Search ga_s2am_ard_3 across January 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
2022-01-01 10:14:41	ga_s2am_ard_3-2-1_54JXQ_2022-01-01_final
2022-01-01 10:15:51	ga_s2am_ard_3-2-1_54HXK_2022-01-01_final
2022-01-01 11:55:08	ga_s2am_ard_3-2-1_50JNR_2022-01-01_final
2022-01-01 11:55:17	ga_s2am_ard_3-2-1_50JPQ_2022-01-01_final
2022-01-01 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-01-01_final
2022-01-02 09:45:31	ga_s2am_ard_3-2-1_55JFF_2022-01-02_final
2022-01-02 09:46:43	ga_s2am_ard_3-2-1_55HFA_2022-01-02_final
2022-01-02 09:46:54	ga_s2am_ard_3-2-1_55HCA_2022-01-02_final
2022-01-02 11:25:05	ga_s2am_ard_3-2-1_51JVL_2022-01-02_final
2022-01-02 11:25:11	ga_s2am_ard_3-2-1_51JXK_2022-01-02_final
2022-01-03 10:55:04	ga_s2am_ard_3-2-1_52JFQ_2022-01-03_final
2022-01-05 09:56:50	ga_s2am_ard_3-2-1_55HCA_2022-01-05_final
2022-01-05 09:56:59	ga_s2am_ard_3-2-1_54HXF_2022-01-05_final
2022-01-05 11:34:54	ga_s2am_ard_3-2-1_51JVL_2022-01-05_final
2022-01-05 11:35:01	ga_s2am_ard_3-2-1_51JVL_2022-01-05_final
2022-01-06 11:04:52	ga_s2am_ard_3-2-1_52JDR_2022-01-06_final
2022-01-06 11:04:59	ga_s2am_ard_3-2-1_52JFQ_2022-01-06_final
2022-01-07 10:34:52	ga_s2am_ard_3-2-1_53JPK_2022-01-07_final
2022-01-07 10:35:50	ga_s2am_ard_3-2-1_53JPF_2022-01-07_final
2022-01-07 10:37:10	ga_s2am_ard_3-2-1_53HPV_2022-01-07_final.stac-item
2022-01-08 10:04:34	ga_s2am_ard_3-2-1_55JCK_2022-01-08_final
2022-01-08 10:05:57	ga_s2am_ard_3-2-1_54HXK_2022-01-08_final
2022-01-08 10:06:55	ga_s2am_ard_3-2-1_54HXF_2022-01-08_final
2022-01-08 11:45:13	ga_s2am_ard_3-2-1_50JNR_2022-01-08_final
2022-01-08 11:45:23	ga_s2am_ard_3-2-1_50JPQ_2022-01-08_final
2022-01-08 11:46:42	ga_s2am_ard_3-2-1_50HMK_2022-01-08_final
2022-01-09 09:36:47	ga_s2am_ard_3-2-1_55HFA_2022-01-09_final
2022-01-09 11:14:47	ga_s2am_ard_3-2-1_52JDR_2022-01-09_final
2022-01-09 11:16:04	ga_s2am_ard_3-2-1_52JCL_2022-01-09_final
2022-01-09 11:16:13	ga_s2am_ard_3-2-1_51JXF_2022-01-09_final
2022-01-09 11:16:17	ga_s2am_ard_3-2-1_52HCK_2022-01-09_final.stac-item
2022-01-09 11:16:32	ga_s2am_ard_3-2-1_51HWE_2022-01-09_final
2022-01-11 10:15:51	ga_s2am_ard_3-2-1_54HXK_2022-01-11_final
2022-01-11 11:55:07	ga_s2am_ard_3-2-1_50JNR_2022-01-11_final
2022-01-11 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-01-11_final
2022-01-12 09:45:31	ga_s2am_ard_3-2-1_55JFF_2022-01-12_final
2022-01-12 09:46:43	ga_s2am_ard_3-2-1_55HFA_2022-01-12_final
2022-01-12 11:25:04	ga_s2am_ard_3-2-1_51JVL_2022-01-12_final
2022-01-12 11:25:11	ga_s2am_ard_3-2-1_51JXK_2022-01-12_final
2022-01-12 11:26:27	ga_s2am_ard_3-2-1_51HWE_2022-01-12_final
2022-01-13 10:55:03	ga_s2am_ard_3-2-1_52JFQ_2022-01-13_final
2022-01-14 10:25:53	ga_s2am_ard_3-2-1_53JPF_2022-01-14_final
2022-01-14 10:27:06	ga_s2am_ard_3-2-1_53HPA_2022-01-14_final
2022-01-15 09:56:58	ga_s2am_ard_3-2-1_54HXF_2022-01-15_final
2022-01-15 11:34:59	ga_s2am_ard_3-2-1_51JVL_2022-01-15_final
2022-01-16 11:04:51	ga_s2am_ard_3-2-1_52JDR_2022-01-16_final
2022-01-16 11:04:54	ga_s2am_ard_3-2-1_52JFQ_2022-01-16_final
2022-01-16 11:04:57	ga_s2am_ard_3-2-1_52JDR_2022-01-16_final
2022-01-16 11:05:01	ga_s2am_ard_3-2-1_52JFQ_2022-01-16_final
2022-01-17 10:34:51	ga_s2am_ard_3-2-1_53JPK_2022-01-17_final
2022-01-17 10:34:58	ga_s2am_ard_3-2-1_53JPK_2022-01-17_final
2022-01-17 10:35:49	ga_s2am_ard_3-2-1_53JPF_2022-01-17_final
2022-01-17 10:36:59	ga_s2am_ard_3-2-1_53HPA_2022-01-17_final
2022-01-18 10:04:33	ga_s2am_ard_3-2-1_55JCK_2022-01-18_final
2022-01-18 10:05:56	ga_s2am_ard_3-2-1_54HXK_2022-01-18_final
2022-01-18 10:06:54	ga_s2am_ard_3-2-1_54HXF_2022-01-18_final
2022-01-18 11:45:12	ga_s2am_ard_3-2-1_50JNR_2022-01-18_final
2022-01-18 11:45:22	ga_s2am_ard_3-2-1_50JPQ_2022-01-18_final
2022-01-18 11:46:41	ga_s2am_ard_3-2-1_50HMK_2022-01-18_final
2022-01-19 11:14:46	ga_s2am_ard_3-2-1_52JDR_2022-01-19_final
2022-01-19 11:16:12	ga_s2am_ard_3-2-1_51JXF_2022-01-19_final
2022-01-19 11:16:31	ga_s2am_ard_3-2-1_51HWE_2022-01-19_final
2022-01-21 10:14:39	ga_s2am_ard_3-2-1_54JXQ_2022-01-21_final
2022-01-21 10:15:50	ga_s2am_ard_3-2-1_54HXK_2022-01-21_final
2022-01-21 11:55:06	ga_s2am_ard_3-2-1_50JNR_2022-01-21_final
2022-01-21 11:55:16	ga_s2am_ard_3-2-1_50JPQ_2022-01-21_final
2022-01-21 11:56:36	ga_s2am_ard_3-2-1_50HMK_2022-01-21_final
2022-01-22 09:45:30	ga_s2am_ard_3-2-1_55JFF_2022-01-22_final
2022-01-22 09:46:42	ga_s2am_ard_3-2-1_55HFA_2022-01-22_final
2022-01-22 11:25:03	ga_s2am_ard_3-2-1_51JVL_2022-01-22_final
2022-01-22 11:25:09	ga_s2am_ard_3-2-1_51JXK_2022-01-22_final
2022-01-22 11:26:26	ga_s2am_ard_3-2-1_51HWE_2022-01-22_final
2022-01-22 11:26:29	ga_s2am_ard_3-2-1_51HVE_2022-01-22_final
2022-01-23 10:55:02	ga_s2am_ard_3-2-1_52JFQ_2022-01-23_final
2022-01-24 10:25:47	ga_s2am_ard_3-2-1_53JPF_2022-01-24_final
2022-01-24 10:25:53	ga_s2am_ard_3-2-1_53JPF_2022-01-24_final
2022-01-24 10:27:05	ga_s2am_ard_3-2-1_53HPA_2022-01-24_final
2022-01-25 09:56:57	ga_s2am_ard_3-2-1_54HXF_2022-01-25_final
2022-01-25 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-01-25_final
2022-01-25 11:36:23	ga_s2am_ard_3-2-1_51HVE_2022-01-25_final
2022-01-26 11:04:50	ga_s2am_ard_3-2-1_52JDR_2022-01-26_final
2022-01-26 11:04:58	ga_s2am_ard_3-2-1_52JFQ_2022-01-26_final
2022-01-27 10:34:51	ga_s2am_ard_3-2-1_53JPK_2022-01-27_final
2022-01-27 10:35:49	ga_s2am_ard_3-2-1_53JPF_2022-01-27_final
2022-01-27 10:36:59	ga_s2am_ard_3-2-1_53HPA_2022-01-27_final
2022-01-28 10:04:33	ga_s2am_ard_3-2-1_55JCK_2022-01-28_final
2022-01-28 10:05:56	ga_s2am_ard_3-2-1_54HXK_2022-01-28_final
2022-01-28 10:06:53	ga_s2am_ard_3-2-1_54HXF_2022-01-28_final
2022-01-28 11:45:11	ga_s2am_ard_3-2-1_50JNR_2022-01-28_final
2022-01-28 11:45:21	ga_s2am_ard_3-2-1_50JPQ_2022-01-28_final
2022-01-28 11:46:41	ga_s2am_ard_3-2-1_50HMK_2022-01-28_final
2022-01-29 09:36:46	ga_s2am_ard_3-2-1_55HFA_2022-01-29_final
2022-01-29 11:14:46	ga_s2am_ard_3-2-1_52JDR_2022-01-29_final
2022-01-29 11:16:02	ga_s2am_ard_3-2-1_52JCL_2022-01-29_final
2022-01-29 11:16:12	ga_s2am_ard_3-2-1_51JXF_2022-01-29_final
2022-01-29 11:16:16	ga_s2am_ard_3-2-1_52HCK_2022-01-29_final.stac-item
2022-01-29 11:16:31	ga_s2am_ard_3-2-1_51HWE_2022-01-29_final
2022-01-31 10:14:39	ga_s2am_ard_3-2-1_54JXQ_2022-01-31_final
2022-01-31 10:15:50	ga_s2am_ard_3-2-1_54HXK_2022-01-31_final
2022-01-31 11:55:06	ga_s2am_ard_3-2-1_50JNR_2022-01-31_final

Return to ga_s2am_ard_3 across January 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

January

All days