Search ga_s2am_ard_3 whole collection

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
2015-08-25 10:45:29	ga_s2am_ard_3-2-1_53JLH_2015-08-25_final.stac-item
2017-09-23 10:43:02	ga_s2am_ard_3-2-1_53JLF_2017-09-23_final
2017-10-13 10:43:05	ga_s2am_ard_3-2-1_53JLF_2017-10-13_final
2017-11-02 10:43:05	ga_s2am_ard_3-2-1_53JLF_2017-11-02_final
2017-11-22 10:43:02	ga_s2am_ard_3-2-1_53JLF_2017-11-22_final
2017-12-12 10:43:01	ga_s2am_ard_3-2-1_53JLF_2017-12-12_final
2018-01-01 10:42:59	ga_s2am_ard_3-2-1_53JLF_2018-01-01_final
2018-01-21 10:43:00	ga_s2am_ard_3-2-1_53JLF_2018-01-21_final
2018-02-10 10:43:02	ga_s2am_ard_3-2-1_53JLF_2018-02-10_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53JLF_2018-02-20_final
2018-03-02 10:37:24	ga_s2am_ard_3-2-1_53JLF_2018-03-02_final
2018-03-12 10:37:23	ga_s2am_ard_3-2-1_53JLF_2018-03-12_final
2018-03-22 10:37:24	ga_s2am_ard_3-2-1_53JLF_2018-03-22_final
2018-04-01 10:37:26	ga_s2am_ard_3-2-1_53JLF_2018-04-01_final
2018-04-11 10:37:28	ga_s2am_ard_3-2-1_53JLF_2018-04-11_final
2018-04-21 10:37:29	ga_s2am_ard_3-2-1_53JLF_2018-04-21_final
2018-05-01 10:37:29	ga_s2am_ard_3-2-1_53JLF_2018-05-01_final
2018-05-11 10:37:30	ga_s2am_ard_3-2-1_53JLF_2018-05-11_final
2018-05-21 10:37:29	ga_s2am_ard_3-2-1_53JLF_2018-05-21_final
2018-05-31 10:37:28	ga_s2am_ard_3-2-1_53JLF_2018-05-31_final
2018-06-10 10:37:27	ga_s2am_ard_3-2-1_53JLF_2018-06-10_final
2018-06-20 10:40:49	ga_s2am_ard_3-2-1_53JLF_2018-06-20_final
2018-06-30 10:37:28	ga_s2am_ard_3-2-1_53JLF_2018-06-30_final
2018-07-10 10:37:28	ga_s2am_ard_3-2-1_53JLF_2018-07-10_final
2018-07-20 10:37:28	ga_s2am_ard_3-2-1_53JLF_2018-07-20_final
2021-12-21 10:45:56	ga_s2am_ard_3-2-1_53JLF_2021-12-21_final
2021-12-31 10:45:57	ga_s2am_ard_3-2-1_53JLF_2021-12-31_final
2022-01-20 10:45:55	ga_s2am_ard_3-2-1_53JLF_2022-01-20_final
2022-01-30 10:45:55	ga_s2am_ard_3-2-1_53JLF_2022-01-30_final
2022-02-19 10:45:56	ga_s2am_ard_3-2-1_53JLF_2022-02-19_final
2022-03-01 10:45:58	ga_s2am_ard_3-2-1_53JLF_2022-03-01_final
2022-03-11 10:45:59	ga_s2am_ard_3-2-1_53JLF_2022-03-11_final
2022-03-21 10:45:58	ga_s2am_ard_3-2-1_53JLF_2022-03-21_final
2022-04-30 10:46:00	ga_s2am_ard_3-2-1_53JLF_2022-04-30_final
2022-06-09 10:46:04	ga_s2am_ard_3-2-1_53JLF_2022-06-09_final
2022-06-19 10:46:07	ga_s2am_ard_3-2-1_53JLF_2022-06-19_final
2022-06-29 10:46:08	ga_s2am_ard_3-2-1_53JLF_2022-06-29_final
2022-07-09 10:46:08	ga_s2am_ard_3-2-1_53JLF_2022-07-09_final
2022-07-19 10:46:07	ga_s2am_ard_3-2-1_53JLF_2022-07-19_final
2022-07-29 10:46:04	ga_s2am_ard_3-2-1_53JLF_2022-07-29_final
2022-08-08 10:46:06	ga_s2am_ard_3-2-1_53JLF_2022-08-08_final
2022-08-18 10:46:08	ga_s2am_ard_3-2-1_53JLF_2022-08-18_final
2022-08-28 10:46:07	ga_s2am_ard_3-2-1_53JLF_2022-08-28_final.stac-item
2022-09-07 10:46:06	ga_s2am_ard_3-2-1_53JLF_2022-09-07_final.stac-item
2022-09-17 10:46:04	ga_s2am_ard_3-2-1_53JLF_2022-09-17_final.stac-item
2022-09-27 10:46:02	ga_s2am_ard_3-2-1_53JLF_2022-09-27_final.stac-item
2022-10-07 10:46:02	ga_s2am_ard_3-2-1_53JLF_2022-10-07_final.stac-item
2022-12-06 10:45:55	ga_s2am_ard_3-2-1_53JLF_2022-12-06_final.stac-item
2022-12-26 10:45:48	ga_s2am_ard_3-2-1_53JLF_2022-12-26_final.stac-item
2022-12-26 10:45:55	ga_s2am_ard_3-2-1_53JLF_2022-12-26_final.stac-item
2023-01-05 10:45:54	ga_s2am_ard_3-2-1_53JLF_2023-01-05_final.stac-item
2023-01-15 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-01-15_final.stac-item
2023-01-25 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-01-25_final.stac-item
2023-02-04 10:45:54	ga_s2am_ard_3-2-1_53JLF_2023-02-04_final.stac-item
2023-02-14 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-02-14_final.stac-item
2023-02-24 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-02-24_final.stac-item
2023-03-06 10:45:51	ga_s2am_ard_3-2-1_53JLF_2023-03-06_final.stac-item
2023-03-16 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-03-16_final.stac-item
2023-03-26 10:45:53	ga_s2am_ard_3-2-1_53JLF_2023-03-26_final.stac-item
2023-04-05 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-04-05_final.stac-item
2023-04-15 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-04-15_final.stac-item
2023-04-25 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-04-25_final.stac-item
2023-05-05 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-05-05_final.stac-item
2023-05-15 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-05-15_final.stac-item
2023-05-25 10:45:58	ga_s2am_ard_3-2-1_53JLF_2023-05-25_final.stac-item
2023-06-04 10:45:59	ga_s2am_ard_3-2-1_53JLF_2023-06-04_final.stac-item
2023-06-14 10:45:59	ga_s2am_ard_3-2-1_53JLF_2023-06-14_final.stac-item
2023-06-24 10:45:58	ga_s2am_ard_3-2-1_53JLF_2023-06-24_final.stac-item
2023-07-04 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-07-04_final.stac-item
2023-07-14 10:46:02	ga_s2am_ard_3-2-1_53JLF_2023-07-14_final.stac-item
2023-07-24 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-07-24_final.stac-item
2023-08-03 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-08-03_final.stac-item
2023-08-13 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-08-13_final.stac-item
2023-08-23 10:46:01	ga_s2am_ard_3-2-1_53JLF_2023-08-23_final.stac-item
2023-09-02 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-09-02_final.stac-item
2023-09-12 10:46:00	ga_s2am_ard_3-2-1_53JLF_2023-09-12_final.stac-item
2023-09-22 10:45:56	ga_s2am_ard_3-2-1_53JLF_2023-09-22_final.stac-item
2023-10-12 10:45:53	ga_s2am_ard_3-2-1_53JLF_2023-10-12_final.stac-item
2023-10-22 10:45:55	ga_s2am_ard_3-2-1_53JLF_2023-10-22_final.stac-item
2023-11-01 10:45:54	ga_s2am_ard_3-2-1_53JLF_2023-11-01_final.stac-item
2023-11-11 10:45:54	ga_s2am_ard_3-2-1_53JLF_2023-11-11_final.stac-item
2023-11-21 10:45:52	ga_s2am_ard_3-2-1_53JLF_2023-11-21_final.stac-item
2023-12-01 10:45:46	ga_s2am_ard_3-2-1_53JLF_2023-12-01_final.stac-item
2023-12-11 10:45:50	ga_s2am_ard_3-2-1_53JLF_2023-12-11_final.stac-item
2023-12-31 10:45:54	ga_s2am_ard_3-2-1_53JLF_2023-12-31_final.stac-item
2024-01-10 10:45:29	ga_s2am_ard_3-2-1_53JLG_2024-01-10_final.stac-item
2024-01-10 10:45:50	ga_s2am_ard_3-2-1_53JLF_2024-01-10_final.stac-item
2024-01-20 10:45:46	ga_s2am_ard_3-2-1_53JLF_2024-01-20_final.stac-item
2024-01-30 10:45:50	ga_s2am_ard_3-2-1_53JLF_2024-01-30_final.stac-item
2024-02-09 10:45:51	ga_s2am_ard_3-2-1_53JLF_2024-02-09_final.stac-item
2024-02-19 10:45:53	ga_s2am_ard_3-2-1_53JLF_2024-02-19_final.stac-item
2024-02-29 10:45:55	ga_s2am_ard_3-2-1_53JLF_2024-02-29_final.stac-item
2024-03-10 10:45:55	ga_s2am_ard_3-2-1_53JLF_2024-03-10_final.stac-item
2024-03-20 10:45:56	ga_s2am_ard_3-2-1_53JLF_2024-03-20_final.stac-item
2024-03-30 10:45:55	ga_s2am_ard_3-2-1_53JLF_2024-03-30_final.stac-item
2024-04-09 10:45:55	ga_s2am_ard_3-2-1_53JLF_2024-04-09_final.stac-item
2024-04-19 10:45:58	ga_s2am_ard_3-2-1_53JLF_2024-04-19_final.stac-item
2024-04-29 10:45:58	ga_s2am_ard_3-2-1_53JLF_2024-04-29_final.stac-item
2024-05-09 10:45:57	ga_s2am_ard_3-2-1_53JLF_2024-05-09_final.stac-item
2024-05-19 10:45:56	ga_s2am_ard_3-2-1_53JLF_2024-05-19_final.stac-item

Return to ga_s2am_ard_3 whole collection 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

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