Search ga_s2am_ard_3 across April 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
2019-04-01 09:53:15	ga_s2am_ard_3-2-1_55KFQ_2019-04-01_final
2019-04-01 09:55:11	ga_s2am_ard_3-2-1_55JBH_2019-04-01_final
2019-04-01 11:35:48	ga_s2am_ard_3-2-1_51JTH_2019-04-01_final
2019-04-02 09:24:24	ga_s2am_ard_3-2-1_56JNQ_2019-04-01_final.stac-item
2019-04-02 09:24:28	ga_s2am_ard_3-2-1_56JMQ_2019-04-01_final
2019-04-02 11:02:11	ga_s2am_ard_3-2-1_53KKA_2019-04-02_final
2019-04-02 11:03:28	ga_s2am_ard_3-2-1_52KGA_2019-04-02_final
2019-04-03 10:33:28	ga_s2am_ard_3-2-1_54KUV_2019-04-03_final
2019-04-03 10:33:38	ga_s2am_ard_3-2-1_53KPQ_2019-04-03_final
2019-04-03 10:33:53	ga_s2am_ard_3-2-1_53KPP_2019-04-03_final
2019-04-03 10:35:09	ga_s2am_ard_3-2-1_54JTN_2019-04-03_final
2019-04-03 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-04-03_final
2019-04-04 10:03:21	ga_s2am_ard_3-2-1_55KCQ_2019-04-04_final
2019-04-04 10:05:06	ga_s2am_ard_3-2-1_55JBH_2019-04-04_final
2019-04-04 11:43:59	ga_s2am_ard_3-2-1_51KUQ_2019-04-04_final
2019-04-04 11:45:44	ga_s2am_ard_3-2-1_51JTH_2019-04-04_final
2019-04-05 09:33:14	ga_s2am_ard_3-2-1_56KLV_2019-04-05_final
2019-04-05 09:34:20	ga_s2am_ard_3-2-1_56JNQ_2019-04-05_final.stac-item
2019-04-05 09:34:24	ga_s2am_ard_3-2-1_56JMQ_2019-04-05_final
2019-04-05 11:13:52	ga_s2am_ard_3-2-1_52KCV_2019-04-05_final
2019-04-06 10:43:42	ga_s2am_ard_3-2-1_53KMQ_2019-04-06_final
2019-04-06 10:43:46	ga_s2am_ard_3-2-1_53KLQ_2019-04-06_final
2019-04-07 10:13:28	ga_s2am_ard_3-2-1_54KXV_2019-04-07_final
2019-04-07 10:14:47	ga_s2am_ard_3-2-1_54JVQ_2019-04-07_final
2019-04-07 11:56:01	ga_s2am_ard_3-2-1_50JKN_2019-04-07_final
2019-04-08 11:22:24	ga_s2am_ard_3-2-1_52KBF_2019-04-08_final
2019-04-08 11:22:28	ga_s2am_ard_3-2-1_51KYA_2019-04-08_final
2019-04-09 10:53:34	ga_s2am_ard_3-2-1_52KGA_2019-04-09_final
2019-04-09 10:53:41	ga_s2am_ard_3-2-1_53KLQ_2019-04-09_final
2019-04-10 10:23:19	ga_s2am_ard_3-2-1_54KXV_2019-04-10_final
2019-04-10 10:23:31	ga_s2am_ard_3-2-1_54KVV_2019-04-10_final
2019-04-10 10:23:34	ga_s2am_ard_3-2-1_54KUV_2019-04-10_final
2019-04-10 10:25:19	ga_s2am_ard_3-2-1_54JTN_2019-04-10_final
2019-04-10 12:05:57	ga_s2am_ard_3-2-1_50JKN_2019-04-10_final
2019-04-11 09:53:17	ga_s2am_ard_3-2-1_55KFQ_2019-04-11_final
2019-04-11 09:55:13	ga_s2am_ard_3-2-1_55JBH_2019-04-11_final
2019-04-11 11:35:50	ga_s2am_ard_3-2-1_51JTH_2019-04-11_final
2019-04-12 09:24:25	ga_s2am_ard_3-2-1_56JNQ_2019-04-11_final.stac-item
2019-04-12 09:24:30	ga_s2am_ard_3-2-1_56JMQ_2019-04-11_final
2019-04-12 11:02:12	ga_s2am_ard_3-2-1_53KKA_2019-04-12_final
2019-04-12 11:03:29	ga_s2am_ard_3-2-1_52KGA_2019-04-12_final
2019-04-13 10:33:30	ga_s2am_ard_3-2-1_54KUV_2019-04-13_final
2019-04-13 10:33:40	ga_s2am_ard_3-2-1_53KPQ_2019-04-13_final
2019-04-13 10:33:55	ga_s2am_ard_3-2-1_53KPP_2019-04-13_final
2019-04-13 10:35:10	ga_s2am_ard_3-2-1_54JTN_2019-04-13_final
2019-04-13 12:14:00	ga_s2am_ard_3-2-1_49KGR_2019-04-13_final
2019-04-14 10:03:23	ga_s2am_ard_3-2-1_55KCQ_2019-04-14_final
2019-04-14 10:05:08	ga_s2am_ard_3-2-1_55JBH_2019-04-14_final
2019-04-14 11:44:00	ga_s2am_ard_3-2-1_51KUQ_2019-04-14_final
2019-04-14 11:45:46	ga_s2am_ard_3-2-1_51JTH_2019-04-14_final
2019-04-15 09:33:15	ga_s2am_ard_3-2-1_56KLV_2019-04-15_final
2019-04-15 09:34:21	ga_s2am_ard_3-2-1_56JNQ_2019-04-15_final.stac-item
2019-04-15 09:34:25	ga_s2am_ard_3-2-1_56JMQ_2019-04-15_final
2019-04-15 11:13:54	ga_s2am_ard_3-2-1_52KCV_2019-04-15_final
2019-04-16 10:43:43	ga_s2am_ard_3-2-1_53KMQ_2019-04-16_final
2019-04-16 10:43:48	ga_s2am_ard_3-2-1_53KLQ_2019-04-16_final
2019-04-17 10:13:29	ga_s2am_ard_3-2-1_54KXV_2019-04-17_final
2019-04-17 10:14:48	ga_s2am_ard_3-2-1_54JVQ_2019-04-17_final
2019-04-17 11:56:02	ga_s2am_ard_3-2-1_50JKN_2019-04-17_final
2019-04-18 11:22:25	ga_s2am_ard_3-2-1_52KBF_2019-04-18_final
2019-04-18 11:22:29	ga_s2am_ard_3-2-1_51KYA_2019-04-18_final
2019-04-19 10:53:35	ga_s2am_ard_3-2-1_52KGA_2019-04-19_final
2019-04-19 10:53:42	ga_s2am_ard_3-2-1_53KLQ_2019-04-19_final
2019-04-20 10:23:20	ga_s2am_ard_3-2-1_54KXV_2019-04-20_final
2019-04-20 10:23:32	ga_s2am_ard_3-2-1_54KVV_2019-04-20_final
2019-04-20 10:23:35	ga_s2am_ard_3-2-1_54KUV_2019-04-20_final
2019-04-20 10:25:20	ga_s2am_ard_3-2-1_54JTN_2019-04-20_final
2019-04-20 12:05:58	ga_s2am_ard_3-2-1_50JKN_2019-04-20_final
2019-04-21 09:53:18	ga_s2am_ard_3-2-1_55KFQ_2019-04-21_final
2019-04-21 09:55:14	ga_s2am_ard_3-2-1_55JBH_2019-04-21_final
2019-04-21 11:35:51	ga_s2am_ard_3-2-1_51JTH_2019-04-21_final
2019-04-22 09:24:27	ga_s2am_ard_3-2-1_56JNQ_2019-04-21_final.stac-item
2019-04-22 09:24:31	ga_s2am_ard_3-2-1_56JMQ_2019-04-21_final
2019-04-22 11:02:13	ga_s2am_ard_3-2-1_53KKA_2019-04-22_final
2019-04-22 11:03:30	ga_s2am_ard_3-2-1_52KGA_2019-04-22_final
2019-04-23 10:33:31	ga_s2am_ard_3-2-1_54KUV_2019-04-23_final
2019-04-23 10:33:41	ga_s2am_ard_3-2-1_53KPQ_2019-04-23_final
2019-04-23 10:33:56	ga_s2am_ard_3-2-1_53KPP_2019-04-23_final
2019-04-23 10:35:11	ga_s2am_ard_3-2-1_54JTN_2019-04-23_final
2019-04-23 12:14:01	ga_s2am_ard_3-2-1_49KGR_2019-04-23_final
2019-04-24 10:03:24	ga_s2am_ard_3-2-1_55KCQ_2019-04-24_final
2019-04-24 10:05:09	ga_s2am_ard_3-2-1_55JBH_2019-04-24_final
2019-04-24 11:44:01	ga_s2am_ard_3-2-1_51KUQ_2019-04-24_final
2019-04-24 11:45:47	ga_s2am_ard_3-2-1_51JTH_2019-04-24_final
2019-04-25 09:33:16	ga_s2am_ard_3-2-1_56KLV_2019-04-25_final
2019-04-25 09:34:22	ga_s2am_ard_3-2-1_56JNQ_2019-04-25_final.stac-item
2019-04-25 09:34:26	ga_s2am_ard_3-2-1_56JMQ_2019-04-25_final
2019-04-25 11:13:54	ga_s2am_ard_3-2-1_52KCV_2019-04-25_final
2019-04-26 10:43:44	ga_s2am_ard_3-2-1_53KMQ_2019-04-26_final
2019-04-26 10:43:49	ga_s2am_ard_3-2-1_53KLQ_2019-04-26_final
2019-04-27 10:13:30	ga_s2am_ard_3-2-1_54KXV_2019-04-27_final
2019-04-27 10:14:49	ga_s2am_ard_3-2-1_54JVQ_2019-04-27_final
2019-04-27 11:56:03	ga_s2am_ard_3-2-1_50JKN_2019-04-27_final
2019-04-28 11:22:26	ga_s2am_ard_3-2-1_52KBF_2019-04-28_final
2019-04-29 10:53:36	ga_s2am_ard_3-2-1_52KGA_2019-04-29_final
2019-04-29 10:53:43	ga_s2am_ard_3-2-1_53KLQ_2019-04-29_final
2019-04-30 10:23:21	ga_s2am_ard_3-2-1_54KXV_2019-04-30_final
2019-04-30 10:23:33	ga_s2am_ard_3-2-1_54KVV_2019-04-30_final
2019-04-30 10:23:36	ga_s2am_ard_3-2-1_54KUV_2019-04-30_final
2019-04-30 10:25:21	ga_s2am_ard_3-2-1_54JTN_2019-04-30_final

Return to ga_s2am_ard_3 across April 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

April

All days