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
2015-10-01 12:13:46	ga_s2am_ard_3-2-1_49KFR_2015-10-01_final.stac-item
2022-09-04 12:14:57	ga_s2am_ard_3-2-1_49JFN_2022-09-04_final.stac-item
2022-09-14 12:14:55	ga_s2am_ard_3-2-1_49JFN_2022-09-14_final.stac-item
2022-09-24 12:14:52	ga_s2am_ard_3-2-1_49JFN_2022-09-24_final.stac-item
2022-10-04 12:14:52	ga_s2am_ard_3-2-1_49JFN_2022-10-04_final.stac-item
2022-10-14 12:14:50	ga_s2am_ard_3-2-1_49JFN_2022-10-14_final.stac-item
2022-10-24 12:14:48	ga_s2am_ard_3-2-1_49JFN_2022-10-24_final.stac-item
2022-11-03 12:14:49	ga_s2am_ard_3-2-1_49JFN_2022-11-03_final.stac-item
2022-11-13 12:14:48	ga_s2am_ard_3-2-1_49JFN_2022-11-13_final.stac-item
2022-11-23 12:14:45	ga_s2am_ard_3-2-1_49JFN_2022-11-23_final.stac-item
2022-12-03 12:14:46	ga_s2am_ard_3-2-1_49JFN_2022-12-03_final.stac-item
2022-12-13 12:14:02	ga_s2am_ard_3-2-1_49KFR_2022-12-13_nrt.stac-item
2022-12-13 12:14:12	ga_s2am_ard_3-2-1_49KFQ_2022-12-13_nrt.stac-item
2022-12-13 12:14:45	ga_s2am_ard_3-2-1_49JFN_2022-12-13_final.stac-item
2022-12-23 12:13:59	ga_s2am_ard_3-2-1_49KFR_2022-12-23_nrt.stac-item
2022-12-23 12:14:43	ga_s2am_ard_3-2-1_49JFN_2022-12-23_final.stac-item
2023-01-02 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-01-02_nrt.stac-item
2023-01-02 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-01-02_final.stac-item
2023-01-12 12:14:00	ga_s2am_ard_3-2-1_49KFR_2023-01-12_nrt.stac-item
2023-01-12 12:14:43	ga_s2am_ard_3-2-1_49JFN_2023-01-12_final.stac-item
2023-01-22 12:13:57	ga_s2am_ard_3-2-1_49KFR_2023-01-22_nrt.stac-item
2023-01-22 12:14:41	ga_s2am_ard_3-2-1_49JFN_2023-01-22_final.stac-item
2023-02-01 12:14:00	ga_s2am_ard_3-2-1_49KFR_2023-02-01_nrt.stac-item
2023-02-11 12:14:00	ga_s2am_ard_3-2-1_49KFR_2023-02-11_nrt.stac-item
2023-02-11 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-02-11_final.stac-item
2023-02-21 12:13:59	ga_s2am_ard_3-2-1_49KFR_2023-02-21_nrt.stac-item
2023-02-21 12:14:43	ga_s2am_ard_3-2-1_49JFN_2023-02-21_final.stac-item
2023-03-03 12:13:59	ga_s2am_ard_3-2-1_49KFR_2023-03-03_nrt.stac-item
2023-03-03 12:14:42	ga_s2am_ard_3-2-1_49JFN_2023-03-03_final.stac-item
2023-03-13 12:13:58	ga_s2am_ard_3-2-1_49KFR_2023-03-13_nrt.stac-item
2023-03-23 12:14:00	ga_s2am_ard_3-2-1_49KFR_2023-03-23_nrt.stac-item
2023-04-02 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-04-02_nrt.stac-item
2023-04-02 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-04-02_final.stac-item
2023-04-12 12:14:02	ga_s2am_ard_3-2-1_49KFR_2023-04-12_nrt.stac-item
2023-04-12 12:14:45	ga_s2am_ard_3-2-1_49JFN_2023-04-12_final.stac-item
2023-04-22 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-04-22_nrt.stac-item
2023-04-22 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-04-22_final.stac-item
2023-05-02 12:14:02	ga_s2am_ard_3-2-1_49KFR_2023-05-02_nrt.stac-item
2023-05-02 12:14:46	ga_s2am_ard_3-2-1_49JFN_2023-05-02_final.stac-item
2023-05-12 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-05-12_nrt.stac-item
2023-05-12 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-05-12_final.stac-item
2023-05-22 12:14:05	ga_s2am_ard_3-2-1_49KFR_2023-05-22_nrt.stac-item
2023-05-22 12:14:48	ga_s2am_ard_3-2-1_49JFN_2023-05-22_final.stac-item
2023-06-01 12:14:06	ga_s2am_ard_3-2-1_49KFR_2023-06-01_nrt.stac-item
2023-06-01 12:14:49	ga_s2am_ard_3-2-1_49JFN_2023-06-01_final.stac-item
2023-06-11 12:14:06	ga_s2am_ard_3-2-1_49KFR_2023-06-11_nrt.stac-item
2023-06-11 12:14:49	ga_s2am_ard_3-2-1_49JFN_2023-06-11_final.stac-item
2023-06-21 12:14:05	ga_s2am_ard_3-2-1_49KFR_2023-06-21_nrt.stac-item
2023-06-21 12:14:49	ga_s2am_ard_3-2-1_49JFN_2023-06-21_final.stac-item
2023-07-01 12:14:06	ga_s2am_ard_3-2-1_49KFR_2023-07-01_nrt.stac-item
2023-07-01 12:14:50	ga_s2am_ard_3-2-1_49JFN_2023-07-01_final.stac-item
2023-07-11 12:14:07	ga_s2am_ard_3-2-1_49KFR_2023-07-11_nrt.stac-item
2023-07-11 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-07-11_final.stac-item
2023-07-21 12:14:06	ga_s2am_ard_3-2-1_49KFR_2023-07-21_interim.stac-item
2023-07-21 12:14:49	ga_s2am_ard_3-2-1_49JFN_2023-07-21_final.stac-item
2023-07-31 12:14:07	ga_s2am_ard_3-2-1_49KFR_2023-07-31_nrt.stac-item
2023-07-31 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-07-31_final.stac-item
2023-08-10 12:14:50	ga_s2am_ard_3-2-1_49JFN_2023-08-10_final.stac-item
2023-08-20 12:14:08	ga_s2am_ard_3-2-1_49KFR_2023-08-20_nrt.stac-item
2023-08-20 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-08-20_final.stac-item
2023-08-30 12:14:07	ga_s2am_ard_3-2-1_49KFR_2023-08-30_nrt.stac-item
2023-08-30 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-08-30_final.stac-item
2023-09-09 12:14:07	ga_s2am_ard_3-2-1_49KFR_2023-09-09_nrt.stac-item
2023-09-09 12:14:50	ga_s2am_ard_3-2-1_49JFN_2023-09-09_final.stac-item
2023-09-19 12:14:04	ga_s2am_ard_3-2-1_49KFR_2023-09-19_nrt.stac-item
2023-09-19 12:14:48	ga_s2am_ard_3-2-1_49JFN_2023-09-19_final.stac-item
2023-09-29 12:14:04	ga_s2am_ard_3-2-1_49KFR_2023-09-29_nrt.stac-item
2023-09-29 12:14:48	ga_s2am_ard_3-2-1_49JFN_2023-09-29_final.stac-item
2023-10-09 12:14:45	ga_s2am_ard_3-2-1_49JFN_2023-10-09_final.stac-item
2023-10-19 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-10-19_nrt.stac-item
2023-10-19 12:14:45	ga_s2am_ard_3-2-1_49JFN_2023-10-19_final.stac-item
2023-10-29 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-10-29_nrt.stac-item
2023-10-29 12:14:45	ga_s2am_ard_3-2-1_49JFN_2023-10-29_final.stac-item
2023-11-08 12:14:01	ga_s2am_ard_3-2-1_49KFR_2023-11-08_nrt.stac-item
2023-11-08 12:14:45	ga_s2am_ard_3-2-1_49JFN_2023-11-08_final.stac-item
2023-11-18 12:13:59	ga_s2am_ard_3-2-1_49KFR_2023-11-18_nrt.stac-item
2023-11-18 12:14:43	ga_s2am_ard_3-2-1_49JFN_2023-11-18_final.stac-item
2023-11-28 12:13:54	ga_s2am_ard_3-2-1_49KFR_2023-11-28_nrt.stac-item
2023-11-28 12:14:38	ga_s2am_ard_3-2-1_49JFN_2023-11-28_final.stac-item
2023-12-08 12:13:56	ga_s2am_ard_3-2-1_49KFR_2023-12-08_nrt.stac-item
2023-12-08 12:14:40	ga_s2am_ard_3-2-1_49JFN_2023-12-08_final.stac-item
2023-12-18 12:13:58	ga_s2am_ard_3-2-1_49KFR_2023-12-18_nrt.stac-item
2023-12-18 12:14:41	ga_s2am_ard_3-2-1_49JFN_2023-12-18_final.stac-item
2023-12-28 12:13:59	ga_s2am_ard_3-2-1_49KFR_2023-12-28_nrt.stac-item
2023-12-28 12:14:42	ga_s2am_ard_3-2-1_49JFN_2023-12-28_final.stac-item
2024-01-07 12:13:58	ga_s2am_ard_3-2-1_49KFR_2024-01-07_nrt.stac-item
2024-01-17 12:13:53	ga_s2am_ard_3-2-1_49KFR_2024-01-17_nrt.stac-item
2024-01-27 12:13:56	ga_s2am_ard_3-2-1_49KFR_2024-01-27_nrt.stac-item
2024-02-06 12:13:58	ga_s2am_ard_3-2-1_49KFR_2024-02-06_nrt.stac-item
2024-02-16 12:13:59	ga_s2am_ard_3-2-1_49KFR_2024-02-16_nrt.stac-item
2024-02-26 12:14:01	ga_s2am_ard_3-2-1_49KFR_2024-02-26_nrt.stac-item
2024-02-26 12:14:13	ga_s2am_ard_3-2-1_49KFQ_2024-02-26_nrt.stac-item
2024-03-07 12:14:02	ga_s2am_ard_3-2-1_49KFR_2024-03-07_nrt.stac-item
2024-03-17 12:14:02	ga_s2am_ard_3-2-1_49KFR_2024-03-17_nrt.stac-item
2024-03-27 12:14:02	ga_s2am_ard_3-2-1_49KFR_2024-03-27_nrt.stac-item
2024-04-06 12:14:00	ga_s2am_ard_3-2-1_49KFR_2024-04-06_nrt.stac-item
2024-04-16 12:14:04	ga_s2am_ard_3-2-1_49KFR_2024-04-16_nrt.stac-item
2024-04-26 12:14:04	ga_s2am_ard_3-2-1_49KFR_2024-04-26_nrt.stac-item
2024-04-26 12:14:11	ga_s2am_ard_3-2-1_49KFR_2024-04-26_nrt.stac-item
2024-05-06 12:14:04	ga_s2am_ard_3-2-1_49KFR_2024-05-06_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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