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
2015-12-05 11:26:08	ga_s2am_ard_3-2-1_51JUF_2015-12-05_final.stac-item
2016-01-04 11:26:26	ga_s2am_ard_3-2-1_51JUF_2016-01-04_final.stac-item
2016-04-13 11:26:08	ga_s2am_ard_3-2-1_51JUF_2016-04-13_final.stac-item
2016-06-22 11:26:10	ga_s2am_ard_3-2-1_51JUF_2016-06-22_final.stac-item
2016-08-01 11:26:13	ga_s2am_ard_3-2-1_51JUF_2016-08-01_final.stac-item
2016-08-21 11:26:11	ga_s2am_ard_3-2-1_51JUF_2016-08-21_final.stac-item
2016-09-10 11:26:07	ga_s2am_ard_3-2-1_51JUF_2016-09-10_final.stac-item
2019-06-23 11:43:19	ga_s2am_ard_3-2-1_51KUT_2019-06-23_final
2019-10-01 11:43:16	ga_s2am_ard_3-2-1_51KUT_2019-10-01_final
2019-10-31 11:43:18	ga_s2am_ard_3-2-1_51KUT_2019-10-31_final
2019-11-10 11:43:17	ga_s2am_ard_3-2-1_51KUT_2019-11-10_final
2019-11-20 11:43:16	ga_s2am_ard_3-2-1_51KUT_2019-11-20_final
2019-11-30 11:43:14	ga_s2am_ard_3-2-1_51KUT_2019-11-30_final
2019-12-10 11:43:11	ga_s2am_ard_3-2-1_51KUT_2019-12-10_final
2019-12-20 11:43:09	ga_s2am_ard_3-2-1_51KUT_2019-12-20_final
2020-04-25 11:35:03	ga_s2am_ard_3-2-1_51JUL_2020-04-25_final
2020-05-05 11:35:05	ga_s2am_ard_3-2-1_51JUL_2020-05-05_final
2020-05-15 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-05-15_final
2020-05-25 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-05-25_final
2020-06-04 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-06-04_final
2020-06-14 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-06-14_final
2020-06-24 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-06-24_final
2020-07-04 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-07-04_final
2020-07-14 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-07-14_final
2020-07-24 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-07-24_final
2020-08-03 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-08-03_final
2020-08-13 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-08-13_final
2020-08-23 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-08-23_final
2020-09-02 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-09-02_final
2020-09-12 11:35:05	ga_s2am_ard_3-2-1_51JUL_2020-09-12_final
2020-09-22 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-09-22_final
2020-10-02 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-10-02_final
2020-10-12 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-10-12_final
2020-10-22 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-10-22_final
2020-11-01 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-11-01_final
2020-11-11 11:35:05	ga_s2am_ard_3-2-1_51JUL_2020-11-11_final
2020-11-21 11:35:03	ga_s2am_ard_3-2-1_51JUL_2020-11-21_final
2020-12-01 11:35:01	ga_s2am_ard_3-2-1_51JUL_2020-12-01_final
2020-12-11 11:34:57	ga_s2am_ard_3-2-1_51JUL_2020-12-11_final
2022-12-17 11:50:43	ga_s2am_ard_3-2-1_51LUH_2022-12-17_nrt.stac-item
2022-12-27 11:50:43	ga_s2am_ard_3-2-1_51LUH_2022-12-27_nrt.stac-item
2023-01-06 11:50:43	ga_s2am_ard_3-2-1_51LUH_2023-01-06_nrt.stac-item
2023-01-16 11:50:40	ga_s2am_ard_3-2-1_51LUH_2023-01-16_nrt.stac-item
2023-01-26 11:50:41	ga_s2am_ard_3-2-1_51LUH_2023-01-26_nrt.stac-item
2023-02-05 11:50:43	ga_s2am_ard_3-2-1_51LUH_2023-02-05_nrt.stac-item
2023-02-09 11:35:05	ga_s2am_ard_3-2-1_51JUL_2023-02-09_final.stac-item
2023-02-15 11:50:41	ga_s2am_ard_3-2-1_51LUH_2023-02-15_nrt.stac-item
2023-02-25 11:50:42	ga_s2am_ard_3-2-1_51LUH_2023-02-25_nrt.stac-item
2023-03-07 11:50:40	ga_s2am_ard_3-2-1_51LUH_2023-03-07_nrt.stac-item
2023-03-17 11:50:42	ga_s2am_ard_3-2-1_51LUH_2023-03-17_nrt.stac-item
2023-03-27 11:50:42	ga_s2am_ard_3-2-1_51LUH_2023-03-27_nrt.stac-item
2023-04-06 11:50:44	ga_s2am_ard_3-2-1_51LUH_2023-04-06_nrt.stac-item
2023-04-26 11:50:44	ga_s2am_ard_3-2-1_51LUH_2023-04-26_nrt.stac-item
2023-05-06 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-05-06_nrt.stac-item
2023-05-16 11:50:45	ga_s2am_ard_3-2-1_51LUH_2023-05-16_nrt.stac-item
2023-05-26 11:50:47	ga_s2am_ard_3-2-1_51LUH_2023-05-26_nrt.stac-item
2023-06-05 11:50:48	ga_s2am_ard_3-2-1_51LUH_2023-06-05_nrt.stac-item
2023-06-15 11:50:48	ga_s2am_ard_3-2-1_51LUH_2023-06-15_nrt.stac-item
2023-06-25 11:50:47	ga_s2am_ard_3-2-1_51LUH_2023-06-25_nrt.stac-item
2023-07-05 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-07-05_nrt.stac-item
2023-07-15 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-07-15_nrt.stac-item
2023-07-19 11:36:22	ga_s2am_ard_3-2-1_51JUF_2023-07-19_final.stac-item
2023-07-25 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-07-25_nrt.stac-item
2023-08-04 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-08-04_nrt.stac-item
2023-08-14 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-08-14_nrt.stac-item
2023-08-24 11:50:50	ga_s2am_ard_3-2-1_51LUH_2023-08-24_nrt.stac-item
2023-08-28 11:35:37	ga_s2am_ard_3-2-1_51JUJ_2023-08-28_final.stac-item
2023-09-03 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-09-03_nrt.stac-item
2023-09-13 11:50:49	ga_s2am_ard_3-2-1_51LUH_2023-09-13_nrt.stac-item
2023-09-23 11:50:46	ga_s2am_ard_3-2-1_51LUH_2023-09-23_nrt.stac-item
2023-10-03 11:50:46	ga_s2am_ard_3-2-1_51LUH_2023-10-03_nrt.stac-item
2023-10-13 11:50:42	ga_s2am_ard_3-2-1_51LUH_2023-10-13_nrt.stac-item
2023-10-23 11:50:44	ga_s2am_ard_3-2-1_51LUH_2023-10-23_nrt.stac-item
2023-11-02 11:50:43	ga_s2am_ard_3-2-1_51LUH_2023-11-02_nrt.stac-item
2023-11-12 11:50:43	ga_s2am_ard_3-2-1_51LUH_2023-11-12_nrt.stac-item
2023-11-22 11:50:40	ga_s2am_ard_3-2-1_51LUH_2023-11-22_nrt.stac-item
2023-11-26 11:34:50	ga_s2am_ard_3-2-1_51JUL_2023-11-26_final.stac-item
2023-11-26 11:34:56	ga_s2am_ard_3-2-1_51JUL_2023-11-26_final.stac-item
2023-12-02 11:50:36	ga_s2am_ard_3-2-1_51LUH_2023-12-02_nrt.stac-item
2023-12-06 11:35:33	ga_s2am_ard_3-2-1_51JUH_2023-12-06_final.stac-item
2023-12-12 11:50:39	ga_s2am_ard_3-2-1_51LUH_2023-12-12_nrt.stac-item
2023-12-22 11:50:40	ga_s2am_ard_3-2-1_51LUH_2023-12-22_nrt.stac-item
2024-01-01 11:50:41	ga_s2am_ard_3-2-1_51LUH_2024-01-01_nrt.stac-item
2024-01-05 11:35:37	ga_s2am_ard_3-2-1_51JUH_2024-01-05_final.stac-item
2024-01-11 11:50:39	ga_s2am_ard_3-2-1_51LUH_2024-01-11_nrt.stac-item
2024-01-21 11:50:36	ga_s2am_ard_3-2-1_51LUH_2024-01-21_nrt.stac-item
2024-01-31 11:50:40	ga_s2am_ard_3-2-1_51LUH_2024-01-31_nrt.stac-item
2024-02-10 11:50:40	ga_s2am_ard_3-2-1_51LUH_2024-02-10_nrt.stac-item
2024-02-20 11:50:42	ga_s2am_ard_3-2-1_51LUH_2024-02-20_nrt.stac-item
2024-03-01 11:50:44	ga_s2am_ard_3-2-1_51LUH_2024-03-01_nrt.stac-item
2024-03-02 11:26:20	ga_s2am_ard_3-2-1_51JUF_2024-03-02_final.stac-item
2024-03-11 11:50:44	ga_s2am_ard_3-2-1_51LUH_2024-03-11_nrt.stac-item
2024-03-12 11:26:20	ga_s2am_ard_3-2-1_51JUF_2024-03-12_final.stac-item
2024-03-21 11:50:45	ga_s2am_ard_3-2-1_51LUH_2024-03-21_nrt.stac-item
2024-03-31 11:50:43	ga_s2am_ard_3-2-1_51LUH_2024-03-31_nrt.stac-item
2024-04-10 11:50:44	ga_s2am_ard_3-2-1_51LUH_2024-04-10_nrt.stac-item
2024-04-20 11:50:47	ga_s2am_ard_3-2-1_51LUH_2024-04-20_nrt.stac-item
2024-04-30 11:50:47	ga_s2am_ard_3-2-1_51LUH_2024-04-30_nrt.stac-item
2024-05-10 11:50:47	ga_s2am_ard_3-2-1_51LUH_2024-05-10_nrt.stac-item
2024-05-20 11:50:45	ga_s2am_ard_3-2-1_51LUH_2024-05-20_nrt.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

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