Search ga_s2am_ard_3 across October 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
2022-10-01 10:24:25	ga_s2am_ard_3-2-1_54JWR_2022-10-01_final.stac-item
2022-10-01 10:24:38	ga_s2am_ard_3-2-1_54JUR_2022-10-01_final.stac-item
2022-10-01 10:25:56	ga_s2am_ard_3-2-1_53JQF_2022-10-01_final.stac-item
2022-10-02 09:54:30	ga_s2am_ard_3-2-1_55JCL_2022-10-02_final.stac-item
2022-10-02 11:35:01	ga_s2am_ard_3-2-1_51JWL_2022-10-02_final.stac-item
2022-10-02 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-10-02_final.stac-item
2022-10-02 11:35:08	ga_s2am_ard_3-2-1_51JUL_2022-10-02_final.stac-item
2022-10-03 09:24:16	ga_s2am_ard_3-2-1_56JNR_2022-10-02_final.stac-item
2022-10-03 11:04:54	ga_s2am_ard_3-2-1_52JER_2022-10-03_final.stac-item
2022-10-03 11:04:58	ga_s2am_ard_3-2-1_52JDR_2022-10-03_final.stac-item
2022-10-03 11:05:03	ga_s2am_ard_3-2-1_52JCR_2022-10-03_final.stac-item
2022-10-04 10:35:51	ga_s2am_ard_3-2-1_53JQF_2022-10-04_final.stac-item
2022-10-05 10:04:25	ga_s2am_ard_3-2-1_55JCL_2022-10-05_final.stac-item
2022-10-05 10:05:39	ga_s2am_ard_3-2-1_54JYL_2022-10-05_final.stac-item
2022-10-05 11:44:58	ga_s2am_ard_3-2-1_51JUL_2022-10-05_final.stac-item
2022-10-05 11:45:10	ga_s2am_ard_3-2-1_51JTL_2022-10-05_final.stac-item
2022-10-05 11:45:18	ga_s2am_ard_3-2-1_50JNR_2022-10-05_final.stac-item
2022-10-06 09:34:11	ga_s2am_ard_3-2-1_56JNR_2022-10-06_final.stac-item
2022-10-06 09:34:18	ga_s2am_ard_3-2-1_56JLR_2022-10-06_final.stac-item
2022-10-06 09:35:37	ga_s2am_ard_3-2-1_55JGF_2022-10-06_final.stac-item
2022-10-06 11:14:53	ga_s2am_ard_3-2-1_52JDR_2022-10-06_final.stac-item
2022-10-06 11:14:56	ga_s2am_ard_3-2-1_52JCR_2022-10-06_final.stac-item
2022-10-06 11:16:15	ga_s2am_ard_3-2-1_51JYF_2022-10-06_final.stac-item
2022-10-07 10:44:49	ga_s2am_ard_3-2-1_53JLL_2022-10-07_final.stac-item
2022-10-07 10:46:07	ga_s2am_ard_3-2-1_52JGL_2022-10-07_final.stac-item
2022-10-08 11:55:13	ga_s2am_ard_3-2-1_50JNR_2022-10-08_final.stac-item
2022-10-08 11:55:16	ga_s2am_ard_3-2-1_50JMR_2022-10-08_final.stac-item
2022-10-08 11:55:19	ga_s2am_ard_3-2-1_50JLR_2022-10-08_final.stac-item
2022-10-09 09:44:12	ga_s2am_ard_3-2-1_56JLR_2022-10-09_final.stac-item
2022-10-09 09:45:28	ga_s2am_ard_3-2-1_56JKL_2022-10-09_final.stac-item
2022-10-09 11:25:05	ga_s2am_ard_3-2-1_51JWL_2022-10-09_final.stac-item
2022-10-09 11:25:10	ga_s2am_ard_3-2-1_51JVL_2022-10-09_final.stac-item
2022-10-10 10:56:02	ga_s2am_ard_3-2-1_52JGL_2022-10-10_final.stac-item
2022-10-11 10:24:27	ga_s2am_ard_3-2-1_54JUR_2022-10-11_final.stac-item
2022-10-11 10:24:28	ga_s2am_ard_3-2-1_54JWR_2022-10-11_final.stac-item
2022-10-11 10:24:36	ga_s2am_ard_3-2-1_54JUR_2022-10-11_final.stac-item
2022-10-11 10:25:54	ga_s2am_ard_3-2-1_53JQF_2022-10-11_final.stac-item
2022-10-11 12:05:04	ga_s2am_ard_3-2-1_50JMR_2022-10-11_final.stac-item
2022-10-12 09:54:28	ga_s2am_ard_3-2-1_55JCL_2022-10-12_final.stac-item
2022-10-12 11:35:00	ga_s2am_ard_3-2-1_51JWL_2022-10-12_final.stac-item
2022-10-12 11:35:03	ga_s2am_ard_3-2-1_51JVL_2022-10-12_final.stac-item
2022-10-12 11:35:06	ga_s2am_ard_3-2-1_51JUL_2022-10-12_final.stac-item
2022-10-13 11:04:52	ga_s2am_ard_3-2-1_52JER_2022-10-13_final.stac-item
2022-10-13 11:04:55	ga_s2am_ard_3-2-1_52JDR_2022-10-13_final.stac-item
2022-10-13 11:05:01	ga_s2am_ard_3-2-1_52JCR_2022-10-13_final.stac-item
2022-10-14 10:35:49	ga_s2am_ard_3-2-1_53JQF_2022-10-14_final.stac-item
2022-10-15 10:04:23	ga_s2am_ard_3-2-1_55JCL_2022-10-15_final.stac-item
2022-10-15 10:05:37	ga_s2am_ard_3-2-1_54JYL_2022-10-15_final.stac-item
2022-10-15 11:44:55	ga_s2am_ard_3-2-1_51JUL_2022-10-15_final.stac-item
2022-10-15 11:45:07	ga_s2am_ard_3-2-1_51JTL_2022-10-15_final.stac-item
2022-10-15 11:45:16	ga_s2am_ard_3-2-1_50JNR_2022-10-15_final.stac-item
2022-10-16 09:34:15	ga_s2am_ard_3-2-1_56JLR_2022-10-16_final.stac-item
2022-10-16 09:35:34	ga_s2am_ard_3-2-1_55JGF_2022-10-16_final.stac-item
2022-10-16 11:14:50	ga_s2am_ard_3-2-1_52JDR_2022-10-16_final.stac-item
2022-10-16 11:14:53	ga_s2am_ard_3-2-1_52JCR_2022-10-16_final.stac-item
2022-10-16 11:16:12	ga_s2am_ard_3-2-1_51JYF_2022-10-16_final.stac-item
2022-10-17 10:44:45	ga_s2am_ard_3-2-1_53JLL_2022-10-17_final.stac-item
2022-10-17 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-10-17_final.stac-item
2022-10-18 11:55:09	ga_s2am_ard_3-2-1_50JNR_2022-10-18_final.stac-item
2022-10-18 11:55:15	ga_s2am_ard_3-2-1_50JLR_2022-10-18_final.stac-item
2022-10-19 09:44:08	ga_s2am_ard_3-2-1_56JLR_2022-10-19_final.stac-item
2022-10-19 09:45:24	ga_s2am_ard_3-2-1_56JKL_2022-10-19_final.stac-item
2022-10-19 11:25:01	ga_s2am_ard_3-2-1_51JWL_2022-10-19_final.stac-item
2022-10-19 11:25:06	ga_s2am_ard_3-2-1_51JVL_2022-10-19_final.stac-item
2022-10-20 10:54:39	ga_s2am_ard_3-2-1_53JLL_2022-10-20_final.stac-item
2022-10-20 10:55:58	ga_s2am_ard_3-2-1_52JGL_2022-10-20_final.stac-item
2022-10-21 10:24:32	ga_s2am_ard_3-2-1_54JUR_2022-10-21_final.stac-item
2022-10-21 10:25:50	ga_s2am_ard_3-2-1_53JQF_2022-10-21_final.stac-item
2022-10-22 09:54:25	ga_s2am_ard_3-2-1_55JCL_2022-10-22_final.stac-item
2022-10-22 11:34:56	ga_s2am_ard_3-2-1_51JWL_2022-10-22_final.stac-item
2022-10-22 11:35:00	ga_s2am_ard_3-2-1_51JVL_2022-10-22_final.stac-item
2022-10-22 11:35:03	ga_s2am_ard_3-2-1_51JUL_2022-10-22_final.stac-item
2022-10-23 11:04:49	ga_s2am_ard_3-2-1_52JER_2022-10-23_final.stac-item
2022-10-23 11:04:53	ga_s2am_ard_3-2-1_52JDR_2022-10-23_final.stac-item
2022-10-23 11:04:58	ga_s2am_ard_3-2-1_52JCR_2022-10-23_final.stac-item
2022-10-24 10:35:47	ga_s2am_ard_3-2-1_53JQF_2022-10-24_final.stac-item
2022-10-25 10:04:21	ga_s2am_ard_3-2-1_55JCL_2022-10-25_final.stac-item
2022-10-25 10:05:35	ga_s2am_ard_3-2-1_54JYL_2022-10-25_final.stac-item
2022-10-25 11:44:54	ga_s2am_ard_3-2-1_51JUL_2022-10-25_final.stac-item
2022-10-25 11:45:14	ga_s2am_ard_3-2-1_50JNR_2022-10-25_final.stac-item
2022-10-26 09:34:07	ga_s2am_ard_3-2-1_56JNR_2022-10-26_final.stac-item
2022-10-26 09:34:14	ga_s2am_ard_3-2-1_56JLR_2022-10-26_final.stac-item
2022-10-26 09:35:33	ga_s2am_ard_3-2-1_55JGF_2022-10-26_final.stac-item
2022-10-26 11:14:49	ga_s2am_ard_3-2-1_52JDR_2022-10-26_final.stac-item
2022-10-26 11:14:52	ga_s2am_ard_3-2-1_52JCR_2022-10-26_final.stac-item
2022-10-26 11:16:11	ga_s2am_ard_3-2-1_51JYF_2022-10-26_final.stac-item
2022-10-27 10:44:45	ga_s2am_ard_3-2-1_53JLL_2022-10-27_final.stac-item
2022-10-27 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-10-27_final.stac-item
2022-10-28 11:55:09	ga_s2am_ard_3-2-1_50JNR_2022-10-28_final.stac-item
2022-10-28 11:55:13	ga_s2am_ard_3-2-1_50JMR_2022-10-28_final.stac-item
2022-10-28 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-10-28_final.stac-item
2022-10-29 09:44:09	ga_s2am_ard_3-2-1_56JLR_2022-10-29_final.stac-item
2022-10-29 09:45:25	ga_s2am_ard_3-2-1_56JKL_2022-10-29_final.stac-item
2022-10-29 11:25:02	ga_s2am_ard_3-2-1_51JWL_2022-10-29_final.stac-item
2022-10-29 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-10-29_final.stac-item
2022-10-30 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-10-30_final.stac-item
2022-10-31 10:24:26	ga_s2am_ard_3-2-1_54JVR_2022-10-31_final.stac-item
2022-10-31 10:24:28	ga_s2am_ard_3-2-1_54JUR_2022-10-31_final.stac-item
2022-10-31 10:24:35	ga_s2am_ard_3-2-1_54JUR_2022-10-31_final.stac-item
2022-10-31 10:25:53	ga_s2am_ard_3-2-1_53JQF_2022-10-31_final.stac-item

Return to ga_s2am_ard_3 across October 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

October

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