final
2019-11-26 12:05:01	ga_s2am_ard_3-2-1_49JGM_2019-11-26_final
2020-01-28 12:14:24	ga_s2am_ard_3-2-1_49JHN_2020-01-28_final
2020-02-17 12:14:20	ga_s2am_ard_3-2-1_49KGP_2020-02-17_final
2020-02-17 12:14:35	ga_s2am_ard_3-2-1_49JGN_2020-02-17_final
2020-03-18 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2020-03-18_final
2020-03-28 12:14:23	ga_s2am_ard_3-2-1_49KGP_2020-03-28_final
2020-04-14 12:05:14	ga_s2am_ard_3-2-1_49JGL_2020-04-14_final
2020-05-04 12:04:35	ga_s2am_ard_3-2-1_49KGP_2020-05-04_final
2020-06-26 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-06-26_final
2020-08-05 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-08-05_final
2020-08-12 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-08-12_final
2020-08-22 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-08-22_final
2020-09-14 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-09-14_final
2020-10-01 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-10-01_final
2021-01-12 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-01-12_final
2021-03-20 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-03-20_final
2021-04-09 12:04:38	ga_s2am_ard_3-2-1_49JHN_2021-04-09_final
2021-04-19 12:05:05	ga_s2am_ard_3-2-1_49JGL_2021-04-19_final
2021-05-09 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-05-09_final
2021-06-18 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-06-18_final
2021-10-16 12:04:51	ga_s2am_ard_3-2-1_49JGN_2021-10-16_final
2021-11-25 12:04:42	ga_s2am_ard_3-2-1_49JHN_2021-11-25_final
2021-12-15 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-12-15_final
2022-02-06 12:14:26	ga_s2am_ard_3-2-1_49KGP_2022-02-06_final
2022-02-06 12:14:41	ga_s2am_ard_3-2-1_49JGN_2022-02-06_final
2022-03-15 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-03-15_final
2022-04-24 12:05:20	ga_s2am_ard_3-2-1_49JGL_2022-04-24_final
2022-05-14 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-05-14_final
2022-06-03 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-06-03_final
2022-06-06 12:14:20	ga_s2am_ard_3-2-1_49KGQ_2022-06-06_final
2022-07-03 12:05:10	ga_s2am_ard_3-2-1_49JHM_2022-07-03_final
2022-07-23 12:05:08	ga_s2am_ard_3-2-1_49JHM_2022-07-23_final
2022-08-22 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-08-22_final
2022-09-21 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-09-21_final.stac-item
2022-10-21 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-10-21_final.stac-item
2022-11-13 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-11-13_final.stac-item
2022-11-20 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-11-20_final.stac-item
2022-11-30 12:05:01	ga_s2am_ard_3-2-1_49JGM_2022-11-30_final.stac-item
2022-12-03 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-12-03_final.stac-item
2022-12-30 12:04:45	ga_s2am_ard_3-2-1_49JGN_2022-12-30_final.stac-item
2023-02-08 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-02-08_final.stac-item
2023-02-11 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-02-11_final.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_final.stac-item
2023-02-28 12:04:24	ga_s2am_ard_3-2-1_49KHP_2023-02-28_final.stac-item
2023-03-10 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-03-10_final.stac-item
2023-03-23 12:14:55	ga_s2am_ard_3-2-1_49JGM_2023-03-23_final.stac-item
2023-04-29 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-04-29_final.stac-item
2023-05-09 12:04:23	ga_s2am_ard_3-2-1_49KHP_2023-05-09_final.stac-item
2023-05-22 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2023-05-22_final.stac-item
2023-07-11 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-07-11_final.stac-item
2023-07-18 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-07-18_final.stac-item
2023-08-27 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-27_final.stac-item
2023-08-30 12:14:32	ga_s2am_ard_3-2-1_49KGP_2023-08-30_final.stac-item
2023-08-30 12:15:01	ga_s2am_ard_3-2-1_49JGM_2023-08-30_final.stac-item
2023-09-06 12:04:51	ga_s2am_ard_3-2-1_49JGN_2023-09-06_final.stac-item
2023-09-16 12:04:50	ga_s2am_ard_3-2-1_49JGN_2023-09-16_final.stac-item
2023-09-26 12:04:33	ga_s2am_ard_3-2-1_49KGP_2023-09-26_final.stac-item
2023-11-15 12:04:41	ga_s2am_ard_3-2-1_49JHN_2023-11-15_final.stac-item
2023-11-18 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-11-18_final.stac-item
2023-12-08 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2023-12-08_final.stac-item
2023-12-08 12:14:50	ga_s2am_ard_3-2-1_49JGM_2023-12-08_final.stac-item
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-12-25_final.stac-item
2024-01-07 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-01-07_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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