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
2019-03-08 11:56:31	ga_s2am_ard_3-2-1_50HMK_2019-03-08_final
2019-04-17 11:56:39	ga_s2am_ard_3-2-1_50HMK_2019-04-17_final
2019-06-06 11:56:38	ga_s2am_ard_3-2-1_50HMK_2019-06-06_final
2019-12-13 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-12-13_final
2019-12-23 11:56:31	ga_s2am_ard_3-2-1_50HMK_2019-12-23_final
2020-01-12 11:56:31	ga_s2am_ard_3-2-1_50HMK_2020-01-12_final
2020-01-22 11:56:30	ga_s2am_ard_3-2-1_50HMK_2020-01-22_final
2020-02-11 11:56:29	ga_s2am_ard_3-2-1_50HMK_2020-02-11_final
2020-03-02 11:56:32	ga_s2am_ard_3-2-1_50HMK_2020-03-02_final
2020-03-12 11:56:33	ga_s2am_ard_3-2-1_50HMK_2020-03-12_final
2020-04-01 11:56:32	ga_s2am_ard_3-2-1_50HMK_2020-04-01_final
2020-08-19 11:56:42	ga_s2am_ard_3-2-1_50HMK_2020-08-19_final
2020-10-15 11:46:46	ga_s2am_ard_3-2-1_50HMK_2020-10-15_final
2022-12-14 11:47:34	ga_s2am_ard_3-2-1_50HMF_2022-12-14_nrt.stac-item
2022-12-17 11:57:28	ga_s2am_ard_3-2-1_50HMF_2022-12-17_nrt.stac-item
2022-12-24 11:47:32	ga_s2am_ard_3-2-1_50HMF_2022-12-24_nrt.stac-item
2022-12-27 11:57:27	ga_s2am_ard_3-2-1_50HMF_2022-12-27_nrt.stac-item
2023-01-03 11:47:33	ga_s2am_ard_3-2-1_50HMF_2023-01-03_nrt.stac-item
2023-01-06 11:57:27	ga_s2am_ard_3-2-1_50HMF_2023-01-06_nrt.stac-item
2023-01-13 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-01-13_nrt.stac-item
2023-01-16 11:57:25	ga_s2am_ard_3-2-1_50HMF_2023-01-16_nrt.stac-item
2023-01-23 11:47:30	ga_s2am_ard_3-2-1_50HMF_2023-01-23_nrt.stac-item
2023-01-26 11:57:26	ga_s2am_ard_3-2-1_50HMF_2023-01-26_nrt.stac-item
2023-02-02 11:47:30	ga_s2am_ard_3-2-1_50HMF_2023-02-02_nrt.stac-item
2023-02-05 11:57:27	ga_s2am_ard_3-2-1_50HMF_2023-02-05_nrt.stac-item
2023-02-12 11:47:32	ga_s2am_ard_3-2-1_50HMF_2023-02-12_nrt.stac-item
2023-02-15 11:57:26	ga_s2am_ard_3-2-1_50HMF_2023-02-15_nrt.stac-item
2023-02-22 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-02-22_nrt.stac-item
2023-02-25 11:57:26	ga_s2am_ard_3-2-1_50HMF_2023-02-25_nrt.stac-item
2023-03-04 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-03-04_nrt.stac-item
2023-03-07 11:57:24	ga_s2am_ard_3-2-1_50HMF_2023-03-07_nrt.stac-item
2023-03-14 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-03-14_nrt.stac-item
2023-03-17 11:57:26	ga_s2am_ard_3-2-1_50HMF_2023-03-17_nrt.stac-item
2023-03-24 11:47:30	ga_s2am_ard_3-2-1_50HMF_2023-03-24_nrt.stac-item
2023-03-27 11:57:27	ga_s2am_ard_3-2-1_50HMF_2023-03-27_nrt.stac-item
2023-04-03 11:47:33	ga_s2am_ard_3-2-1_50HMF_2023-04-03_nrt.stac-item
2023-04-06 11:57:28	ga_s2am_ard_3-2-1_50HMF_2023-04-06_nrt.stac-item
2023-04-13 11:47:33	ga_s2am_ard_3-2-1_50HMF_2023-04-13_nrt.stac-item
2023-04-16 11:57:27	ga_s2am_ard_3-2-1_50HMF_2023-04-16_nrt.stac-item
2023-04-23 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-04-23_nrt.stac-item
2023-05-03 11:47:32	ga_s2am_ard_3-2-1_50HMF_2023-05-03_nrt.stac-item
2023-05-13 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-05-13_nrt.stac-item
2023-05-23 11:47:36	ga_s2am_ard_3-2-1_50HMF_2023-05-23_nrt.stac-item
2023-06-02 11:47:37	ga_s2am_ard_3-2-1_50HMF_2023-06-02_nrt.stac-item
2023-06-05 11:57:31	ga_s2am_ard_3-2-1_50HMF_2023-06-05_nrt.stac-item
2023-06-12 11:47:37	ga_s2am_ard_3-2-1_50HMF_2023-06-12_nrt.stac-item
2023-06-22 11:47:35	ga_s2am_ard_3-2-1_50HMF_2023-06-22_nrt.stac-item
2023-07-02 11:47:36	ga_s2am_ard_3-2-1_50HMF_2023-07-02_nrt.stac-item
2023-07-12 11:47:37	ga_s2am_ard_3-2-1_50HMF_2023-07-12_nrt.stac-item
2023-07-22 11:47:36	ga_s2am_ard_3-2-1_50HMF_2023-07-22_nrt.stac-item
2023-07-25 11:57:32	ga_s2am_ard_3-2-1_50HMF_2023-07-25_nrt.stac-item
2023-08-01 11:47:37	ga_s2am_ard_3-2-1_50HMF_2023-08-01_nrt.stac-item
2023-08-11 11:47:36	ga_s2am_ard_3-2-1_50HMF_2023-08-11_nrt.stac-item
2023-08-14 11:57:32	ga_s2am_ard_3-2-1_50HMF_2023-08-14_nrt.stac-item
2023-08-21 11:47:38	ga_s2am_ard_3-2-1_50HMF_2023-08-21_nrt.stac-item
2023-08-31 11:47:37	ga_s2am_ard_3-2-1_50HMF_2023-08-31_nrt.stac-item
2023-09-03 11:57:32	ga_s2am_ard_3-2-1_50HMF_2023-09-03_nrt.stac-item
2023-09-10 11:47:38	ga_s2am_ard_3-2-1_50HMF_2023-09-10_nrt.stac-item
2023-09-20 11:47:34	ga_s2am_ard_3-2-1_50HMF_2023-09-20_nrt.stac-item
2023-09-23 11:57:29	ga_s2am_ard_3-2-1_50HMF_2023-09-23_nrt.stac-item
2023-09-30 11:47:34	ga_s2am_ard_3-2-1_50HMF_2023-09-30_nrt.stac-item
2023-10-03 11:57:29	ga_s2am_ard_3-2-1_50HMF_2023-10-03_nrt.stac-item
2023-10-10 11:47:32	ga_s2am_ard_3-2-1_50HMF_2023-10-10_nrt.stac-item
2023-10-13 11:57:25	ga_s2am_ard_3-2-1_50HMF_2023-10-13_nrt.stac-item
2023-10-20 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-10-20_nrt.stac-item
2023-10-23 11:57:27	ga_s2am_ard_3-2-1_50HMF_2023-10-23_nrt.stac-item
2023-10-30 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-10-30_nrt.stac-item
2023-11-02 11:57:26	ga_s2am_ard_3-2-1_50HMF_2023-11-02_nrt.stac-item
2023-11-09 11:47:31	ga_s2am_ard_3-2-1_50HMF_2023-11-09_nrt.stac-item
2023-11-19 11:47:29	ga_s2am_ard_3-2-1_50HMF_2023-11-19_nrt.stac-item
2023-11-29 11:47:25	ga_s2am_ard_3-2-1_50HMF_2023-11-29_final.stac-item
2023-12-02 11:57:19	ga_s2am_ard_3-2-1_50HMF_2023-12-02_final.stac-item
2023-12-09 11:47:26	ga_s2am_ard_3-2-1_50HMF_2023-12-09_final.stac-item
2023-12-12 11:57:22	ga_s2am_ard_3-2-1_50HMF_2023-12-12_final.stac-item
2023-12-19 11:47:28	ga_s2am_ard_3-2-1_50HMF_2023-12-19_final.stac-item
2023-12-29 11:47:30	ga_s2am_ard_3-2-1_50HMF_2023-12-29_final.stac-item
2024-01-08 11:47:27	ga_s2am_ard_3-2-1_50HMF_2024-01-08_final.stac-item
2024-01-11 11:57:22	ga_s2am_ard_3-2-1_50HMF_2024-01-11_final.stac-item
2024-01-18 11:47:24	ga_s2am_ard_3-2-1_50HMF_2024-01-18_final.stac-item
2024-01-28 11:47:26	ga_s2am_ard_3-2-1_50HMF_2024-01-28_final.stac-item
2024-01-31 11:57:22	ga_s2am_ard_3-2-1_50HMF_2024-01-31_final.stac-item
2024-02-07 11:47:27	ga_s2am_ard_3-2-1_50HMF_2024-02-07_final.stac-item
2024-02-10 11:57:23	ga_s2am_ard_3-2-1_50HMF_2024-02-10_final.stac-item
2024-02-17 11:47:29	ga_s2am_ard_3-2-1_50HMF_2024-02-17_final.stac-item
2024-02-20 11:57:25	ga_s2am_ard_3-2-1_50HMF_2024-02-20_final.stac-item
2024-02-27 11:47:31	ga_s2am_ard_3-2-1_50HMF_2024-02-27_final.stac-item
2024-03-01 11:57:27	ga_s2am_ard_3-2-1_50HMF_2024-03-01_final.stac-item
2024-03-08 11:47:32	ga_s2am_ard_3-2-1_50HMF_2024-03-08_final.stac-item
2024-03-11 11:57:27	ga_s2am_ard_3-2-1_50HMF_2024-03-11_final.stac-item
2024-03-18 11:47:32	ga_s2am_ard_3-2-1_50HMF_2024-03-18_final.stac-item
2024-03-21 11:57:28	ga_s2am_ard_3-2-1_50HMF_2024-03-21_final.stac-item
2024-03-28 11:47:32	ga_s2am_ard_3-2-1_50HMF_2024-03-28_final.stac-item
2024-04-07 11:47:30	ga_s2am_ard_3-2-1_50HMF_2024-04-07_nrt.stac-item
2024-04-17 11:47:36	ga_s2am_ard_3-2-1_50HMF_2024-04-17_nrt.stac-item
2024-04-27 11:47:34	ga_s2am_ard_3-2-1_50HMF_2024-04-27_nrt.stac-item
2024-04-30 11:57:30	ga_s2am_ard_3-2-1_50HMF_2024-04-30_nrt.stac-item
2024-05-07 11:47:34	ga_s2am_ard_3-2-1_50HMF_2024-05-07_nrt.stac-item
2024-05-10 11:57:30	ga_s2am_ard_3-2-1_50HMF_2024-05-10_nrt.stac-item
2024-05-17 11:47:34	ga_s2am_ard_3-2-1_50HMF_2024-05-17_nrt.stac-item
2024-05-27 11:47:32	ga_s2am_ard_3-2-1_50HMF_2024-05-27_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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