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
2018-03-07 11:30:40	ga_s2am_ard_3-2-1_51JWL_2018-03-07_final
2018-04-03 11:23:03	ga_s2am_ard_3-2-1_51JWL_2018-04-03_final
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JWL_2018-04-23_final
2018-04-26 11:32:59	ga_s2am_ard_3-2-1_51JWL_2018-04-26_final
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_51JWL_2018-05-03_final
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51JWL_2018-05-06_final
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51JWL_2018-06-05_final
2018-06-22 11:20:28	ga_s2am_ard_3-2-1_51JWL_2018-06-22_final
2018-07-02 11:23:55	ga_s2am_ard_3-2-1_51JWL_2018-07-02_final
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51JWL_2018-07-15_final
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51JWL_2018-07-25_final
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51JWL_2018-08-01_final
2018-08-11 11:19:45	ga_s2am_ard_3-2-1_51JWL_2018-08-11_final
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51JWL_2018-08-14_final
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51JWL_2018-08-31_final
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JWL_2018-09-03_final
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JWL_2018-09-10_final
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_51JWL_2018-09-13_final
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51JWL_2018-09-20_final
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JWL_2018-09-23_final
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWL_2018-09-30_final
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_51JWL_2018-10-03_final
2022-01-05 11:35:01	ga_s2am_ard_3-2-1_51JVL_2022-01-05_final
2022-01-12 11:25:04	ga_s2am_ard_3-2-1_51JVL_2022-01-12_final
2022-01-15 11:34:59	ga_s2am_ard_3-2-1_51JVL_2022-01-15_final
2022-01-22 11:25:03	ga_s2am_ard_3-2-1_51JVL_2022-01-22_final
2022-01-25 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-01-25_final
2022-02-01 11:25:03	ga_s2am_ard_3-2-1_51JVL_2022-02-01_final
2022-02-04 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-02-04_final
2022-02-11 11:25:02	ga_s2am_ard_3-2-1_51JVL_2022-02-11_final
2022-02-14 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-02-14_final
2022-02-21 11:25:05	ga_s2am_ard_3-2-1_51JVL_2022-02-21_final
2022-02-24 11:35:00	ga_s2am_ard_3-2-1_51JVL_2022-02-24_final
2022-03-03 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-03-03_final
2022-03-06 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-03-06_final
2022-03-13 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-03-13_final
2022-03-16 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-03-16_final
2022-03-23 11:25:06	ga_s2am_ard_3-2-1_51JVL_2022-03-23_final
2022-03-26 11:35:00	ga_s2am_ard_3-2-1_51JVL_2022-03-26_final
2022-04-02 11:25:05	ga_s2am_ard_3-2-1_51JVL_2022-04-02_final
2022-04-05 11:34:59	ga_s2am_ard_3-2-1_51JVL_2022-04-05_final
2022-04-12 11:25:06	ga_s2am_ard_3-2-1_51JVL_2022-04-12_final
2022-04-15 11:35:01	ga_s2am_ard_3-2-1_51JVL_2022-04-15_final
2022-04-22 11:25:08	ga_s2am_ard_3-2-1_51JVL_2022-04-22_final
2022-04-25 11:35:03	ga_s2am_ard_3-2-1_51JVL_2022-04-25_final
2022-05-02 11:25:08	ga_s2am_ard_3-2-1_51JVL_2022-05-02_final
2022-05-05 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-05-05_final
2022-05-12 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-05-12_final
2022-05-15 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-05-15_final
2022-05-22 11:25:10	ga_s2am_ard_3-2-1_51JVL_2022-05-22_final
2022-05-25 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-05-25_final
2022-06-01 11:25:11	ga_s2am_ard_3-2-1_51JVL_2022-06-01_final
2022-06-04 11:35:06	ga_s2am_ard_3-2-1_51JVL_2022-06-04_final
2022-06-11 11:25:13	ga_s2am_ard_3-2-1_51JVL_2022-06-11_final
2022-06-14 11:35:08	ga_s2am_ard_3-2-1_51JVL_2022-06-14_final
2022-06-21 11:25:15	ga_s2am_ard_3-2-1_51JVL_2022-06-21_final
2022-06-24 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-06-24_final
2022-07-01 11:25:16	ga_s2am_ard_3-2-1_51JVL_2022-07-01_final
2022-07-04 11:35:11	ga_s2am_ard_3-2-1_51JVL_2022-07-04_final
2022-07-11 11:25:16	ga_s2am_ard_3-2-1_51JVL_2022-07-11_final
2022-07-14 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-07-14_final
2022-07-21 11:25:15	ga_s2am_ard_3-2-1_51JVL_2022-07-21_final
2022-07-24 11:35:08	ga_s2am_ard_3-2-1_51JVL_2022-07-24_final
2022-07-31 11:25:13	ga_s2am_ard_3-2-1_51JVL_2022-07-31_final
2022-08-03 11:35:08	ga_s2am_ard_3-2-1_51JVL_2022-08-03_final
2022-08-10 11:25:15	ga_s2am_ard_3-2-1_51JVL_2022-08-10_final
2022-08-13 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-08-13_final
2022-08-20 11:25:16	ga_s2am_ard_3-2-1_51JVL_2022-08-20_final
2022-08-23 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-08-23_final
2022-08-30 11:25:16	ga_s2am_ard_3-2-1_51JVL_2022-08-30_final
2022-09-02 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-09-02_final.stac-item
2022-09-09 11:25:14	ga_s2am_ard_3-2-1_51JVL_2022-09-09_final.stac-item
2022-09-12 11:35:08	ga_s2am_ard_3-2-1_51JVL_2022-09-12_final.stac-item
2022-09-19 11:25:12	ga_s2am_ard_3-2-1_51JVL_2022-09-19_final.stac-item
2022-09-22 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-09-22_final.stac-item
2022-09-29 11:25:11	ga_s2am_ard_3-2-1_51JVL_2022-09-29_final.stac-item
2022-10-02 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-10-02_final.stac-item
2022-10-09 11:25:10	ga_s2am_ard_3-2-1_51JVL_2022-10-09_final.stac-item
2022-10-12 11:35:03	ga_s2am_ard_3-2-1_51JVL_2022-10-12_final.stac-item
2022-10-19 11:25:06	ga_s2am_ard_3-2-1_51JVL_2022-10-19_final.stac-item
2022-10-22 11:35:00	ga_s2am_ard_3-2-1_51JVL_2022-10-22_final.stac-item
2022-10-29 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-10-29_final.stac-item
2022-11-01 11:35:02	ga_s2am_ard_3-2-1_51JVL_2022-11-01_final.stac-item
2022-11-11 11:35:01	ga_s2am_ard_3-2-1_51JVL_2022-11-11_final.stac-item
2022-11-18 11:25:05	ga_s2am_ard_3-2-1_51JVL_2022-11-18_final.stac-item
2022-11-21 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-11-21_final.stac-item
2022-11-28 11:25:03	ga_s2am_ard_3-2-1_51JVL_2022-11-28_final.stac-item
2022-12-01 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-12-01_final.stac-item
2022-12-08 11:25:04	ga_s2am_ard_3-2-1_51JVL_2022-12-08_final.stac-item
2022-12-11 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-12-11_final.stac-item
2022-12-18 11:25:02	ga_s2am_ard_3-2-1_51JVL_2022-12-18_final.stac-item
2022-12-21 11:34:56	ga_s2am_ard_3-2-1_51JVL_2022-12-21_final.stac-item
2022-12-28 11:25:02	ga_s2am_ard_3-2-1_51JVL_2022-12-28_final.stac-item
2022-12-31 11:34:57	ga_s2am_ard_3-2-1_51JVL_2022-12-31_final.stac-item
2023-01-07 11:25:02	ga_s2am_ard_3-2-1_51JVL_2023-01-07_final.stac-item
2023-01-10 11:34:56	ga_s2am_ard_3-2-1_51JVL_2023-01-10_final.stac-item
2023-01-17 11:24:59	ga_s2am_ard_3-2-1_51JVL_2023-01-17_final.stac-item
2023-01-20 11:34:52	ga_s2am_ard_3-2-1_51JVL_2023-01-20_final.stac-item
2023-01-27 11:25:01	ga_s2am_ard_3-2-1_51JVL_2023-01-27_final.stac-item
2023-01-30 11:34:56	ga_s2am_ard_3-2-1_51JVL_2023-01-30_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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