Search ga_s2am_ard_3 across 2022

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
2022-01-01 11:53:00	ga_s2am_ard_3-2-1_50KRD_2022-01-01_final
2022-01-02 11:22:57	ga_s2am_ard_3-2-1_51KYU_2022-01-02_final
2022-01-09 09:33:26	ga_s2am_ard_3-2-1_56KMU_2022-01-09_final
2022-01-12 11:22:57	ga_s2am_ard_3-2-1_51KYU_2022-01-12_final
2022-01-22 11:22:56	ga_s2am_ard_3-2-1_51KYU_2022-01-22_final
2022-01-29 09:33:25	ga_s2am_ard_3-2-1_56KMU_2022-01-29_final
2022-02-01 11:22:56	ga_s2am_ard_3-2-1_51KYU_2022-02-01_final
2022-02-08 09:33:24	ga_s2am_ard_3-2-1_56KMU_2022-02-08_final
2022-02-11 11:22:55	ga_s2am_ard_3-2-1_51KYU_2022-02-11_final
2022-02-18 09:33:26	ga_s2am_ard_3-2-1_56KMU_2022-02-18_final
2022-02-21 11:22:58	ga_s2am_ard_3-2-1_51KYU_2022-02-21_final
2022-02-28 09:33:28	ga_s2am_ard_3-2-1_56KMU_2022-02-28_final
2022-03-03 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-03-03_final
2022-03-10 09:33:29	ga_s2am_ard_3-2-1_56KMU_2022-03-10_final
2022-03-13 11:23:00	ga_s2am_ard_3-2-1_51KYU_2022-03-13_final
2022-03-20 09:33:28	ga_s2am_ard_3-2-1_56KMU_2022-03-20_final
2022-03-23 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-03-23_final
2022-03-30 09:33:27	ga_s2am_ard_3-2-1_56KMU_2022-03-30_final
2022-04-02 11:22:58	ga_s2am_ard_3-2-1_51KYU_2022-04-02_final
2022-04-09 09:33:26	ga_s2am_ard_3-2-1_56KMU_2022-04-09_final
2022-04-12 11:22:58	ga_s2am_ard_3-2-1_51KYU_2022-04-12_final
2022-04-19 09:33:29	ga_s2am_ard_3-2-1_56KMU_2022-04-19_final
2022-04-22 11:23:00	ga_s2am_ard_3-2-1_51KYU_2022-04-22_final
2022-04-29 09:33:30	ga_s2am_ard_3-2-1_56KMU_2022-04-29_final
2022-05-02 11:23:01	ga_s2am_ard_3-2-1_51KYU_2022-05-02_final
2022-05-09 09:33:29	ga_s2am_ard_3-2-1_56KMU_2022-05-09_final
2022-05-12 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-05-12_final
2022-05-19 09:33:30	ga_s2am_ard_3-2-1_56KMU_2022-05-19_final
2022-05-22 11:23:02	ga_s2am_ard_3-2-1_51KYU_2022-05-22_final
2022-05-29 09:33:32	ga_s2am_ard_3-2-1_56KMU_2022-05-29_final
2022-06-01 11:23:04	ga_s2am_ard_3-2-1_51KYU_2022-06-01_final
2022-06-08 09:33:33	ga_s2am_ard_3-2-1_56KMU_2022-06-08_final
2022-06-11 11:23:05	ga_s2am_ard_3-2-1_51KYU_2022-06-11_final
2022-06-18 09:33:36	ga_s2am_ard_3-2-1_56KMU_2022-06-18_final
2022-06-21 11:23:08	ga_s2am_ard_3-2-1_51KYU_2022-06-21_final
2022-06-28 09:33:37	ga_s2am_ard_3-2-1_56KMU_2022-06-28_final
2022-07-01 11:23:09	ga_s2am_ard_3-2-1_51KYU_2022-07-01_final
2022-07-08 09:33:38	ga_s2am_ard_3-2-1_56KMU_2022-07-08_final
2022-07-11 11:23:09	ga_s2am_ard_3-2-1_51KYU_2022-07-11_final
2022-07-16 10:33:00	ga_s2am_ard_3-2-1_53KRT_2022-07-16_final
2022-07-18 09:33:37	ga_s2am_ard_3-2-1_56KMU_2022-07-18_final
2022-07-21 11:23:07	ga_s2am_ard_3-2-1_51KYU_2022-07-21_final
2022-07-26 10:32:58	ga_s2am_ard_3-2-1_53KRT_2022-07-26_final
2022-07-28 09:33:34	ga_s2am_ard_3-2-1_56KMU_2022-07-28_final
2022-07-31 11:23:00	ga_s2am_ard_3-2-1_51KYU_2022-07-31_final
2022-08-05 10:32:59	ga_s2am_ard_3-2-1_53KRT_2022-08-05_final
2022-08-07 09:33:36	ga_s2am_ard_3-2-1_56KMU_2022-08-07_final
2022-08-10 11:23:08	ga_s2am_ard_3-2-1_51KYU_2022-08-10_final
2022-08-15 10:33:00	ga_s2am_ard_3-2-1_53KRT_2022-08-15_final
2022-08-17 09:33:37	ga_s2am_ard_3-2-1_56KMU_2022-08-17_final
2022-08-20 11:23:08	ga_s2am_ard_3-2-1_51KYU_2022-08-20_final
2022-08-24 11:03:07	ga_s2am_ard_3-2-1_52KHC_2022-08-24_final.stac-item
2022-08-25 10:33:00	ga_s2am_ard_3-2-1_53KRT_2022-08-25_final
2022-08-30 11:23:08	ga_s2am_ard_3-2-1_51KYU_2022-08-30_final
2022-09-04 10:32:48	ga_s2am_ard_3-2-1_54KVC_2022-09-04_final.stac-item
2022-09-06 09:33:36	ga_s2am_ard_3-2-1_56KMU_2022-09-06_final.stac-item
2022-09-09 11:23:07	ga_s2am_ard_3-2-1_51KYU_2022-09-09_final.stac-item
2022-09-13 11:02:54	ga_s2am_ard_3-2-1_52KFD_2022-09-13_final.stac-item
2022-09-14 10:32:53	ga_s2am_ard_3-2-1_53KRT_2022-09-14_final.stac-item
2022-09-16 09:33:34	ga_s2am_ard_3-2-1_56KMU_2022-09-16_final.stac-item
2022-09-19 11:23:04	ga_s2am_ard_3-2-1_51KYU_2022-09-19_final.stac-item
2022-09-24 10:32:52	ga_s2am_ard_3-2-1_53KQT_2022-09-24_final.stac-item
2022-09-26 09:33:32	ga_s2am_ard_3-2-1_56KMU_2022-09-26_final.stac-item
2022-09-27 10:42:56	ga_s2am_ard_3-2-1_53KPT_2022-09-27_final.stac-item
2022-09-29 11:23:03	ga_s2am_ard_3-2-1_51KYU_2022-09-29_final.stac-item
2022-10-04 10:32:50	ga_s2am_ard_3-2-1_53KRT_2022-10-04_final.stac-item
2022-10-06 09:33:31	ga_s2am_ard_3-2-1_56KMU_2022-10-06_final.stac-item
2022-10-09 11:23:02	ga_s2am_ard_3-2-1_51KYU_2022-10-09_final.stac-item
2022-10-14 10:32:48	ga_s2am_ard_3-2-1_53KRT_2022-10-14_final.stac-item
2022-10-16 09:33:28	ga_s2am_ard_3-2-1_56KMU_2022-10-16_final.stac-item
2022-10-19 11:22:58	ga_s2am_ard_3-2-1_51KYU_2022-10-19_final.stac-item
2022-10-24 10:32:46	ga_s2am_ard_3-2-1_53KRT_2022-10-24_final.stac-item
2022-10-24 10:32:47	ga_s2am_ard_3-2-1_53KQT_2022-10-24_final.stac-item
2022-10-26 09:33:28	ga_s2am_ard_3-2-1_56KMU_2022-10-26_final.stac-item
2022-10-27 10:42:37	ga_s2am_ard_3-2-1_53KNU_2022-10-27_final.stac-item
2022-10-29 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-10-29_final.stac-item
2022-11-03 10:32:52	ga_s2am_ard_3-2-1_53KRT_2022-11-03_final.stac-item
2022-11-05 09:33:29	ga_s2am_ard_3-2-1_56KMU_2022-11-05_final.stac-item
2022-11-13 10:32:51	ga_s2am_ard_3-2-1_53KRT_2022-11-13_final.stac-item
2022-11-15 09:33:27	ga_s2am_ard_3-2-1_56KMU_2022-11-15_final.stac-item
2022-11-18 11:22:57	ga_s2am_ard_3-2-1_51KYU_2022-11-18_final.stac-item
2022-11-23 10:32:48	ga_s2am_ard_3-2-1_53KRT_2022-11-23_final.stac-item
2022-11-28 11:22:55	ga_s2am_ard_3-2-1_51KYU_2022-11-28_final.stac-item
2022-11-28 11:23:06	ga_s2am_ard_3-2-1_51KZT_2022-11-28_final.stac-item
2022-12-03 10:32:48	ga_s2am_ard_3-2-1_53KRT_2022-12-03_final.stac-item
2022-12-04 10:02:42	ga_s2am_ard_3-2-1_54KZC_2022-12-04_final.stac-item
2022-12-08 11:22:56	ga_s2am_ard_3-2-1_51KYU_2022-12-08_final.stac-item
2022-12-08 11:23:07	ga_s2am_ard_3-2-1_51KZT_2022-12-08_final.stac-item
2022-12-12 11:02:55	ga_s2am_ard_3-2-1_52KHC_2022-12-12_final.stac-item
2022-12-13 10:32:48	ga_s2am_ard_3-2-1_53KRT_2022-12-13_final.stac-item
2022-12-14 10:02:41	ga_s2am_ard_3-2-1_54KZC_2022-12-14_final.stac-item
2022-12-18 11:22:55	ga_s2am_ard_3-2-1_51KYU_2022-12-18_final.stac-item
2022-12-18 11:23:06	ga_s2am_ard_3-2-1_51KZT_2022-12-18_final.stac-item
2022-12-19 10:52:58	ga_s2am_ard_3-2-1_52KHC_2022-12-19_final.stac-item
2022-12-22 11:02:42	ga_s2am_ard_3-2-1_52KGD_2022-12-22_final.stac-item
2022-12-22 11:04:12	ga_s2am_ard_3-2-1_52JFT_2022-12-22_final.stac-item
2022-12-23 10:32:45	ga_s2am_ard_3-2-1_53KRT_2022-12-23_final.stac-item
2022-12-28 11:22:54	ga_s2am_ard_3-2-1_51KYU_2022-12-28_final.stac-item
2022-12-28 11:23:05	ga_s2am_ard_3-2-1_51KZT_2022-12-28_final.stac-item
2022-12-29 10:52:44	ga_s2am_ard_3-2-1_53KNT_2022-12-29_final.stac-item

Return to ga_s2am_ard_3 across 2022 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

2022

All months