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
2015-12-03 10:41:12	ga_s2am_ard_3-2-1_53LRE_2015-12-03_final.stac-item
2022-12-13 10:31:09	ga_s2am_ard_3-2-1_53LRE_2022-12-13_nrt.stac-item
2022-12-16 10:41:01	ga_s2am_ard_3-2-1_53LRE_2022-12-16_nrt.stac-item
2022-12-23 10:31:07	ga_s2am_ard_3-2-1_53LRE_2022-12-23_nrt.stac-item
2022-12-26 10:41:00	ga_s2am_ard_3-2-1_53LRE_2022-12-26_nrt.stac-item
2023-01-02 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-01-02_nrt.stac-item
2023-01-05 10:41:01	ga_s2am_ard_3-2-1_53LRE_2023-01-05_nrt.stac-item
2023-01-12 10:31:07	ga_s2am_ard_3-2-1_53LRE_2023-01-12_nrt.stac-item
2023-01-15 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-01-15_nrt.stac-item
2023-01-22 10:31:05	ga_s2am_ard_3-2-1_53LRE_2023-01-22_nrt.stac-item
2023-01-25 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-01-25_nrt.stac-item
2023-02-01 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-02-01_nrt.stac-item
2023-02-04 10:41:01	ga_s2am_ard_3-2-1_53LRE_2023-02-04_nrt.stac-item
2023-02-11 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-02-11_nrt.stac-item
2023-02-14 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-02-14_nrt.stac-item
2023-02-21 10:31:07	ga_s2am_ard_3-2-1_53LRE_2023-02-21_nrt.stac-item
2023-02-24 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-02-24_nrt.stac-item
2023-03-03 10:31:06	ga_s2am_ard_3-2-1_53LRE_2023-03-03_nrt.stac-item
2023-03-06 10:40:58	ga_s2am_ard_3-2-1_53LRE_2023-03-06_nrt.stac-item
2023-03-13 10:31:06	ga_s2am_ard_3-2-1_53LRE_2023-03-13_nrt.stac-item
2023-03-16 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-03-16_nrt.stac-item
2023-03-23 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-03-23_nrt.stac-item
2023-03-26 10:41:00	ga_s2am_ard_3-2-1_53LRE_2023-03-26_nrt.stac-item
2023-04-02 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-04-02_nrt.stac-item
2023-04-05 10:41:01	ga_s2am_ard_3-2-1_53LRE_2023-04-05_nrt.stac-item
2023-04-12 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-04-12_nrt.stac-item
2023-04-15 10:41:02	ga_s2am_ard_3-2-1_53LRE_2023-04-15_nrt.stac-item
2023-04-22 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-04-22_nrt.stac-item
2023-04-25 10:41:02	ga_s2am_ard_3-2-1_53LRE_2023-04-25_nrt.stac-item
2023-05-02 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-05-02_nrt.stac-item
2023-05-05 10:41:02	ga_s2am_ard_3-2-1_53LRE_2023-05-05_nrt.stac-item
2023-05-12 10:31:08	ga_s2am_ard_3-2-1_53LRE_2023-05-12_nrt.stac-item
2023-05-15 10:41:02	ga_s2am_ard_3-2-1_53LRE_2023-05-15_nrt.stac-item
2023-05-22 10:31:12	ga_s2am_ard_3-2-1_53LRE_2023-05-22_nrt.stac-item
2023-05-25 10:41:05	ga_s2am_ard_3-2-1_53LRE_2023-05-25_nrt.stac-item
2023-06-01 10:31:13	ga_s2am_ard_3-2-1_53LRE_2023-06-01_nrt.stac-item
2023-06-04 10:40:57	ga_s2am_ard_3-2-1_53LRE_2023-06-04_nrt.stac-item
2023-06-04 10:41:06	ga_s2am_ard_3-2-1_53LRE_2023-06-04_nrt.stac-item
2023-06-11 10:31:13	ga_s2am_ard_3-2-1_53LRE_2023-06-11_nrt.stac-item
2023-06-14 10:40:58	ga_s2am_ard_3-2-1_53LRE_2023-06-14_nrt.stac-item
2023-06-14 10:41:06	ga_s2am_ard_3-2-1_53LRE_2023-06-14_nrt.stac-item
2023-06-21 10:31:13	ga_s2am_ard_3-2-1_53LRE_2023-06-21_nrt.stac-item
2023-06-24 10:40:57	ga_s2am_ard_3-2-1_53LRE_2023-06-24_nrt.stac-item
2023-06-24 10:41:05	ga_s2am_ard_3-2-1_53LRE_2023-06-24_nrt.stac-item
2023-07-01 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-07-01_nrt.stac-item
2023-07-04 10:40:58	ga_s2am_ard_3-2-1_53LRE_2023-07-04_nrt.stac-item
2023-07-04 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-07-04_nrt.stac-item
2023-07-11 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-07-11_nrt.stac-item
2023-07-14 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-07-14_nrt.stac-item
2023-07-21 10:31:13	ga_s2am_ard_3-2-1_53LRE_2023-07-21_nrt.stac-item
2023-07-24 10:41:06	ga_s2am_ard_3-2-1_53LRE_2023-07-24_nrt.stac-item
2023-07-31 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-07-31_nrt.stac-item
2023-08-03 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-08-03_nrt.stac-item
2023-08-10 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-08-10_nrt.stac-item
2023-08-13 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-08-13_nrt.stac-item
2023-08-20 10:31:15	ga_s2am_ard_3-2-1_53LRE_2023-08-20_nrt.stac-item
2023-08-23 10:41:08	ga_s2am_ard_3-2-1_53LRE_2023-08-23_nrt.stac-item
2023-08-30 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-08-30_nrt.stac-item
2023-09-02 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-09-02_nrt.stac-item
2023-09-09 10:31:14	ga_s2am_ard_3-2-1_53LRE_2023-09-09_nrt.stac-item
2023-09-12 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-09-12_nrt.stac-item
2023-09-19 10:31:12	ga_s2am_ard_3-2-1_53LRE_2023-09-19_nrt.stac-item
2023-09-22 10:41:03	ga_s2am_ard_3-2-1_53LRE_2023-09-22_nrt.stac-item
2023-09-29 10:31:11	ga_s2am_ard_3-2-1_53LRE_2023-09-29_nrt.stac-item
2023-10-02 10:41:04	ga_s2am_ard_3-2-1_53LRE_2023-10-02_nrt.stac-item
2023-10-09 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-10-09_nrt.stac-item
2023-10-12 10:41:00	ga_s2am_ard_3-2-1_53LRE_2023-10-12_nrt.stac-item
2023-10-19 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-10-19_nrt.stac-item
2023-10-22 10:41:02	ga_s2am_ard_3-2-1_53LRE_2023-10-22_nrt.stac-item
2023-10-29 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-10-29_nrt.stac-item
2023-11-01 10:41:00	ga_s2am_ard_3-2-1_53LRE_2023-11-01_nrt.stac-item
2023-11-01 10:41:07	ga_s2am_ard_3-2-1_53LRE_2023-11-01_nrt.stac-item
2023-11-08 10:31:09	ga_s2am_ard_3-2-1_53LRE_2023-11-08_nrt.stac-item
2023-11-11 10:41:01	ga_s2am_ard_3-2-1_53LRE_2023-11-11_nrt.stac-item
2023-11-18 10:31:07	ga_s2am_ard_3-2-1_53LRE_2023-11-18_nrt.stac-item
2023-11-21 10:40:58	ga_s2am_ard_3-2-1_53LRE_2023-11-21_nrt.stac-item
2023-12-01 10:40:53	ga_s2am_ard_3-2-1_53LRE_2023-12-01_nrt.stac-item
2023-12-08 10:31:04	ga_s2am_ard_3-2-1_53LRE_2023-12-08_nrt.stac-item
2023-12-11 10:40:57	ga_s2am_ard_3-2-1_53LRE_2023-12-11_nrt.stac-item
2023-12-18 10:31:05	ga_s2am_ard_3-2-1_53LRE_2023-12-18_nrt.stac-item
2023-12-21 10:40:58	ga_s2am_ard_3-2-1_53LRE_2023-12-21_nrt.stac-item
2023-12-28 10:31:06	ga_s2am_ard_3-2-1_53LRE_2023-12-28_nrt.stac-item
2023-12-31 10:40:59	ga_s2am_ard_3-2-1_53LRE_2023-12-31_nrt.stac-item
2024-01-07 10:31:05	ga_s2am_ard_3-2-1_53LRE_2024-01-07_nrt.stac-item
2024-01-10 10:40:57	ga_s2am_ard_3-2-1_53LRE_2024-01-10_nrt.stac-item
2024-01-17 10:31:01	ga_s2am_ard_3-2-1_53LRE_2024-01-17_nrt.stac-item
2024-01-20 10:40:53	ga_s2am_ard_3-2-1_53LRE_2024-01-20_nrt.stac-item
2024-01-27 10:31:04	ga_s2am_ard_3-2-1_53LRE_2024-01-27_nrt.stac-item
2024-01-30 10:40:57	ga_s2am_ard_3-2-1_53LRE_2024-01-30_nrt.stac-item
2024-02-06 10:31:05	ga_s2am_ard_3-2-1_53LRE_2024-02-06_nrt.stac-item
2024-02-09 10:40:58	ga_s2am_ard_3-2-1_53LRE_2024-02-09_nrt.stac-item
2024-02-16 10:31:07	ga_s2am_ard_3-2-1_53LRE_2024-02-16_nrt.stac-item
2024-02-19 10:40:51	ga_s2am_ard_3-2-1_53LRE_2024-02-19_nrt.stac-item
2024-02-19 10:41:00	ga_s2am_ard_3-2-1_53LRE_2024-02-19_nrt.stac-item
2024-02-29 10:40:53	ga_s2am_ard_3-2-1_53LRE_2024-02-29_nrt.stac-item
2024-02-29 10:41:02	ga_s2am_ard_3-2-1_53LRE_2024-02-29_nrt.stac-item
2024-03-07 10:31:10	ga_s2am_ard_3-2-1_53LRE_2024-03-07_nrt.stac-item
2024-03-10 10:41:02	ga_s2am_ard_3-2-1_53LRE_2024-03-10_nrt.stac-item
2024-03-27 10:31:10	ga_s2am_ard_3-2-1_53LRE_2024-03-27_nrt.stac-item
2024-03-30 10:41:01	ga_s2am_ard_3-2-1_53LRE_2024-03-30_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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