Search ga_s2am_ard_3 across June 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
2019-06-01 11:00:46	ga_s2am_ard_3-2-1_53LKG_2019-06-01_final
2019-06-02 10:32:07	ga_s2am_ard_3-2-1_53KRA_2019-06-02_final
2019-06-02 10:33:01	ga_s2am_ard_3-2-1_54KUB_2019-06-02_final
2019-06-02 10:33:15	ga_s2am_ard_3-2-1_53KPS_2019-06-02_final
2019-06-03 10:02:54	ga_s2am_ard_3-2-1_55KCS_2019-06-03_final
2019-06-03 11:43:27	ga_s2am_ard_3-2-1_51KVS_2019-06-03_final
2019-06-03 11:43:31	ga_s2am_ard_3-2-1_51KUS_2019-06-03_final
2019-06-03 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-06-03_final
2019-06-04 11:13:17	ga_s2am_ard_3-2-1_52KEB_2019-06-04_final
2019-06-04 11:13:21	ga_s2am_ard_3-2-1_52KDB_2019-06-04_final
2019-06-04 11:13:24	ga_s2am_ard_3-2-1_52KCB_2019-06-04_final
2019-06-04 11:13:31	ga_s2am_ard_3-2-1_51KZS_2019-06-04_final
2019-06-05 10:40:38	ga_s2am_ard_3-2-1_53LQG_2019-06-05_final.stac-item
2019-06-05 10:42:02	ga_s2am_ard_3-2-1_53KRA_2019-06-05_final
2019-06-05 10:43:07	ga_s2am_ard_3-2-1_53KPS_2019-06-05_final
2019-06-06 10:11:55	ga_s2am_ard_3-2-1_54KZF_2019-06-06_final
2019-06-06 11:53:41	ga_s2am_ard_3-2-1_50KNB_2019-06-06_final
2019-06-06 11:53:45	ga_s2am_ard_3-2-1_50KMB_2019-06-06_final
2019-06-06 11:53:49	ga_s2am_ard_3-2-1_50KNB_2019-06-06_final
2019-06-06 11:53:50	ga_s2am_ard_3-2-1_50KMB_2019-06-06_final
2019-06-07 11:22:25	ga_s2am_ard_3-2-1_51KZA_2019-06-07_final
2019-06-07 11:23:18	ga_s2am_ard_3-2-1_52KCB_2019-06-07_final
2019-06-07 11:23:30	ga_s2am_ard_3-2-1_51KXS_2019-06-07_final
2019-06-08 10:50:30	ga_s2am_ard_3-2-1_53LQG_2019-06-08_final.stac-item
2019-06-08 10:53:13	ga_s2am_ard_3-2-1_53KLS_2019-06-08_final
2019-06-09 10:23:05	ga_s2am_ard_3-2-1_54KUB_2019-06-09_final
2019-06-09 12:03:36	ga_s2am_ard_3-2-1_50KNB_2019-06-09_final
2019-06-09 12:03:40	ga_s2am_ard_3-2-1_50KMB_2019-06-09_final
2019-06-09 12:03:43	ga_s2am_ard_3-2-1_50KLB_2019-06-09_final
2019-06-10 09:52:48	ga_s2am_ard_3-2-1_55KFS_2019-06-10_final
2019-06-10 09:56:27	ga_s2am_ard_3-2-1_54HYH_2019-06-10_final
2019-06-10 11:33:30	ga_s2am_ard_3-2-1_51KWS_2019-06-10_final
2019-06-10 11:33:33	ga_s2am_ard_3-2-1_51KVS_2019-06-10_final
2019-06-10 11:33:37	ga_s2am_ard_3-2-1_51KUS_2019-06-10_final
2019-06-10 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-06-10_final
2019-06-11 11:00:46	ga_s2am_ard_3-2-1_53LKG_2019-06-11_final
2019-06-12 10:32:07	ga_s2am_ard_3-2-1_53KRA_2019-06-12_final
2019-06-12 10:33:01	ga_s2am_ard_3-2-1_54KUB_2019-06-12_final
2019-06-12 10:33:15	ga_s2am_ard_3-2-1_53KPS_2019-06-12_final
2019-06-13 10:02:54	ga_s2am_ard_3-2-1_55KCS_2019-06-13_final
2019-06-13 11:43:28	ga_s2am_ard_3-2-1_51KVS_2019-06-13_final
2019-06-13 11:43:32	ga_s2am_ard_3-2-1_51KUS_2019-06-13_final
2019-06-13 11:46:56	ga_s2am_ard_3-2-1_50HQH_2019-06-13_final
2019-06-14 11:13:19	ga_s2am_ard_3-2-1_52KDB_2019-06-14_final
2019-06-14 11:13:20	ga_s2am_ard_3-2-1_52KCB_2019-06-14_final
2019-06-14 11:13:24	ga_s2am_ard_3-2-1_52KEB_2019-06-14_final
2019-06-14 11:13:25	ga_s2am_ard_3-2-1_52KDB_2019-06-14_final
2019-06-14 11:13:27	ga_s2am_ard_3-2-1_52KCB_2019-06-14_final
2019-06-14 11:13:29	ga_s2am_ard_3-2-1_52KBB_2019-06-14_final
2019-06-14 11:13:32	ga_s2am_ard_3-2-1_51KZS_2019-06-14_final
2019-06-15 10:40:39	ga_s2am_ard_3-2-1_53LQG_2019-06-15_final.stac-item
2019-06-15 10:42:03	ga_s2am_ard_3-2-1_53KRA_2019-06-15_final
2019-06-15 10:43:08	ga_s2am_ard_3-2-1_53KPS_2019-06-15_final
2019-06-16 10:11:56	ga_s2am_ard_3-2-1_54KZF_2019-06-16_final
2019-06-16 11:53:42	ga_s2am_ard_3-2-1_50KNB_2019-06-16_final
2019-06-16 11:53:46	ga_s2am_ard_3-2-1_50KMB_2019-06-16_final
2019-06-16 11:53:52	ga_s2am_ard_3-2-1_50KMB_2019-06-16_final
2019-06-17 09:42:40	ga_s2am_ard_3-2-1_56KMB_2019-06-17_final.stac-item
2019-06-17 11:22:27	ga_s2am_ard_3-2-1_51KZA_2019-06-17_final
2019-06-17 11:23:20	ga_s2am_ard_3-2-1_52KCB_2019-06-17_final
2019-06-17 11:23:31	ga_s2am_ard_3-2-1_51KXS_2019-06-17_final
2019-06-18 10:50:31	ga_s2am_ard_3-2-1_53LQG_2019-06-18_final.stac-item
2019-06-18 10:53:14	ga_s2am_ard_3-2-1_53KLS_2019-06-18_final
2019-06-19 10:23:07	ga_s2am_ard_3-2-1_54KUB_2019-06-19_final
2019-06-19 12:03:37	ga_s2am_ard_3-2-1_50KNB_2019-06-19_final
2019-06-19 12:03:41	ga_s2am_ard_3-2-1_50KMB_2019-06-19_final
2019-06-19 12:03:45	ga_s2am_ard_3-2-1_50KLB_2019-06-19_final
2019-06-20 09:52:50	ga_s2am_ard_3-2-1_55KFS_2019-06-20_final
2019-06-20 09:56:28	ga_s2am_ard_3-2-1_54HYH_2019-06-20_final
2019-06-20 11:33:31	ga_s2am_ard_3-2-1_51KWS_2019-06-20_final
2019-06-20 11:33:34	ga_s2am_ard_3-2-1_51KVS_2019-06-20_final
2019-06-20 11:33:38	ga_s2am_ard_3-2-1_51KUS_2019-06-20_final
2019-06-20 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-06-20_final
2019-06-21 11:00:47	ga_s2am_ard_3-2-1_53LKG_2019-06-21_final
2019-06-23 11:43:29	ga_s2am_ard_3-2-1_51KVS_2019-06-23_final
2019-06-23 11:43:33	ga_s2am_ard_3-2-1_51KUS_2019-06-23_final
2019-06-24 11:13:21	ga_s2am_ard_3-2-1_52KCB_2019-06-24_final
2019-06-24 11:13:25	ga_s2am_ard_3-2-1_52KEB_2019-06-24_final
2019-06-24 11:13:28	ga_s2am_ard_3-2-1_52KCB_2019-06-24_final
2019-06-25 10:40:41	ga_s2am_ard_3-2-1_53LQG_2019-06-25_final.stac-item
2019-06-25 10:42:04	ga_s2am_ard_3-2-1_53KRA_2019-06-25_final
2019-06-25 10:43:09	ga_s2am_ard_3-2-1_53KPS_2019-06-25_final
2019-06-26 10:11:57	ga_s2am_ard_3-2-1_54KZF_2019-06-26_final
2019-06-26 10:13:02	ga_s2am_ard_3-2-1_54KXB_2019-06-26_final
2019-06-26 11:53:43	ga_s2am_ard_3-2-1_50KNB_2019-06-26_final
2019-06-26 11:53:47	ga_s2am_ard_3-2-1_50KMB_2019-06-26_final
2019-06-27 11:22:28	ga_s2am_ard_3-2-1_51KZA_2019-06-27_final
2019-06-27 11:23:21	ga_s2am_ard_3-2-1_52KCB_2019-06-27_final
2019-06-27 11:23:32	ga_s2am_ard_3-2-1_51KXS_2019-06-27_final
2019-06-28 10:50:32	ga_s2am_ard_3-2-1_53LQG_2019-06-28_final.stac-item
2019-06-28 10:53:15	ga_s2am_ard_3-2-1_53KLS_2019-06-28_final
2019-06-29 10:22:58	ga_s2am_ard_3-2-1_54KXB_2019-06-29_final
2019-06-29 10:23:08	ga_s2am_ard_3-2-1_54KUB_2019-06-29_final
2019-06-29 12:03:38	ga_s2am_ard_3-2-1_50KNB_2019-06-29_final
2019-06-29 12:03:42	ga_s2am_ard_3-2-1_50KMB_2019-06-29_final
2019-06-29 12:03:46	ga_s2am_ard_3-2-1_50KLB_2019-06-29_final
2019-06-30 09:52:51	ga_s2am_ard_3-2-1_55KFS_2019-06-30_final
2019-06-30 09:56:29	ga_s2am_ard_3-2-1_54HYH_2019-06-30_final
2019-06-30 11:33:32	ga_s2am_ard_3-2-1_51KWS_2019-06-30_final
2019-06-30 11:33:35	ga_s2am_ard_3-2-1_51KVS_2019-06-30_final

Return to ga_s2am_ard_3 across June 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

June

All days