Search ga_s2am_ard_3 across September 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
2019-09-01 10:04:40	ga_s2am_ard_3-2-1_54JYQ_2019-09-01_final
2019-09-01 10:05:35	ga_s2am_ard_3-2-1_55JBF_2019-09-01_final
2019-09-01 11:45:04	ga_s2am_ard_3-2-1_50JQR_2019-09-01_final
2019-09-01 11:45:15	ga_s2am_ard_3-2-1_51JTK_2019-09-01_final
2019-09-01 11:45:18	ga_s2am_ard_3-2-1_50JQQ_2019-09-01_final
2019-09-01 11:45:22	ga_s2am_ard_3-2-1_50JPQ_2019-09-01_final
2019-09-02 09:35:45	ga_s2am_ard_3-2-1_55HGE_2019-09-02_final
2019-09-02 11:15:11	ga_s2am_ard_3-2-1_51JYK_2019-09-02_final
2019-09-02 11:16:06	ga_s2am_ard_3-2-1_52JBL_2019-09-02_final
2019-09-03 10:44:50	ga_s2am_ard_3-2-1_53JNK_2019-09-03_final
2019-09-03 10:45:00	ga_s2am_ard_3-2-1_53JKK_2019-09-03_final
2019-09-03 10:45:58	ga_s2am_ard_3-2-1_53JKF_2019-09-03_final
2019-09-04 10:14:35	ga_s2am_ard_3-2-1_54JYQ_2019-09-04_final
2019-09-04 11:55:16	ga_s2am_ard_3-2-1_50JPQ_2019-09-04_final
2019-09-05 09:44:24	ga_s2am_ard_3-2-1_56JKQ_2019-09-05_final
2019-09-05 09:44:28	ga_s2am_ard_3-2-1_55JGK_2019-09-05_final
2019-09-05 09:45:40	ga_s2am_ard_3-2-1_55HGE_2019-09-05_final
2019-09-05 11:25:05	ga_s2am_ard_3-2-1_51JYK_2019-09-05_final
2019-09-06 10:54:55	ga_s2am_ard_3-2-1_53JKK_2019-09-06_final
2019-09-06 10:54:58	ga_s2am_ard_3-2-1_52JGQ_2019-09-06_final
2019-09-06 10:55:02	ga_s2am_ard_3-2-1_52JFQ_2019-09-06_final
2019-09-06 10:55:53	ga_s2am_ard_3-2-1_53JKF_2019-09-06_final
2019-09-07 10:24:47	ga_s2am_ard_3-2-1_54JTQ_2019-09-07_final
2019-09-07 10:24:51	ga_s2am_ard_3-2-1_53JQK_2019-09-07_final
2019-09-07 10:25:46	ga_s2am_ard_3-2-1_54JTL_2019-09-07_final
2019-09-07 10:26:00	ga_s2am_ard_3-2-1_54HTK_2019-09-07_final
2019-09-07 12:05:14	ga_s2am_ard_3-2-1_49JGL_2019-09-07_final
2019-09-07 12:05:28	ga_s2am_ard_3-2-1_49JGK_2019-09-07_final
2019-09-08 09:55:53	ga_s2am_ard_3-2-1_55HBE_2019-09-08_final
2019-09-08 11:36:31	ga_s2am_ard_3-2-1_51HTE_2019-09-08_final
2019-09-09 11:06:09	ga_s2am_ard_3-2-1_52JBL_2019-09-09_final
2019-09-10 10:34:42	ga_s2am_ard_3-2-1_54JTQ_2019-09-10_final
2019-09-10 10:34:45	ga_s2am_ard_3-2-1_53JQK_2019-09-10_final
2019-09-10 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-09-10_final
2019-09-10 12:15:18	ga_s2am_ard_3-2-1_49JGK_2019-09-10_final
2019-09-11 10:04:38	ga_s2am_ard_3-2-1_54JYQ_2019-09-11_final
2019-09-11 10:05:33	ga_s2am_ard_3-2-1_55JBF_2019-09-11_final
2019-09-11 11:45:02	ga_s2am_ard_3-2-1_50JQR_2019-09-11_final
2019-09-11 11:45:12	ga_s2am_ard_3-2-1_51JTK_2019-09-11_final
2019-09-11 11:45:16	ga_s2am_ard_3-2-1_50JQQ_2019-09-11_final
2019-09-11 11:45:19	ga_s2am_ard_3-2-1_50JPQ_2019-09-11_final
2019-09-12 09:35:43	ga_s2am_ard_3-2-1_55HGE_2019-09-12_final
2019-09-12 11:15:09	ga_s2am_ard_3-2-1_51JYK_2019-09-12_final
2019-09-12 11:16:04	ga_s2am_ard_3-2-1_52JBL_2019-09-12_final
2019-09-13 10:44:48	ga_s2am_ard_3-2-1_53JNK_2019-09-13_final
2019-09-13 10:44:58	ga_s2am_ard_3-2-1_53JKK_2019-09-13_final
2019-09-13 10:45:56	ga_s2am_ard_3-2-1_53JKF_2019-09-13_final
2019-09-14 10:14:34	ga_s2am_ard_3-2-1_54JYQ_2019-09-14_final
2019-09-14 11:55:14	ga_s2am_ard_3-2-1_50JPQ_2019-09-14_final
2019-09-15 09:44:23	ga_s2am_ard_3-2-1_56JKQ_2019-09-15_final
2019-09-15 09:44:27	ga_s2am_ard_3-2-1_55JGK_2019-09-15_final
2019-09-15 09:45:39	ga_s2am_ard_3-2-1_55HGE_2019-09-15_final
2019-09-15 11:25:05	ga_s2am_ard_3-2-1_51JYK_2019-09-15_final
2019-09-16 10:54:55	ga_s2am_ard_3-2-1_53JKK_2019-09-16_final
2019-09-16 10:54:58	ga_s2am_ard_3-2-1_52JGQ_2019-09-16_final
2019-09-16 10:55:01	ga_s2am_ard_3-2-1_52JFQ_2019-09-16_final
2019-09-16 10:55:53	ga_s2am_ard_3-2-1_53JKF_2019-09-16_final
2019-09-17 10:24:47	ga_s2am_ard_3-2-1_54JTQ_2019-09-17_final
2019-09-17 10:24:51	ga_s2am_ard_3-2-1_53JQK_2019-09-17_final
2019-09-17 10:25:46	ga_s2am_ard_3-2-1_54JTL_2019-09-17_final
2019-09-17 10:26:00	ga_s2am_ard_3-2-1_54HTK_2019-09-17_final
2019-09-17 12:05:14	ga_s2am_ard_3-2-1_49JGL_2019-09-17_final
2019-09-17 12:05:29	ga_s2am_ard_3-2-1_49JGK_2019-09-17_final
2019-09-18 09:55:53	ga_s2am_ard_3-2-1_55HBE_2019-09-18_final
2019-09-18 11:36:31	ga_s2am_ard_3-2-1_51HTE_2019-09-18_final
2019-09-19 11:06:10	ga_s2am_ard_3-2-1_52JBL_2019-09-19_final
2019-09-20 10:34:44	ga_s2am_ard_3-2-1_54JTQ_2019-09-20_final
2019-09-20 10:34:47	ga_s2am_ard_3-2-1_53JQK_2019-09-20_final
2019-09-20 12:15:10	ga_s2am_ard_3-2-1_49JGL_2019-09-20_final
2019-09-20 12:15:20	ga_s2am_ard_3-2-1_49JGK_2019-09-20_final
2019-09-21 10:04:40	ga_s2am_ard_3-2-1_54JYQ_2019-09-21_final
2019-09-21 10:05:35	ga_s2am_ard_3-2-1_55JBF_2019-09-21_final
2019-09-21 11:45:03	ga_s2am_ard_3-2-1_50JQR_2019-09-21_final
2019-09-21 11:45:14	ga_s2am_ard_3-2-1_51JTK_2019-09-21_final
2019-09-21 11:45:18	ga_s2am_ard_3-2-1_50JQQ_2019-09-21_final
2019-09-21 11:45:21	ga_s2am_ard_3-2-1_50JPQ_2019-09-21_final
2019-09-22 09:35:45	ga_s2am_ard_3-2-1_55HGE_2019-09-22_final
2019-09-22 11:15:11	ga_s2am_ard_3-2-1_51JYK_2019-09-22_final
2019-09-22 11:16:06	ga_s2am_ard_3-2-1_52JBL_2019-09-22_final
2019-09-23 10:44:50	ga_s2am_ard_3-2-1_53JNK_2019-09-23_final
2019-09-23 10:45:00	ga_s2am_ard_3-2-1_53JKK_2019-09-23_final
2019-09-23 10:45:58	ga_s2am_ard_3-2-1_53JKF_2019-09-23_final
2019-09-25 09:44:29	ga_s2am_ard_3-2-1_55JGK_2019-09-25_final
2019-09-25 09:45:41	ga_s2am_ard_3-2-1_55HGE_2019-09-25_final
2019-09-25 11:25:06	ga_s2am_ard_3-2-1_51JYK_2019-09-25_final
2019-09-26 10:54:56	ga_s2am_ard_3-2-1_53JKK_2019-09-26_final
2019-09-26 10:54:59	ga_s2am_ard_3-2-1_52JGQ_2019-09-26_final
2019-09-26 10:55:03	ga_s2am_ard_3-2-1_52JFQ_2019-09-26_final
2019-09-26 10:55:55	ga_s2am_ard_3-2-1_53JKF_2019-09-26_final
2019-09-27 10:24:49	ga_s2am_ard_3-2-1_54JTQ_2019-09-27_final
2019-09-27 10:24:52	ga_s2am_ard_3-2-1_53JQK_2019-09-27_final
2019-09-27 10:25:48	ga_s2am_ard_3-2-1_54JTL_2019-09-27_final
2019-09-27 10:26:02	ga_s2am_ard_3-2-1_54HTK_2019-09-27_final
2019-09-27 12:05:16	ga_s2am_ard_3-2-1_49JGL_2019-09-27_final
2019-09-27 12:05:30	ga_s2am_ard_3-2-1_49JGK_2019-09-27_final
2019-09-28 09:55:55	ga_s2am_ard_3-2-1_55HBE_2019-09-28_final
2019-09-28 11:36:33	ga_s2am_ard_3-2-1_51HTE_2019-09-28_final
2019-09-30 10:34:45	ga_s2am_ard_3-2-1_54JTQ_2019-09-30_final
2019-09-30 10:34:48	ga_s2am_ard_3-2-1_53JQK_2019-09-30_final
2019-09-30 12:15:12	ga_s2am_ard_3-2-1_49JGL_2019-09-30_final

Return to ga_s2am_ard_3 across September 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

September

All days