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
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51KTQ_2018-08-17_final
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_51KTQ_2018-09-06_final
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_51KTQ_2018-09-26_final
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_51KTQ_2018-10-06_final
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_51KTQ_2018-10-16_final
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KTQ_2018-11-05_final
2018-11-25 11:43:54	ga_s2am_ard_3-2-1_51KTQ_2018-11-25_final
2018-12-15 11:43:53	ga_s2am_ard_3-2-1_51KTQ_2018-12-15_final
2018-12-25 11:43:54	ga_s2am_ard_3-2-1_51KTQ_2018-12-25_final
2019-01-14 11:43:57	ga_s2am_ard_3-2-1_51KTQ_2019-01-14_final
2019-01-24 11:43:58	ga_s2am_ard_3-2-1_51KTQ_2019-01-24_final
2019-02-03 11:43:58	ga_s2am_ard_3-2-1_51KTQ_2019-02-03_final
2019-02-13 11:43:58	ga_s2am_ard_3-2-1_51KTQ_2019-02-13_final
2019-02-23 11:43:57	ga_s2am_ard_3-2-1_51KTQ_2019-02-23_final
2019-03-05 11:43:56	ga_s2am_ard_3-2-1_51KTQ_2019-03-05_final
2019-03-15 11:43:58	ga_s2am_ard_3-2-1_51KTQ_2019-03-15_final
2019-03-25 11:44:00	ga_s2am_ard_3-2-1_51KTQ_2019-03-25_final
2019-04-04 11:44:02	ga_s2am_ard_3-2-1_51KTQ_2019-04-04_final
2019-04-14 11:44:04	ga_s2am_ard_3-2-1_51KTQ_2019-04-14_final
2019-04-24 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-04-24_final
2019-05-04 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-05-04_final
2019-05-14 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-05-14_final
2019-05-24 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-05-24_final
2019-06-03 11:44:04	ga_s2am_ard_3-2-1_51KTQ_2019-06-03_final
2019-06-13 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-06-13_final
2019-06-23 11:44:06	ga_s2am_ard_3-2-1_51KTQ_2019-06-23_final
2019-07-03 11:44:06	ga_s2am_ard_3-2-1_51KTQ_2019-07-03_final
2019-07-13 11:44:07	ga_s2am_ard_3-2-1_51KTQ_2019-07-13_final
2019-07-23 11:44:07	ga_s2am_ard_3-2-1_51KTQ_2019-07-23_final
2019-08-02 11:44:06	ga_s2am_ard_3-2-1_51KTQ_2019-08-02_final
2019-09-01 11:44:02	ga_s2am_ard_3-2-1_51KTQ_2019-09-01_final
2019-09-11 11:44:00	ga_s2am_ard_3-2-1_51KTQ_2019-09-11_final
2019-09-21 11:44:02	ga_s2am_ard_3-2-1_51KTQ_2019-09-21_final
2019-10-11 11:44:04	ga_s2am_ard_3-2-1_51KTQ_2019-10-11_final
2019-10-21 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-10-21_final
2019-10-31 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-10-31_final
2019-11-10 11:44:04	ga_s2am_ard_3-2-1_51KTQ_2019-11-10_final
2019-11-20 11:44:03	ga_s2am_ard_3-2-1_51KTQ_2019-11-20_final
2019-11-30 11:44:01	ga_s2am_ard_3-2-1_51KTQ_2019-11-30_final
2019-12-10 11:43:58	ga_s2am_ard_3-2-1_51KTQ_2019-12-10_final
2021-05-03 11:44:14	ga_s2am_ard_3-2-1_51KTP_2021-05-03_final
2021-05-13 11:44:16	ga_s2am_ard_3-2-1_51KTP_2021-05-13_final
2021-05-23 11:44:17	ga_s2am_ard_3-2-1_51KTP_2021-05-23_final
2021-06-02 11:44:17	ga_s2am_ard_3-2-1_51KTP_2021-06-02_final
2021-06-22 11:44:17	ga_s2am_ard_3-2-1_51KTP_2021-06-22_final
2021-07-02 11:44:18	ga_s2am_ard_3-2-1_51KTP_2021-07-02_final
2021-07-12 11:44:19	ga_s2am_ard_3-2-1_51KTP_2021-07-12_final
2021-07-22 11:44:20	ga_s2am_ard_3-2-1_51KTP_2021-07-22_final
2021-08-01 11:44:19	ga_s2am_ard_3-2-1_51KTP_2021-08-01_final
2021-08-11 11:44:19	ga_s2am_ard_3-2-1_51KTP_2021-08-11_final
2021-08-21 11:44:18	ga_s2am_ard_3-2-1_51KTP_2021-08-21_final
2021-08-31 11:44:17	ga_s2am_ard_3-2-1_51KTP_2021-08-31_final
2021-09-10 11:44:16	ga_s2am_ard_3-2-1_51KTP_2021-09-10_final
2021-09-20 11:44:19	ga_s2am_ard_3-2-1_51KTP_2021-09-20_final
2021-09-30 11:44:20	ga_s2am_ard_3-2-1_51KTP_2021-09-30_final
2021-10-10 11:44:21	ga_s2am_ard_3-2-1_51KTP_2021-10-10_final
2021-10-20 11:44:21	ga_s2am_ard_3-2-1_51KTP_2021-10-20_final
2021-10-30 11:44:21	ga_s2am_ard_3-2-1_51KTP_2021-10-30_final
2021-11-19 11:44:16	ga_s2am_ard_3-2-1_51KTP_2021-11-19_final
2021-11-29 11:44:16	ga_s2am_ard_3-2-1_51KTP_2021-11-29_final
2021-12-09 11:44:15	ga_s2am_ard_3-2-1_51KTP_2021-12-09_final
2021-12-19 11:44:17	ga_s2am_ard_3-2-1_51KTP_2021-12-19_final
2021-12-29 11:44:18	ga_s2am_ard_3-2-1_51KTP_2021-12-29_final
2022-01-08 11:44:18	ga_s2am_ard_3-2-1_51KTP_2022-01-08_final
2022-01-18 11:44:16	ga_s2am_ard_3-2-1_51KTP_2022-01-18_final
2022-01-28 11:44:16	ga_s2am_ard_3-2-1_51KTP_2022-01-28_final
2022-02-07 11:44:16	ga_s2am_ard_3-2-1_51KTP_2022-02-07_final
2022-02-17 11:44:17	ga_s2am_ard_3-2-1_51KTP_2022-02-17_final
2022-02-27 11:44:19	ga_s2am_ard_3-2-1_51KTP_2022-02-27_final
2022-03-09 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-03-09_final
2022-03-19 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-03-19_final
2022-03-29 11:44:19	ga_s2am_ard_3-2-1_51KTP_2022-03-29_final
2022-04-08 11:44:17	ga_s2am_ard_3-2-1_51KTP_2022-04-08_final
2022-04-18 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-04-18_final
2022-04-28 11:44:21	ga_s2am_ard_3-2-1_51KTP_2022-04-28_final
2022-05-08 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-05-08_final
2022-05-18 11:44:22	ga_s2am_ard_3-2-1_51KTP_2022-05-18_final
2022-05-28 11:44:24	ga_s2am_ard_3-2-1_51KTP_2022-05-28_final
2022-06-07 11:44:24	ga_s2am_ard_3-2-1_51KTP_2022-06-07_final
2022-06-17 11:44:27	ga_s2am_ard_3-2-1_51KTP_2022-06-17_final
2022-06-27 11:44:29	ga_s2am_ard_3-2-1_51KTP_2022-06-27_final
2022-07-07 11:44:29	ga_s2am_ard_3-2-1_51KTP_2022-07-07_final
2022-07-17 11:44:28	ga_s2am_ard_3-2-1_51KTP_2022-07-17_final
2022-07-27 11:44:26	ga_s2am_ard_3-2-1_51KTP_2022-07-27_final
2022-08-06 11:44:27	ga_s2am_ard_3-2-1_51KTP_2022-08-06_final
2022-08-16 11:44:29	ga_s2am_ard_3-2-1_51KTP_2022-08-16_final
2022-08-26 11:44:29	ga_s2am_ard_3-2-1_51KTP_2022-08-26_final
2022-09-05 11:44:28	ga_s2am_ard_3-2-1_51KTP_2022-09-05_final.stac-item
2022-09-15 11:44:26	ga_s2am_ard_3-2-1_51KTP_2022-09-15_final.stac-item
2022-09-25 11:44:23	ga_s2am_ard_3-2-1_51KTP_2022-09-25_final.stac-item
2022-10-05 11:44:23	ga_s2am_ard_3-2-1_51KTP_2022-10-05_final.stac-item
2022-10-15 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-10-15_final.stac-item
2022-10-25 11:44:19	ga_s2am_ard_3-2-1_51KTP_2022-10-25_final.stac-item
2022-11-04 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-11-04_final.stac-item
2022-11-14 11:44:19	ga_s2am_ard_3-2-1_51KTP_2022-11-14_final.stac-item
2022-11-24 11:44:15	ga_s2am_ard_3-2-1_51KTP_2022-11-24_final.stac-item
2022-12-04 11:44:17	ga_s2am_ard_3-2-1_51KTP_2022-12-04_final.stac-item
2022-12-14 11:44:16	ga_s2am_ard_3-2-1_51KTP_2022-12-14_final.stac-item
2022-12-24 11:44:14	ga_s2am_ard_3-2-1_51KTP_2022-12-24_final.stac-item
2023-01-03 11:44:15	ga_s2am_ard_3-2-1_51KTP_2023-01-03_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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