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
2018-07-20 10:37:28	ga_s2am_ard_3-2-1_53JNJ_2018-07-20_final
2018-07-30 10:37:28	ga_s2am_ard_3-2-1_53JNJ_2018-07-30_final
2018-08-09 10:37:27	ga_s2am_ard_3-2-1_53JNJ_2018-08-09_final
2018-09-08 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-09-08_final
2018-09-18 10:37:23	ga_s2am_ard_3-2-1_53JNJ_2018-09-18_final
2018-09-28 10:37:23	ga_s2am_ard_3-2-1_53JNJ_2018-09-28_final
2018-10-08 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-10-08_final
2018-10-18 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-10-18_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-10-28_final
2018-12-27 10:44:57	ga_s2am_ard_3-2-1_53JNJ_2018-12-27_final
2019-01-06 10:44:59	ga_s2am_ard_3-2-1_53JNJ_2019-01-06_final
2019-01-16 10:45:00	ga_s2am_ard_3-2-1_53JNJ_2019-01-16_final
2019-04-26 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-04-26_final
2019-05-03 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-03_final
2019-05-06 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-05-06_final
2019-05-13 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-13_final
2019-05-16 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-05-16_final
2019-05-23 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-05-23_final
2019-05-26 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-05-26_final
2019-06-02 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-06-02_final
2019-06-05 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-06-05_final
2019-06-12 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-06-12_final
2019-06-15 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-06-15_final
2019-06-25 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-06-25_final
2019-07-01 11:05:24	ga_s2am_ard_3-2-1_52JDP_2019-07-01_final
2019-07-02 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-02_final
2019-07-04 11:15:17	ga_s2am_ard_3-2-1_52JDP_2019-07-04_final
2019-07-05 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-07-05_final
2019-07-11 11:05:25	ga_s2am_ard_3-2-1_52JDP_2019-07-11_final
2019-07-12 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-12_final
2019-07-15 10:45:10	ga_s2am_ard_3-2-1_53JNJ_2019-07-15_final
2019-07-21 11:05:25	ga_s2am_ard_3-2-1_52JDP_2019-07-21_final
2019-07-22 10:35:14	ga_s2am_ard_3-2-1_53JNJ_2019-07-22_final
2019-07-25 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-07-25_final
2019-07-31 11:05:24	ga_s2am_ard_3-2-1_52JDP_2019-07-31_final
2019-08-01 10:35:13	ga_s2am_ard_3-2-1_53JNJ_2019-08-01_final
2019-08-04 10:45:09	ga_s2am_ard_3-2-1_53JNJ_2019-08-04_final
2019-08-10 11:05:23	ga_s2am_ard_3-2-1_52JDP_2019-08-10_final
2019-08-10 11:05:30	ga_s2am_ard_3-2-1_52JDP_2019-08-10_final
2019-08-11 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-08-11_final
2019-08-14 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-08-14_final
2019-08-20 11:05:22	ga_s2am_ard_3-2-1_52JDP_2019-08-20_final
2019-08-21 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-08-21_final
2019-08-23 11:15:14	ga_s2am_ard_3-2-1_52JDP_2019-08-23_final
2019-08-24 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-08-24_final
2019-08-30 11:05:20	ga_s2am_ard_3-2-1_52JDP_2019-08-30_final
2019-08-31 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2019-08-31_final
2019-09-02 11:15:12	ga_s2am_ard_3-2-1_52JDP_2019-09-02_final
2019-09-03 10:45:04	ga_s2am_ard_3-2-1_53JNJ_2019-09-03_final
2019-09-09 11:05:18	ga_s2am_ard_3-2-1_52JDP_2019-09-09_final
2019-09-09 11:05:24	ga_s2am_ard_3-2-1_52JDP_2019-09-09_final
2019-09-10 10:35:07	ga_s2am_ard_3-2-1_53JNJ_2019-09-10_final
2019-09-12 11:15:10	ga_s2am_ard_3-2-1_52JDP_2019-09-12_final
2019-09-13 10:45:03	ga_s2am_ard_3-2-1_53JNJ_2019-09-13_final
2019-09-19 11:05:19	ga_s2am_ard_3-2-1_52JDP_2019-09-19_final
2019-09-20 10:35:09	ga_s2am_ard_3-2-1_53JNJ_2019-09-20_final
2019-09-23 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2019-09-23_final
2019-09-29 11:05:25	ga_s2am_ard_3-2-1_52JDP_2019-09-29_final
2019-09-30 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2019-09-30_final
2019-10-03 10:45:06	ga_s2am_ard_3-2-1_53JNJ_2019-10-03_final
2019-10-09 11:05:22	ga_s2am_ard_3-2-1_52JDP_2019-10-09_final
2019-10-10 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-10-10_final
2019-10-13 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-10-13_final
2019-10-19 11:05:23	ga_s2am_ard_3-2-1_52JDP_2019-10-19_final
2019-10-20 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-10-20_final
2019-10-23 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-10-23_final
2019-10-29 11:05:23	ga_s2am_ard_3-2-1_52JDP_2019-10-29_final
2019-10-30 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-10-30_final
2019-11-02 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-11-02_final
2019-11-08 11:05:22	ga_s2am_ard_3-2-1_52JDP_2019-11-08_final
2019-11-09 10:35:11	ga_s2am_ard_3-2-1_53JNJ_2019-11-09_final
2019-11-12 10:45:07	ga_s2am_ard_3-2-1_53JNJ_2019-11-12_final
2019-11-18 11:05:21	ga_s2am_ard_3-2-1_52JDP_2019-11-18_final
2019-11-19 10:35:10	ga_s2am_ard_3-2-1_53JNJ_2019-11-19_final
2019-11-21 11:15:13	ga_s2am_ard_3-2-1_52JDP_2019-11-21_final
2019-11-22 10:45:05	ga_s2am_ard_3-2-1_53JNJ_2019-11-22_final
2019-11-28 11:05:19	ga_s2am_ard_3-2-1_52JDP_2019-11-28_final
2019-11-29 10:35:08	ga_s2am_ard_3-2-1_53JNJ_2019-11-29_final
2019-12-01 11:15:11	ga_s2am_ard_3-2-1_52JDP_2019-12-01_final
2019-12-02 10:45:03	ga_s2am_ard_3-2-1_53JNJ_2019-12-02_final
2019-12-08 11:05:17	ga_s2am_ard_3-2-1_52JDP_2019-12-08_final
2019-12-09 10:35:06	ga_s2am_ard_3-2-1_53JNJ_2019-12-09_final
2019-12-11 11:15:09	ga_s2am_ard_3-2-1_52JDP_2019-12-11_final
2019-12-12 10:45:00	ga_s2am_ard_3-2-1_53JNJ_2019-12-12_final
2019-12-18 11:05:13	ga_s2am_ard_3-2-1_52JDP_2019-12-18_final
2019-12-19 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2019-12-19_final
2019-12-21 11:15:06	ga_s2am_ard_3-2-1_52JDP_2019-12-21_final
2019-12-22 10:44:58	ga_s2am_ard_3-2-1_53JNJ_2019-12-22_final
2019-12-28 11:05:14	ga_s2am_ard_3-2-1_52JDP_2019-12-28_final
2019-12-29 10:35:03	ga_s2am_ard_3-2-1_53JNJ_2019-12-29_final
2019-12-31 11:15:07	ga_s2am_ard_3-2-1_52JDP_2019-12-31_final
2020-01-07 11:05:14	ga_s2am_ard_3-2-1_52JDP_2020-01-07_final
2020-01-10 11:15:07	ga_s2am_ard_3-2-1_52JDP_2020-01-10_final
2020-01-17 11:05:13	ga_s2am_ard_3-2-1_52JDP_2020-01-17_final
2020-01-20 11:15:06	ga_s2am_ard_3-2-1_52JDP_2020-01-20_final
2020-01-27 11:05:12	ga_s2am_ard_3-2-1_52JDP_2020-01-27_final
2020-01-30 11:15:05	ga_s2am_ard_3-2-1_52JDP_2020-01-30_final
2020-02-06 11:05:11	ga_s2am_ard_3-2-1_52JDP_2020-02-06_final
2020-04-16 11:05:19	ga_s2am_ard_3-2-1_52JDP_2020-04-16_final
2020-08-04 11:05:25	ga_s2am_ard_3-2-1_52JDP_2020-08-04_final

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

All years