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
2016-12-25 10:04:36	ga_s2am_ard_3-2-1_54HWF_2016-12-25_final
2017-02-23 10:06:24	ga_s2am_ard_3-2-1_54HWF_2017-02-23_final
2017-03-15 10:06:32	ga_s2am_ard_3-2-1_54HWF_2017-03-15_final
2017-04-04 10:06:38	ga_s2am_ard_3-2-1_54HWF_2017-04-04_final
2017-05-14 10:06:44	ga_s2am_ard_3-2-1_54HWF_2017-05-14_final
2017-06-23 10:06:40	ga_s2am_ard_3-2-1_54HWF_2017-06-23_final
2017-07-13 10:06:42	ga_s2am_ard_3-2-1_54HWF_2017-07-13_final
2017-08-02 10:03:31	ga_s2am_ard_3-2-1_54HWF_2017-08-02_final
2017-08-22 10:03:30	ga_s2am_ard_3-2-1_54HWF_2017-08-22_final
2017-10-01 10:03:26	ga_s2am_ard_3-2-1_54HWF_2017-10-01_final
2022-01-08 10:06:59	ga_s2am_ard_3-2-1_54HWF_2022-01-08_final
2022-01-18 10:06:57	ga_s2am_ard_3-2-1_54HWF_2022-01-18_final
2022-01-28 10:06:57	ga_s2am_ard_3-2-1_54HWF_2022-01-28_final
2022-02-07 10:06:57	ga_s2am_ard_3-2-1_54HWF_2022-02-07_final
2022-02-17 10:06:58	ga_s2am_ard_3-2-1_54HWF_2022-02-17_final
2022-02-27 10:07:00	ga_s2am_ard_3-2-1_54HWF_2022-02-27_final
2022-03-09 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-03-09_final
2022-03-19 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-03-19_final
2022-03-29 10:07:00	ga_s2am_ard_3-2-1_54HWF_2022-03-29_final
2022-04-08 10:06:58	ga_s2am_ard_3-2-1_54HWF_2022-04-08_final
2022-04-18 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-04-18_final
2022-04-28 10:07:02	ga_s2am_ard_3-2-1_54HWF_2022-04-28_final
2022-05-08 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-05-08_final
2022-05-18 10:07:03	ga_s2am_ard_3-2-1_54HWF_2022-05-18_final
2022-05-28 10:07:05	ga_s2am_ard_3-2-1_54HWF_2022-05-28_final
2022-06-07 10:07:05	ga_s2am_ard_3-2-1_54HWF_2022-06-07_final
2022-06-17 10:07:08	ga_s2am_ard_3-2-1_54HWF_2022-06-17_final
2022-06-27 10:07:10	ga_s2am_ard_3-2-1_54HWF_2022-06-27_final
2022-07-07 10:07:10	ga_s2am_ard_3-2-1_54HWF_2022-07-07_final
2022-07-17 10:07:09	ga_s2am_ard_3-2-1_54HWF_2022-07-17_final
2022-07-27 10:07:07	ga_s2am_ard_3-2-1_54HWF_2022-07-27_final
2022-08-06 10:07:08	ga_s2am_ard_3-2-1_54HWF_2022-08-06_final
2022-08-16 10:07:10	ga_s2am_ard_3-2-1_54HWF_2022-08-16_final
2022-08-26 10:07:10	ga_s2am_ard_3-2-1_54HWF_2022-08-26_final
2022-09-05 10:07:09	ga_s2am_ard_3-2-1_54HWF_2022-09-05_final.stac-item
2022-09-15 10:07:07	ga_s2am_ard_3-2-1_54HWF_2022-09-15_final.stac-item
2022-09-25 10:07:04	ga_s2am_ard_3-2-1_54HWF_2022-09-25_final.stac-item
2022-10-05 10:07:04	ga_s2am_ard_3-2-1_54HWF_2022-10-05_final.stac-item
2022-10-15 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-10-15_final.stac-item
2022-10-25 10:07:00	ga_s2am_ard_3-2-1_54HWF_2022-10-25_final.stac-item
2022-11-04 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-11-04_final.stac-item
2022-11-14 10:07:00	ga_s2am_ard_3-2-1_54HWF_2022-11-14_final.stac-item
2022-11-24 10:06:56	ga_s2am_ard_3-2-1_54HWF_2022-11-24_final.stac-item
2022-12-14 10:06:57	ga_s2am_ard_3-2-1_54HWF_2022-12-14_final.stac-item
2023-07-05 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-07-05_final.stac-item
2023-07-15 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-07-15_final.stac-item
2023-07-25 10:14:29	ga_s2am_ard_3-2-1_54JWR_2023-07-25_final.stac-item
2023-07-25 10:14:36	ga_s2am_ard_3-2-1_54JWR_2023-07-25_final.stac-item
2023-08-04 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-08-04_final.stac-item
2023-08-14 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-08-14_final.stac-item
2023-08-24 10:14:34	ga_s2am_ard_3-2-1_54JWR_2023-08-24_final.stac-item
2023-09-03 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-09-03_final.stac-item
2023-09-13 10:14:33	ga_s2am_ard_3-2-1_54JWR_2023-09-13_final.stac-item
2023-09-23 10:14:30	ga_s2am_ard_3-2-1_54JWR_2023-09-23_final.stac-item
2023-10-03 10:14:30	ga_s2am_ard_3-2-1_54JWR_2023-10-03_final.stac-item
2023-10-13 10:14:26	ga_s2am_ard_3-2-1_54JWR_2023-10-13_final.stac-item
2023-10-23 10:14:28	ga_s2am_ard_3-2-1_54JWR_2023-10-23_final.stac-item
2023-10-30 10:06:57	ga_s2am_ard_3-2-1_54HWF_2023-10-30_final.stac-item
2023-11-02 10:14:27	ga_s2am_ard_3-2-1_54JWR_2023-11-02_final.stac-item
2023-11-09 10:06:57	ga_s2am_ard_3-2-1_54HWF_2023-11-09_final.stac-item
2023-11-12 10:14:27	ga_s2am_ard_3-2-1_54JWR_2023-11-12_final.stac-item
2023-11-19 10:06:55	ga_s2am_ard_3-2-1_54HWF_2023-11-19_final.stac-item
2023-11-22 10:14:24	ga_s2am_ard_3-2-1_54JWR_2023-11-22_final.stac-item
2023-11-29 10:06:49	ga_s2am_ard_3-2-1_54HWF_2023-11-29_final.stac-item
2023-12-02 10:14:20	ga_s2am_ard_3-2-1_54JWR_2023-12-02_final.stac-item
2023-12-09 10:06:52	ga_s2am_ard_3-2-1_54HWF_2023-12-09_final.stac-item
2023-12-12 10:14:23	ga_s2am_ard_3-2-1_54JWR_2023-12-12_final.stac-item
2023-12-19 10:06:53	ga_s2am_ard_3-2-1_54HWF_2023-12-19_final.stac-item
2023-12-22 10:14:24	ga_s2am_ard_3-2-1_54JWR_2023-12-22_final.stac-item
2023-12-29 10:06:54	ga_s2am_ard_3-2-1_54HWF_2023-12-29_final.stac-item
2024-01-01 10:14:25	ga_s2am_ard_3-2-1_54JWR_2024-01-01_final.stac-item
2024-01-08 10:06:53	ga_s2am_ard_3-2-1_54HWF_2024-01-08_final.stac-item
2024-01-11 10:14:23	ga_s2am_ard_3-2-1_54JWR_2024-01-11_final.stac-item
2024-01-18 10:06:48	ga_s2am_ard_3-2-1_54HWF_2024-01-18_final.stac-item
2024-01-21 10:14:20	ga_s2am_ard_3-2-1_54JWR_2024-01-21_final.stac-item
2024-01-28 10:06:52	ga_s2am_ard_3-2-1_54HWF_2024-01-28_final.stac-item
2024-01-31 10:14:23	ga_s2am_ard_3-2-1_54JWR_2024-01-31_final.stac-item
2024-02-07 10:06:53	ga_s2am_ard_3-2-1_54HWF_2024-02-07_final.stac-item
2024-02-10 10:14:24	ga_s2am_ard_3-2-1_54JWR_2024-02-10_final.stac-item
2024-02-17 10:06:55	ga_s2am_ard_3-2-1_54HWF_2024-02-17_final.stac-item
2024-02-20 10:14:26	ga_s2am_ard_3-2-1_54JWR_2024-02-20_final.stac-item
2024-02-27 10:06:56	ga_s2am_ard_3-2-1_54HWF_2024-02-27_final.stac-item
2024-03-01 10:14:28	ga_s2am_ard_3-2-1_54JWR_2024-03-01_final.stac-item
2024-03-08 10:06:58	ga_s2am_ard_3-2-1_54HWF_2024-03-08_final.stac-item
2024-03-11 10:14:28	ga_s2am_ard_3-2-1_54JWR_2024-03-11_final.stac-item
2024-03-18 10:06:58	ga_s2am_ard_3-2-1_54HWF_2024-03-18_final.stac-item
2024-03-21 10:14:29	ga_s2am_ard_3-2-1_54JWR_2024-03-21_final.stac-item
2024-03-28 10:06:57	ga_s2am_ard_3-2-1_54HWF_2024-03-28_final.stac-item
2024-03-31 10:14:27	ga_s2am_ard_3-2-1_54JWR_2024-03-31_final.stac-item
2024-04-07 10:06:56	ga_s2am_ard_3-2-1_54HWF_2024-04-07_final.stac-item
2024-04-10 10:14:28	ga_s2am_ard_3-2-1_54JWR_2024-04-10_final.stac-item
2024-04-17 10:07:00	ga_s2am_ard_3-2-1_54HWF_2024-04-17_final.stac-item
2024-04-20 10:14:31	ga_s2am_ard_3-2-1_54JWR_2024-04-20_final.stac-item
2024-04-27 10:06:59	ga_s2am_ard_3-2-1_54HWF_2024-04-27_final.stac-item
2024-04-30 10:14:31	ga_s2am_ard_3-2-1_54JWR_2024-04-30_final.stac-item
2024-05-07 10:07:00	ga_s2am_ard_3-2-1_54HWF_2024-05-07_final.stac-item
2024-05-10 10:14:31	ga_s2am_ard_3-2-1_54JWR_2024-05-10_final.stac-item
2024-05-17 10:06:59	ga_s2am_ard_3-2-1_54HWF_2024-05-17_final.stac-item
2024-05-20 10:14:29	ga_s2am_ard_3-2-1_54JWR_2024-05-20_final.stac-item
2024-05-27 10:06:58	ga_s2am_ard_3-2-1_54HWF_2024-05-27_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

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