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
2016-08-23 12:05:55	ga_s2am_ard_3-2-1_49JGH_2016-08-23_final.stac-item
2019-11-16 12:06:08	ga_s2am_ard_3-2-1_49JGH_2019-11-16_final.stac-item
2022-09-01 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-09-01_final.stac-item
2022-09-11 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-09-11_final.stac-item
2022-09-21 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-09-21_final.stac-item
2022-10-01 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-10-01_final.stac-item
2022-10-11 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2022-10-11_final.stac-item
2022-10-21 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-10-21_final.stac-item
2022-10-31 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-10-31_final.stac-item
2022-11-10 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2022-11-10_final.stac-item
2022-11-20 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-11-20_final.stac-item
2022-11-30 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-11-30_final.stac-item
2022-12-10 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2022-12-10_final.stac-item
2022-12-17 11:56:43	ga_s2am_ard_3-2-1_50HKK_2022-12-17_nrt.stac-item
2022-12-20 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2022-12-20_final.stac-item
2022-12-27 11:56:42	ga_s2am_ard_3-2-1_50HKK_2022-12-27_nrt.stac-item
2022-12-30 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2022-12-30_final.stac-item
2023-01-06 11:56:42	ga_s2am_ard_3-2-1_50HKK_2023-01-06_nrt.stac-item
2023-01-09 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-01-09_final.stac-item
2023-01-16 11:56:40	ga_s2am_ard_3-2-1_50HKK_2023-01-16_nrt.stac-item
2023-01-19 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2023-01-19_final.stac-item
2023-01-29 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-01-29_final.stac-item
2023-02-05 11:56:42	ga_s2am_ard_3-2-1_50HKK_2023-02-05_nrt.stac-item
2023-02-08 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-02-08_final.stac-item
2023-02-08 12:06:19	ga_s2am_ard_3-2-1_49JGG_2023-02-08_nrt.stac-item
2023-02-15 11:56:40	ga_s2am_ard_3-2-1_50HKK_2023-02-15_nrt.stac-item
2023-02-18 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-18_final.stac-item
2023-02-25 11:56:41	ga_s2am_ard_3-2-1_50HKK_2023-02-25_nrt.stac-item
2023-02-28 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-02-28_final.stac-item
2023-03-07 11:56:39	ga_s2am_ard_3-2-1_50HKK_2023-03-07_nrt.stac-item
2023-03-10 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2023-03-10_final.stac-item
2023-03-17 11:56:41	ga_s2am_ard_3-2-1_50HKK_2023-03-17_nrt.stac-item
2023-03-20 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-03-20_final.stac-item
2023-03-27 11:56:42	ga_s2am_ard_3-2-1_50HKK_2023-03-27_nrt.stac-item
2023-03-30 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-03-30_final.stac-item
2023-04-09 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-04-09_final.stac-item
2023-04-19 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-04-19_final.stac-item
2023-04-29 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-04-29_final.stac-item
2023-05-09 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-05-09_final.stac-item
2023-05-19 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-05-19_final.stac-item
2023-05-26 11:56:49	ga_s2am_ard_3-2-1_49HGE_2023-05-26_nrt.stac-item
2023-05-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2023-05-29_final.stac-item
2023-06-05 11:56:49	ga_s2am_ard_3-2-1_49HGE_2023-06-05_nrt.stac-item
2023-06-08 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2023-06-08_final.stac-item
2023-06-15 11:56:49	ga_s2am_ard_3-2-1_49HGE_2023-06-15_nrt.stac-item
2023-06-18 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2023-06-18_final.stac-item
2023-06-18 12:06:06	ga_s2am_ard_3-2-1_50JKN_2023-06-18_final.stac-item
2023-06-18 12:06:07	ga_s2am_ard_3-2-1_49JGH_2023-06-18_final.stac-item
2023-06-25 11:56:48	ga_s2am_ard_3-2-1_49HGE_2023-06-25_nrt.stac-item
2023-06-28 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2023-06-28_final.stac-item
2023-07-05 11:56:50	ga_s2am_ard_3-2-1_49HGE_2023-07-05_nrt.stac-item
2023-07-08 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2023-07-08_final.stac-item
2023-07-15 11:56:50	ga_s2am_ard_3-2-1_49HGE_2023-07-15_nrt.stac-item
2023-07-18 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2023-07-18_final.stac-item
2023-07-25 11:56:50	ga_s2am_ard_3-2-1_49HGE_2023-07-25_nrt.stac-item
2023-07-28 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2023-07-28_final.stac-item
2023-08-04 11:56:50	ga_s2am_ard_3-2-1_49HGE_2023-08-04_nrt.stac-item
2023-08-07 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2023-08-07_final.stac-item
2023-08-14 11:56:51	ga_s2am_ard_3-2-1_49HGE_2023-08-14_nrt.stac-item
2023-08-17 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-17_final.stac-item
2023-08-24 11:56:51	ga_s2am_ard_3-2-1_49HGE_2023-08-24_nrt.stac-item
2023-08-27 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2023-08-27_final.stac-item
2023-09-03 11:56:51	ga_s2am_ard_3-2-1_49HGE_2023-09-03_nrt.stac-item
2023-09-06 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2023-09-06_final.stac-item
2023-09-13 11:56:50	ga_s2am_ard_3-2-1_49HGE_2023-09-13_nrt.stac-item
2023-09-16 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2023-09-16_final.stac-item
2023-09-23 11:56:47	ga_s2am_ard_3-2-1_49HGE_2023-09-23_nrt.stac-item
2023-09-26 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-09-26_final.stac-item
2023-10-03 11:56:47	ga_s2am_ard_3-2-1_49HGE_2023-10-03_nrt.stac-item
2023-10-06 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2023-10-06_final.stac-item
2023-10-13 11:56:43	ga_s2am_ard_3-2-1_49HGE_2023-10-13_nrt.stac-item
2023-10-16 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-10-16_final.stac-item
2023-10-23 11:56:45	ga_s2am_ard_3-2-1_49HGE_2023-10-23_nrt.stac-item
2023-10-26 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-10-26_final.stac-item
2023-11-02 11:56:44	ga_s2am_ard_3-2-1_49HGE_2023-11-02_nrt.stac-item
2023-11-05 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2023-11-05_final.stac-item
2023-11-12 11:56:45	ga_s2am_ard_3-2-1_49HGE_2023-11-12_nrt.stac-item
2023-11-15 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-11-15_final.stac-item
2023-11-22 11:56:41	ga_s2am_ard_3-2-1_49HGE_2023-11-22_nrt.stac-item
2023-11-25 12:05:38	ga_s2am_ard_3-2-1_49JGJ_2023-11-25_final.stac-item
2023-12-02 11:56:37	ga_s2am_ard_3-2-1_49HGE_2023-12-02_nrt.stac-item
2023-12-05 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2023-12-05_final.stac-item
2023-12-12 11:56:41	ga_s2am_ard_3-2-1_49HGE_2023-12-12_nrt.stac-item
2023-12-15 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2023-12-15_final.stac-item
2023-12-22 11:56:41	ga_s2am_ard_3-2-1_49HGE_2023-12-22_nrt.stac-item
2023-12-25 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2023-12-25_final.stac-item
2024-01-01 11:56:42	ga_s2am_ard_3-2-1_49HGE_2024-01-01_nrt.stac-item
2024-01-04 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2024-01-04_final.stac-item
2024-01-11 11:56:40	ga_s2am_ard_3-2-1_49HGE_2024-01-11_nrt.stac-item
2024-01-14 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2024-01-14_final.stac-item
2024-01-21 11:56:37	ga_s2am_ard_3-2-1_49HGE_2024-01-21_nrt.stac-item
2024-01-24 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2024-01-24_final.stac-item
2024-01-31 11:56:41	ga_s2am_ard_3-2-1_49HGE_2024-01-31_nrt.stac-item
2024-03-01 11:56:46	ga_s2am_ard_3-2-1_49HGE_2024-03-01_nrt.stac-item
2024-03-11 11:56:39	ga_s2am_ard_3-2-1_50HKK_2024-03-11_nrt.stac-item
2024-03-11 11:56:40	ga_s2am_ard_3-2-1_49HGE_2024-03-11_nrt.stac-item
2024-03-11 11:56:47	ga_s2am_ard_3-2-1_49HGE_2024-03-11_nrt.stac-item
2024-03-21 11:56:41	ga_s2am_ard_3-2-1_49HGE_2024-03-21_nrt.stac-item
2024-03-21 11:56:47	ga_s2am_ard_3-2-1_49HGE_2024-03-21_nrt.stac-item
2024-03-31 11:56:44	ga_s2am_ard_3-2-1_49HGE_2024-03-31_nrt.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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