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

87 results

Time (local)	Label
2022-12-22 09:24:32	ga_s2am_ard_3-2-1_56JPP_2022-12-21_nrt.stac-item
2023-01-01 09:24:33	ga_s2am_ard_3-2-1_56JPP_2022-12-31_nrt.stac-item
2023-01-08 09:14:42	ga_s2am_ard_3-2-1_56JPP_2023-01-07_nrt.stac-item
2023-01-11 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-01-10_nrt.stac-item
2023-01-21 09:24:30	ga_s2am_ard_3-2-1_56JPP_2023-01-20_nrt.stac-item
2023-01-28 09:14:41	ga_s2am_ard_3-2-1_56JPP_2023-01-27_nrt.stac-item
2023-01-31 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-01-30_nrt.stac-item
2023-02-07 09:14:42	ga_s2am_ard_3-2-1_56JPP_2023-02-06_nrt.stac-item
2023-02-10 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-02-09_nrt.stac-item
2023-03-02 09:24:32	ga_s2am_ard_3-2-1_56JPP_2023-03-01_nrt.stac-item
2023-03-12 09:24:30	ga_s2am_ard_3-2-1_56JPP_2023-03-11_nrt.stac-item
2023-03-19 09:14:41	ga_s2am_ard_3-2-1_56JPP_2023-03-18_nrt.stac-item
2023-03-22 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-03-21_nrt.stac-item
2023-03-29 09:14:41	ga_s2am_ard_3-2-1_56JPP_2023-03-28_nrt.stac-item
2023-04-01 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-03-31_nrt.stac-item
2023-04-08 09:14:43	ga_s2am_ard_3-2-1_56JPP_2023-04-07_nrt.stac-item
2023-04-11 09:24:35	ga_s2am_ard_3-2-1_56JPP_2023-04-10_nrt.stac-item
2023-04-18 09:14:42	ga_s2am_ard_3-2-1_56JPP_2023-04-17_nrt.stac-item
2023-04-21 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-04-20_nrt.stac-item
2023-04-28 09:14:43	ga_s2am_ard_3-2-1_56JPP_2023-04-27_nrt.stac-item
2023-05-01 09:24:27	ga_s2am_ard_3-2-1_56JPP_2023-04-30_nrt.stac-item
2023-05-08 09:14:43	ga_s2am_ard_3-2-1_56JPP_2023-05-07_nrt.stac-item
2023-05-11 09:24:34	ga_s2am_ard_3-2-1_56JPP_2023-05-10_nrt.stac-item
2023-05-18 09:14:45	ga_s2am_ard_3-2-1_56JPP_2023-05-17_nrt.stac-item
2023-05-21 09:24:37	ga_s2am_ard_3-2-1_56JPP_2023-05-20_nrt.stac-item
2023-05-28 09:14:46	ga_s2am_ard_3-2-1_56JPP_2023-05-27_nrt.stac-item
2023-05-31 09:24:38	ga_s2am_ard_3-2-1_56JPP_2023-05-30_nrt.stac-item
2023-06-07 09:14:46	ga_s2am_ard_3-2-1_56JPP_2023-06-06_nrt.stac-item
2023-06-10 09:24:38	ga_s2am_ard_3-2-1_56JPP_2023-06-09_nrt.stac-item
2023-06-17 09:14:47	ga_s2am_ard_3-2-1_56JPP_2023-06-16_nrt.stac-item
2023-06-20 09:24:38	ga_s2am_ard_3-2-1_56JPP_2023-06-19_nrt.stac-item
2023-06-27 09:14:47	ga_s2am_ard_3-2-1_56JPP_2023-06-26_nrt.stac-item
2023-06-30 09:24:39	ga_s2am_ard_3-2-1_56JPP_2023-06-29_nrt.stac-item
2023-07-07 09:14:48	ga_s2am_ard_3-2-1_56JPP_2023-07-06_nrt.stac-item
2023-07-10 09:24:40	ga_s2am_ard_3-2-1_56JPP_2023-07-09_nrt.stac-item
2023-07-17 09:14:48	ga_s2am_ard_3-2-1_56JPP_2023-07-16_nrt.stac-item
2023-07-20 09:24:38	ga_s2am_ard_3-2-1_56JPP_2023-07-19_nrt.stac-item
2023-07-27 09:14:48	ga_s2am_ard_3-2-1_56JPP_2023-07-26_nrt.stac-item
2023-07-30 09:24:40	ga_s2am_ard_3-2-1_56JPP_2023-07-29_nrt.stac-item
2023-08-06 09:14:48	ga_s2am_ard_3-2-1_56JPP_2023-08-05_nrt.stac-item
2023-08-09 09:24:39	ga_s2am_ard_3-2-1_56JPP_2023-08-08_nrt.stac-item
2023-08-16 09:14:49	ga_s2am_ard_3-2-1_56JPP_2023-08-15_nrt.stac-item
2023-08-19 09:24:31	ga_s2am_ard_3-2-1_56JPP_2023-08-18_nrt.stac-item
2023-08-19 09:24:40	ga_s2am_ard_3-2-1_56JPP_2023-08-18_nrt.stac-item
2023-08-26 09:14:49	ga_s2am_ard_3-2-1_56JPP_2023-08-25_nrt.stac-item
2023-08-29 09:24:40	ga_s2am_ard_3-2-1_56JPP_2023-08-28_nrt.stac-item
2023-09-05 09:14:48	ga_s2am_ard_3-2-1_56JPP_2023-09-04_nrt.stac-item
2023-09-08 09:24:40	ga_s2am_ard_3-2-1_56JPP_2023-09-07_nrt.stac-item
2023-09-15 09:14:47	ga_s2am_ard_3-2-1_56JPP_2023-09-14_nrt.stac-item
2023-09-18 09:24:38	ga_s2am_ard_3-2-1_56JPP_2023-09-17_nrt.stac-item
2023-09-28 09:24:37	ga_s2am_ard_3-2-1_56JPP_2023-09-27_nrt.stac-item
2023-10-05 09:14:44	ga_s2am_ard_3-2-1_56JPP_2023-10-04_nrt.stac-item
2023-10-08 09:24:35	ga_s2am_ard_3-2-1_56JPP_2023-10-07_nrt.stac-item
2023-10-18 09:24:34	ga_s2am_ard_3-2-1_56JPP_2023-10-17_nrt.stac-item
2023-10-25 09:14:43	ga_s2am_ard_3-2-1_56JPP_2023-10-24_nrt.stac-item
2023-10-28 09:24:34	ga_s2am_ard_3-2-1_56JPP_2023-10-27_nrt.stac-item
2023-11-14 09:14:42	ga_s2am_ard_3-2-1_56JPP_2023-11-13_nrt.stac-item
2023-11-17 09:24:33	ga_s2am_ard_3-2-1_56JPP_2023-11-16_nrt.stac-item
2023-11-27 09:24:28	ga_s2am_ard_3-2-1_56JPP_2023-11-26_nrt.stac-item
2023-12-07 09:24:28	ga_s2am_ard_3-2-1_56JPP_2023-12-06_nrt.stac-item
2023-12-14 09:14:39	ga_s2am_ard_3-2-1_56JPP_2023-12-13_nrt.stac-item
2023-12-17 09:24:31	ga_s2am_ard_3-2-1_56JPP_2023-12-16_nrt.stac-item
2023-12-24 09:14:40	ga_s2am_ard_3-2-1_56JPP_2023-12-23_nrt.stac-item
2023-12-27 09:24:31	ga_s2am_ard_3-2-1_56JPP_2023-12-26_nrt.stac-item
2024-01-03 09:14:40	ga_s2am_ard_3-2-1_56JPP_2024-01-02_nrt.stac-item
2024-01-06 09:24:31	ga_s2am_ard_3-2-1_56JPP_2024-01-05_nrt.stac-item
2024-01-16 09:24:27	ga_s2am_ard_3-2-1_56JPP_2024-01-15_nrt.stac-item
2024-01-26 09:24:29	ga_s2am_ard_3-2-1_56JPP_2024-01-25_nrt.stac-item
2024-02-05 09:24:30	ga_s2am_ard_3-2-1_56JPP_2024-02-04_nrt.stac-item
2024-02-15 09:24:32	ga_s2am_ard_3-2-1_56JPP_2024-02-14_nrt.stac-item
2024-02-25 09:24:33	ga_s2am_ard_3-2-1_56JPP_2024-02-24_nrt.stac-item
2024-03-03 09:14:43	ga_s2am_ard_3-2-1_56JPP_2024-03-02_nrt.stac-item
2024-03-06 09:24:35	ga_s2am_ard_3-2-1_56JPP_2024-03-05_nrt.stac-item
2024-03-13 09:14:43	ga_s2am_ard_3-2-1_56JPP_2024-03-12_nrt.stac-item
2024-03-16 09:24:34	ga_s2am_ard_3-2-1_56JPP_2024-03-15_nrt.stac-item
2024-03-23 09:14:44	ga_s2am_ard_3-2-1_56JPP_2024-03-22_nrt.stac-item
2024-03-26 09:24:35	ga_s2am_ard_3-2-1_56JPP_2024-03-25_nrt.stac-item
2024-04-05 09:24:32	ga_s2am_ard_3-2-1_56JPP_2024-04-04_nrt.stac-item
2024-04-12 09:14:44	ga_s2am_ard_3-2-1_56JPP_2024-04-11_nrt.stac-item
2024-04-15 09:24:37	ga_s2am_ard_3-2-1_56JPP_2024-04-14_nrt.stac-item
2024-04-22 09:14:46	ga_s2am_ard_3-2-1_56JPP_2024-04-21_nrt.stac-item
2024-04-25 09:24:37	ga_s2am_ard_3-2-1_56JPP_2024-04-24_nrt.stac-item
2024-05-02 09:14:46	ga_s2am_ard_3-2-1_56JPP_2024-05-01_nrt.stac-item
2024-05-05 09:24:37	ga_s2am_ard_3-2-1_56JPP_2024-05-04_nrt.stac-item
2024-05-12 09:14:46	ga_s2am_ard_3-2-1_56JPP_2024-05-11_nrt.stac-item
2024-05-15 09:24:37	ga_s2am_ard_3-2-1_56JPP_2024-05-14_nrt.stac-item
2024-05-25 09:24:34	ga_s2am_ard_3-2-1_56JPP_2024-05-24_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

Other products

All years