Search ga_s2am_ard_3 across 2019

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
2019-01-02 09:26:55	ga_s2am_ard_3-2-1_55HGV_2019-01-01_final
2019-01-05 09:36:51	ga_s2am_ard_3-2-1_55HGV_2019-01-05_final
2019-01-12 09:26:56	ga_s2am_ard_3-2-1_55HGV_2019-01-11_final
2019-01-15 09:36:52	ga_s2am_ard_3-2-1_55HGV_2019-01-15_final
2019-01-22 09:26:57	ga_s2am_ard_3-2-1_55HGV_2019-01-21_final
2019-01-25 09:36:53	ga_s2am_ard_3-2-1_55HGV_2019-01-25_final
2019-02-01 09:26:58	ga_s2am_ard_3-2-1_55HGV_2019-01-31_final
2019-02-04 09:36:53	ga_s2am_ard_3-2-1_55HGV_2019-02-04_final
2019-02-11 09:26:58	ga_s2am_ard_3-2-1_55HGV_2019-02-10_final
2019-02-14 09:36:53	ga_s2am_ard_3-2-1_55HGV_2019-02-14_final
2019-02-21 09:26:57	ga_s2am_ard_3-2-1_55HGV_2019-02-20_final
2019-02-24 09:36:52	ga_s2am_ard_3-2-1_55HGV_2019-02-24_final
2019-02-27 11:26:43	ga_s2am_ard_3-2-1_51HXC_2019-02-27_final.stac-item
2019-03-03 09:26:56	ga_s2am_ard_3-2-1_55HGV_2019-03-02_final
2019-03-06 09:36:51	ga_s2am_ard_3-2-1_55HGV_2019-03-06_final
2019-03-13 09:26:57	ga_s2am_ard_3-2-1_55HGV_2019-03-12_final
2019-03-16 09:36:53	ga_s2am_ard_3-2-1_55HGV_2019-03-16_final
2019-03-23 09:26:59	ga_s2am_ard_3-2-1_55HGV_2019-03-22_final
2019-03-26 09:36:55	ga_s2am_ard_3-2-1_55HGV_2019-03-26_final
2019-04-02 09:27:01	ga_s2am_ard_3-2-1_55HGV_2019-04-01_final
2019-04-05 09:36:57	ga_s2am_ard_3-2-1_55HGV_2019-04-05_final
2019-04-08 11:26:49	ga_s2am_ard_3-2-1_51HXC_2019-04-08_final.stac-item
2019-04-12 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-04-11_final
2019-04-15 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-04-15_final
2019-04-16 10:46:34	ga_s2am_ard_3-2-1_53HMC_2019-04-16_final.stac-item
2019-04-22 09:27:04	ga_s2am_ard_3-2-1_55HGV_2019-04-21_final
2019-04-25 09:37:00	ga_s2am_ard_3-2-1_55HGV_2019-04-25_final
2019-05-02 09:27:05	ga_s2am_ard_3-2-1_55HGV_2019-05-01_final
2019-05-05 09:37:00	ga_s2am_ard_3-2-1_55HGV_2019-05-05_final
2019-05-12 09:27:05	ga_s2am_ard_3-2-1_55HGV_2019-05-11_final
2019-05-15 09:37:00	ga_s2am_ard_3-2-1_55HGV_2019-05-15_final
2019-05-22 09:27:04	ga_s2am_ard_3-2-1_55HGV_2019-05-21_final
2019-05-25 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-05-25_final
2019-05-28 11:26:50	ga_s2am_ard_3-2-1_51HXC_2019-05-28_final.stac-item
2019-05-28 11:26:55	ga_s2am_ard_3-2-1_51HWC_2019-05-28_final.stac-item
2019-06-01 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-05-31_final
2019-06-04 09:36:58	ga_s2am_ard_3-2-1_55HGV_2019-06-04_final
2019-06-07 11:26:50	ga_s2am_ard_3-2-1_51HXC_2019-06-07_final.stac-item
2019-06-11 09:27:04	ga_s2am_ard_3-2-1_55HGV_2019-06-10_final
2019-06-14 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-06-14_final
2019-06-21 09:27:05	ga_s2am_ard_3-2-1_55HGV_2019-06-20_final
2019-06-24 09:37:00	ga_s2am_ard_3-2-1_55HGV_2019-06-24_final
2019-07-01 09:27:06	ga_s2am_ard_3-2-1_55HGV_2019-06-30_final
2019-07-04 09:37:01	ga_s2am_ard_3-2-1_55HGV_2019-07-04_final
2019-07-07 11:26:53	ga_s2am_ard_3-2-1_51HXC_2019-07-07_final.stac-item
2019-07-11 09:27:06	ga_s2am_ard_3-2-1_55HGV_2019-07-10_final
2019-07-14 09:37:01	ga_s2am_ard_3-2-1_55HGV_2019-07-14_final
2019-07-21 09:27:06	ga_s2am_ard_3-2-1_55HGV_2019-07-20_final
2019-07-24 09:37:01	ga_s2am_ard_3-2-1_55HGV_2019-07-24_final
2019-07-27 11:26:52	ga_s2am_ard_3-2-1_51HXC_2019-07-27_final.stac-item
2019-07-31 09:27:05	ga_s2am_ard_3-2-1_55HGV_2019-07-30_final
2019-08-03 09:37:01	ga_s2am_ard_3-2-1_55HGV_2019-08-03_final
2019-08-09 09:57:10	ga_s2am_ard_3-2-1_55HBV_2019-08-09_final
2019-08-10 09:27:05	ga_s2am_ard_3-2-1_55HGV_2019-08-09_final
2019-08-12 10:06:59	ga_s2am_ard_3-2-1_55HBV_2019-08-12_final
2019-08-13 09:37:00	ga_s2am_ard_3-2-1_55HGV_2019-08-13_final
2019-08-19 09:57:09	ga_s2am_ard_3-2-1_55HBV_2019-08-19_final
2019-08-20 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-08-19_final
2019-08-22 10:06:58	ga_s2am_ard_3-2-1_55HBV_2019-08-22_final
2019-08-23 09:36:58	ga_s2am_ard_3-2-1_55HGV_2019-08-23_final
2019-08-29 09:57:08	ga_s2am_ard_3-2-1_55HBV_2019-08-29_final
2019-08-30 09:27:02	ga_s2am_ard_3-2-1_55HGV_2019-08-29_final
2019-09-01 10:06:56	ga_s2am_ard_3-2-1_55HBV_2019-09-01_final
2019-09-02 09:36:57	ga_s2am_ard_3-2-1_55HGV_2019-09-02_final
2019-09-08 09:57:05	ga_s2am_ard_3-2-1_55HBV_2019-09-08_final
2019-09-09 09:27:00	ga_s2am_ard_3-2-1_55HGV_2019-09-08_final
2019-09-11 10:06:54	ga_s2am_ard_3-2-1_55HBV_2019-09-11_final
2019-09-12 09:36:54	ga_s2am_ard_3-2-1_55HGV_2019-09-12_final
2019-09-15 11:26:46	ga_s2am_ard_3-2-1_51HXC_2019-09-15_final.stac-item
2019-09-18 09:57:06	ga_s2am_ard_3-2-1_55HBV_2019-09-18_final
2019-09-19 09:27:01	ga_s2am_ard_3-2-1_55HGV_2019-09-18_final
2019-09-21 10:06:55	ga_s2am_ard_3-2-1_55HBV_2019-09-21_final
2019-09-28 09:57:08	ga_s2am_ard_3-2-1_55HBV_2019-09-28_final
2019-09-29 09:27:02	ga_s2am_ard_3-2-1_55HGV_2019-09-28_final
2019-10-01 10:06:57	ga_s2am_ard_3-2-1_55HBV_2019-10-01_final
2019-10-08 09:57:09	ga_s2am_ard_3-2-1_55HBV_2019-10-08_final
2019-10-09 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-10-08_final
2019-10-11 10:06:58	ga_s2am_ard_3-2-1_55HBV_2019-10-11_final
2019-10-12 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-10-12_final
2019-10-18 09:57:10	ga_s2am_ard_3-2-1_55HBV_2019-10-18_final
2019-10-19 09:27:04	ga_s2am_ard_3-2-1_55HGV_2019-10-18_final
2019-10-21 10:06:59	ga_s2am_ard_3-2-1_55HBV_2019-10-21_final
2019-10-22 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-10-22_final
2019-10-28 09:57:10	ga_s2am_ard_3-2-1_55HBV_2019-10-28_final
2019-10-29 09:27:04	ga_s2am_ard_3-2-1_55HGV_2019-10-28_final
2019-10-31 10:06:59	ga_s2am_ard_3-2-1_55HBV_2019-10-31_final
2019-11-01 09:36:59	ga_s2am_ard_3-2-1_55HGV_2019-11-01_final
2019-11-07 09:57:09	ga_s2am_ard_3-2-1_55HBV_2019-11-07_final
2019-11-08 09:27:03	ga_s2am_ard_3-2-1_55HGV_2019-11-07_final
2019-11-10 10:06:58	ga_s2am_ard_3-2-1_55HBV_2019-11-10_final
2019-11-17 09:57:08	ga_s2am_ard_3-2-1_55HBV_2019-11-17_final
2019-11-20 10:06:57	ga_s2am_ard_3-2-1_55HBV_2019-11-20_final
2019-11-27 09:57:06	ga_s2am_ard_3-2-1_55HBV_2019-11-27_final
2019-11-30 10:06:55	ga_s2am_ard_3-2-1_55HBV_2019-11-30_final
2019-12-04 11:26:46	ga_s2am_ard_3-2-1_51HXC_2019-12-04_final.stac-item
2019-12-07 09:57:04	ga_s2am_ard_3-2-1_55HBV_2019-12-07_final
2019-12-10 10:06:52	ga_s2am_ard_3-2-1_55HBV_2019-12-10_final
2019-12-17 09:57:01	ga_s2am_ard_3-2-1_55HBV_2019-12-17_final
2019-12-20 10:06:50	ga_s2am_ard_3-2-1_55HBV_2019-12-20_final
2019-12-27 09:57:01	ga_s2am_ard_3-2-1_55HBV_2019-12-27_final

Return to ga_s2am_ard_3 across 2019 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

2019

All months