Search ga_s2am_ard_3 across May 2022

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
2022-05-01 10:14:44	ga_s2am_ard_3-2-1_54JXQ_2022-05-01_final
2022-05-01 10:16:00	ga_s2am_ard_3-2-1_54HWK_2022-05-01_final
2022-05-01 10:16:04	ga_s2am_ard_3-2-1_54HVK_2022-05-01_final
2022-05-02 09:45:49	ga_s2am_ard_3-2-1_55HFE_2022-05-02_final
2022-05-02 09:45:53	ga_s2am_ard_3-2-1_55HEE_2022-05-02_final
2022-05-02 11:26:27	ga_s2am_ard_3-2-1_51HXE_2022-05-02_final
2022-05-04 10:24:50	ga_s2am_ard_3-2-1_54JUQ_2022-05-04_final
2022-05-04 10:26:02	ga_s2am_ard_3-2-1_54HUK_2022-05-04_final
2022-05-04 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-05-04_final
2022-05-05 09:54:42	ga_s2am_ard_3-2-1_55JCK_2022-05-05_final
2022-05-05 09:55:47	ga_s2am_ard_3-2-1_55HEE_2022-05-05_final
2022-05-05 11:36:31	ga_s2am_ard_3-2-1_51HUE_2022-05-05_final
2022-05-05 11:36:36	ga_s2am_ard_3-2-1_50HPK_2022-05-05_final
2022-05-05 11:36:38	ga_s2am_ard_3-2-1_51HUE_2022-05-05_final
2022-05-05 11:36:43	ga_s2am_ard_3-2-1_50HPK_2022-05-05_final
2022-05-06 09:24:14	ga_s2am_ard_3-2-1_56JNR_2022-05-05_final.stac-item
2022-05-06 11:04:56	ga_s2am_ard_3-2-1_52JFQ_2022-05-06_final
2022-05-06 11:05:03	ga_s2am_ard_3-2-1_52JFQ_2022-05-06_final
2022-05-06 11:05:13	ga_s2am_ard_3-2-1_52JCQ_2022-05-06_final
2022-05-06 11:05:24	ga_s2am_ard_3-2-1_52JDP_2022-05-06_final
2022-05-08 10:04:37	ga_s2am_ard_3-2-1_55JCK_2022-05-08_final
2022-05-08 10:04:48	ga_s2am_ard_3-2-1_54JXQ_2022-05-08_final
2022-05-08 10:06:03	ga_s2am_ard_3-2-1_54HWK_2022-05-08_final
2022-05-08 11:45:25	ga_s2am_ard_3-2-1_50JPQ_2022-05-08_final
2022-05-08 11:46:38	ga_s2am_ard_3-2-1_50HPK_2022-05-08_final
2022-05-09 09:34:09	ga_s2am_ard_3-2-1_56JNR_2022-05-09_final.stac-item
2022-05-09 11:15:08	ga_s2am_ard_3-2-1_52JCQ_2022-05-09_final
2022-05-09 11:15:16	ga_s2am_ard_3-2-1_52JDP_2022-05-09_final
2022-05-09 11:16:20	ga_s2am_ard_3-2-1_52HCK_2022-05-09_final.stac-item
2022-05-09 11:16:30	ga_s2am_ard_3-2-1_51HXE_2022-05-09_final
2022-05-10 10:45:00	ga_s2am_ard_3-2-1_53JLK_2022-05-10_final
2022-05-10 10:46:10	ga_s2am_ard_3-2-1_53HME_2022-05-10_final
2022-05-11 10:14:43	ga_s2am_ard_3-2-1_54JXQ_2022-05-11_final
2022-05-11 10:15:59	ga_s2am_ard_3-2-1_54HWK_2022-05-11_final
2022-05-11 10:16:02	ga_s2am_ard_3-2-1_54HVK_2022-05-11_final
2022-05-11 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-05-11_final
2022-05-12 09:45:47	ga_s2am_ard_3-2-1_55HFE_2022-05-12_final
2022-05-12 09:45:51	ga_s2am_ard_3-2-1_55HEE_2022-05-12_final
2022-05-12 11:26:25	ga_s2am_ard_3-2-1_51HXE_2022-05-12_final
2022-05-13 10:55:03	ga_s2am_ard_3-2-1_53JLK_2022-05-13_final
2022-05-13 10:56:25	ga_s2am_ard_3-2-1_52HDK_2022-05-13_final.stac-item
2022-05-14 10:24:49	ga_s2am_ard_3-2-1_54JUQ_2022-05-14_final
2022-05-14 10:26:00	ga_s2am_ard_3-2-1_54HUK_2022-05-14_final
2022-05-14 10:26:07	ga_s2am_ard_3-2-1_54HUK_2022-05-14_final
2022-05-14 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2022-05-14_final
2022-05-15 09:54:42	ga_s2am_ard_3-2-1_55JCK_2022-05-15_final
2022-05-15 09:55:47	ga_s2am_ard_3-2-1_55HEE_2022-05-15_final
2022-05-15 11:36:33	ga_s2am_ard_3-2-1_51HUE_2022-05-15_final
2022-05-15 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-05-15_final
2022-05-16 09:24:14	ga_s2am_ard_3-2-1_56JNR_2022-05-15_final.stac-item
2022-05-16 11:05:02	ga_s2am_ard_3-2-1_52JFQ_2022-05-16_final
2022-05-16 11:05:13	ga_s2am_ard_3-2-1_52JCQ_2022-05-16_final
2022-05-16 11:05:24	ga_s2am_ard_3-2-1_52JDP_2022-05-16_final
2022-05-18 10:04:38	ga_s2am_ard_3-2-1_55JCK_2022-05-18_final
2022-05-18 10:04:49	ga_s2am_ard_3-2-1_54JXQ_2022-05-18_final
2022-05-18 10:06:04	ga_s2am_ard_3-2-1_54HWK_2022-05-18_final
2022-05-18 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2022-05-18_final
2022-05-18 11:46:39	ga_s2am_ard_3-2-1_50HPK_2022-05-18_final
2022-05-19 11:15:10	ga_s2am_ard_3-2-1_52JCQ_2022-05-19_final
2022-05-19 11:15:18	ga_s2am_ard_3-2-1_52JDP_2022-05-19_final
2022-05-19 11:16:22	ga_s2am_ard_3-2-1_52HCK_2022-05-19_final.stac-item
2022-05-19 11:16:32	ga_s2am_ard_3-2-1_51HXE_2022-05-19_final
2022-05-20 10:45:01	ga_s2am_ard_3-2-1_53JLK_2022-05-20_final
2022-05-20 10:45:07	ga_s2am_ard_3-2-1_53JLK_2022-05-20_final
2022-05-20 10:46:12	ga_s2am_ard_3-2-1_53HME_2022-05-20_final
2022-05-21 10:14:45	ga_s2am_ard_3-2-1_54JXQ_2022-05-21_final
2022-05-21 10:16:01	ga_s2am_ard_3-2-1_54HWK_2022-05-21_final
2022-05-21 10:16:05	ga_s2am_ard_3-2-1_54HVK_2022-05-21_final
2022-05-22 09:45:51	ga_s2am_ard_3-2-1_55HFE_2022-05-22_final
2022-05-22 09:45:54	ga_s2am_ard_3-2-1_55HEE_2022-05-22_final
2022-05-22 11:26:29	ga_s2am_ard_3-2-1_51HXE_2022-05-22_final
2022-05-23 10:54:59	ga_s2am_ard_3-2-1_53JLK_2022-05-23_final
2022-05-23 10:55:07	ga_s2am_ard_3-2-1_53JLK_2022-05-23_final
2022-05-24 10:24:52	ga_s2am_ard_3-2-1_54JUQ_2022-05-24_final
2022-05-24 10:26:04	ga_s2am_ard_3-2-1_54HUK_2022-05-24_final
2022-05-24 10:26:12	ga_s2am_ard_3-2-1_54HUK_2022-05-24_final
2022-05-24 12:05:30	ga_s2am_ard_3-2-1_50JLQ_2022-05-24_final
2022-05-25 09:54:45	ga_s2am_ard_3-2-1_55JCK_2022-05-25_final
2022-05-25 09:55:50	ga_s2am_ard_3-2-1_55HEE_2022-05-25_final
2022-05-25 11:36:35	ga_s2am_ard_3-2-1_51HUE_2022-05-25_final
2022-05-25 11:36:45	ga_s2am_ard_3-2-1_50HPK_2022-05-25_final
2022-05-26 11:05:05	ga_s2am_ard_3-2-1_52JFQ_2022-05-26_final
2022-05-26 11:05:15	ga_s2am_ard_3-2-1_52JCQ_2022-05-26_final
2022-05-26 11:05:27	ga_s2am_ard_3-2-1_52JDP_2022-05-26_final
2022-05-26 11:06:28	ga_s2am_ard_3-2-1_52HCK_2022-05-26_final.stac-item
2022-05-28 10:04:41	ga_s2am_ard_3-2-1_55JCK_2022-05-28_final
2022-05-28 10:04:51	ga_s2am_ard_3-2-1_54JXQ_2022-05-28_final
2022-05-28 10:06:06	ga_s2am_ard_3-2-1_54HWK_2022-05-28_final
2022-05-28 11:45:29	ga_s2am_ard_3-2-1_50JPQ_2022-05-28_final
2022-05-28 11:46:41	ga_s2am_ard_3-2-1_50HPK_2022-05-28_final
2022-05-29 09:34:12	ga_s2am_ard_3-2-1_56JNR_2022-05-29_final.stac-item
2022-05-29 11:15:11	ga_s2am_ard_3-2-1_52JCQ_2022-05-29_final
2022-05-29 11:15:20	ga_s2am_ard_3-2-1_52JDP_2022-05-29_final
2022-05-29 11:16:34	ga_s2am_ard_3-2-1_51HXE_2022-05-29_final
2022-05-30 10:45:03	ga_s2am_ard_3-2-1_53JLK_2022-05-30_final
2022-05-30 10:45:09	ga_s2am_ard_3-2-1_53JLK_2022-05-30_final
2022-05-30 10:46:14	ga_s2am_ard_3-2-1_53HME_2022-05-30_final
2022-05-31 10:14:47	ga_s2am_ard_3-2-1_54JXQ_2022-05-31_final
2022-05-31 10:16:03	ga_s2am_ard_3-2-1_54HWK_2022-05-31_final
2022-05-31 10:16:06	ga_s2am_ard_3-2-1_54HVK_2022-05-31_final

Return to ga_s2am_ard_3 across May 2022 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

2022

May

All days