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
2017-02-14 09:32:12	ga_s2am_ard_3-2-1_55HFU_2017-02-14_final.stac-item
2017-02-24 09:35:59	ga_s2am_ard_3-2-1_55HFU_2017-02-24_final.stac-item
2017-03-16 09:32:09	ga_s2am_ard_3-2-1_55HFU_2017-03-16_final.stac-item
2017-04-05 09:32:47	ga_s2am_ard_3-2-1_55HFU_2017-04-05_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_55HFU_2017-04-25_final.stac-item
2017-05-15 09:36:59	ga_s2am_ard_3-2-1_55HFU_2017-05-15_final.stac-item
2017-06-04 09:34:37	ga_s2am_ard_3-2-1_55HFU_2017-06-04_final.stac-item
2017-06-24 09:32:16	ga_s2am_ard_3-2-1_55HFU_2017-06-24_final.stac-item
2017-07-14 09:32:18	ga_s2am_ard_3-2-1_55HFU_2017-07-14_final.stac-item
2017-07-14 09:37:10	ga_s2am_ard_3-2-1_55HFU_2017-07-14_final.stac-item
2017-08-23 09:32:19	ga_s2am_ard_3-2-1_55HFU_2017-08-23_final.stac-item
2019-04-05 09:38:42	ga_s2am_ard_3-2-1_55GFN_2019-04-05_final
2019-05-02 09:28:48	ga_s2am_ard_3-2-1_55GFN_2019-05-01_final
2019-05-22 09:28:48	ga_s2am_ard_3-2-1_55GFN_2019-05-21_final
2019-06-01 09:28:47	ga_s2am_ard_3-2-1_55GFN_2019-05-31_final
2019-06-21 09:28:49	ga_s2am_ard_3-2-1_55GFN_2019-06-20_final
2019-07-24 09:38:46	ga_s2am_ard_3-2-1_55GFN_2019-07-24_final
2019-08-13 09:38:44	ga_s2am_ard_3-2-1_55GFN_2019-08-13_final
2019-08-20 09:28:47	ga_s2am_ard_3-2-1_55GFN_2019-08-19_final
2019-09-02 09:38:41	ga_s2am_ard_3-2-1_55GFN_2019-09-02_final
2019-09-19 09:28:44	ga_s2am_ard_3-2-1_55GFN_2019-09-18_final
2019-09-22 09:38:41	ga_s2am_ard_3-2-1_55GFN_2019-09-22_final
2019-09-29 09:28:46	ga_s2am_ard_3-2-1_55GFN_2019-09-28_final
2019-10-09 09:28:47	ga_s2am_ard_3-2-1_55GFN_2019-10-08_final
2019-10-12 09:38:44	ga_s2am_ard_3-2-1_55GFN_2019-10-12_final
2019-10-19 09:28:48	ga_s2am_ard_3-2-1_55GFN_2019-10-18_final
2019-10-22 09:38:44	ga_s2am_ard_3-2-1_55GFN_2019-10-22_final
2019-10-29 09:28:48	ga_s2am_ard_3-2-1_55GFN_2019-10-28_final
2019-11-01 09:38:44	ga_s2am_ard_3-2-1_55GFN_2019-11-01_final
2019-11-08 09:28:47	ga_s2am_ard_3-2-1_55GFN_2019-11-07_final
2019-11-11 09:38:43	ga_s2am_ard_3-2-1_55GFN_2019-11-11_final
2019-11-18 09:28:46	ga_s2am_ard_3-2-1_55GFN_2019-11-17_final
2019-11-21 09:38:42	ga_s2am_ard_3-2-1_55GFN_2019-11-21_final
2019-11-28 09:28:44	ga_s2am_ard_3-2-1_55GFN_2019-11-27_final
2021-12-30 09:38:42	ga_s2am_ard_3-2-1_55GFN_2021-12-30_final
2022-01-09 09:38:42	ga_s2am_ard_3-2-1_55GFN_2022-01-09_final
2022-01-29 09:38:41	ga_s2am_ard_3-2-1_55GFN_2022-01-29_final
2022-02-08 09:38:40	ga_s2am_ard_3-2-1_55GFN_2022-02-08_final
2022-03-20 09:38:44	ga_s2am_ard_3-2-1_55GFN_2022-03-20_final
2022-03-30 09:38:43	ga_s2am_ard_3-2-1_55GFN_2022-03-30_final
2022-04-09 09:38:42	ga_s2am_ard_3-2-1_55GFN_2022-04-09_final
2022-08-07 09:36:41	ga_s2am_ard_3-2-1_55HGB_2022-08-07_final
2022-08-24 09:29:11	ga_s2am_ard_3-2-1_55GFM_2022-08-23_final.stac-item
2022-09-03 09:29:11	ga_s2am_ard_3-2-1_55GFM_2022-09-02_final.stac-item
2022-09-06 09:37:26	ga_s2am_ard_3-2-1_55HFU_2022-09-06_final.stac-item
2022-09-13 09:29:09	ga_s2am_ard_3-2-1_55GFM_2022-09-12_final.stac-item
2022-09-16 09:37:24	ga_s2am_ard_3-2-1_55HFU_2022-09-16_final.stac-item
2022-09-23 09:29:06	ga_s2am_ard_3-2-1_55GFM_2022-09-22_final.stac-item
2022-09-26 09:37:22	ga_s2am_ard_3-2-1_55HFU_2022-09-26_final.stac-item
2022-10-03 09:29:06	ga_s2am_ard_3-2-1_55GFM_2022-10-02_final.stac-item
2022-10-06 09:37:21	ga_s2am_ard_3-2-1_55HFU_2022-10-06_final.stac-item
2022-10-13 09:29:04	ga_s2am_ard_3-2-1_55GFM_2022-10-12_final.stac-item
2022-10-16 09:37:18	ga_s2am_ard_3-2-1_55HFU_2022-10-16_final.stac-item
2022-10-23 09:29:01	ga_s2am_ard_3-2-1_55GFM_2022-10-22_final.stac-item
2022-10-26 09:37:18	ga_s2am_ard_3-2-1_55HFU_2022-10-26_final.stac-item
2022-11-02 09:29:03	ga_s2am_ard_3-2-1_55GFM_2022-11-01_final.stac-item
2022-11-05 09:37:19	ga_s2am_ard_3-2-1_55HFU_2022-11-05_final.stac-item
2022-11-12 09:29:02	ga_s2am_ard_3-2-1_55GFM_2022-11-11_final.stac-item
2022-11-15 09:37:17	ga_s2am_ard_3-2-1_55HFU_2022-11-15_final.stac-item
2022-11-22 09:28:59	ga_s2am_ard_3-2-1_55GFM_2022-11-21_final.stac-item
2022-11-25 09:37:14	ga_s2am_ard_3-2-1_55HFU_2022-11-25_final.stac-item
2022-12-02 09:28:59	ga_s2am_ard_3-2-1_55GFM_2022-12-01_final.stac-item
2022-12-05 09:37:15	ga_s2am_ard_3-2-1_55HFU_2022-12-05_final.stac-item
2022-12-12 09:28:56	ga_s2am_ard_3-2-1_55GFM_2022-12-11_final.stac-item
2022-12-15 09:37:14	ga_s2am_ard_3-2-1_55HFU_2022-12-15_final.stac-item
2022-12-22 09:28:56	ga_s2am_ard_3-2-1_55GFM_2022-12-21_final.stac-item
2023-01-01 09:28:55	ga_s2am_ard_3-2-1_55GFM_2022-12-31_final.stac-item
2023-01-01 09:29:01	ga_s2am_ard_3-2-1_55GFM_2022-12-31_final.stac-item
2023-01-04 09:37:14	ga_s2am_ard_3-2-1_55HFU_2023-01-04_final.stac-item
2023-01-11 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-01-10_final.stac-item
2023-01-14 09:37:12	ga_s2am_ard_3-2-1_55HFU_2023-01-14_final.stac-item
2023-01-21 09:28:54	ga_s2am_ard_3-2-1_55GFM_2023-01-20_final.stac-item
2023-01-24 09:37:11	ga_s2am_ard_3-2-1_55HFU_2023-01-24_final.stac-item
2023-01-31 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-01-30_final.stac-item
2023-02-10 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-02-09_final.stac-item
2023-02-20 09:28:56	ga_s2am_ard_3-2-1_55GFM_2023-02-19_final.stac-item
2023-03-02 09:28:56	ga_s2am_ard_3-2-1_55GFM_2023-03-01_final.stac-item
2023-03-12 09:28:54	ga_s2am_ard_3-2-1_55GFM_2023-03-11_final.stac-item
2023-03-22 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-03-21_final.stac-item
2023-04-01 09:29:00	ga_s2am_ard_3-2-1_55GFM_2023-03-31_final.stac-item
2023-04-11 09:28:59	ga_s2am_ard_3-2-1_55GFM_2023-04-10_final.stac-item
2023-04-21 09:28:55	ga_s2am_ard_3-2-1_55GFM_2023-04-20_final.stac-item
2023-05-01 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-04-30_final.stac-item
2023-05-21 09:28:59	ga_s2am_ard_3-2-1_55GFM_2023-05-20_final.stac-item
2023-05-31 09:29:01	ga_s2am_ard_3-2-1_55GFM_2023-05-30_final.stac-item
2023-07-10 09:29:02	ga_s2am_ard_3-2-1_55GFM_2023-07-09_final.stac-item
2023-07-30 09:29:02	ga_s2am_ard_3-2-1_55GFM_2023-07-29_final.stac-item
2023-09-18 09:29:00	ga_s2am_ard_3-2-1_55GFM_2023-09-17_final.stac-item
2023-09-28 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-09-27_final.stac-item
2023-10-08 09:28:57	ga_s2am_ard_3-2-1_55GFM_2023-10-07_final.stac-item
2023-10-18 09:28:54	ga_s2am_ard_3-2-1_55GFM_2023-10-17_final.stac-item
2023-11-27 09:28:50	ga_s2am_ard_3-2-1_55GFM_2023-11-26_final.stac-item
2023-12-07 09:28:51	ga_s2am_ard_3-2-1_55GFM_2023-12-06_final.stac-item
2024-01-16 09:28:49	ga_s2am_ard_3-2-1_55GFM_2024-01-15_final.stac-item
2024-02-05 09:28:53	ga_s2am_ard_3-2-1_55GFM_2024-02-04_final.stac-item
2024-03-16 09:28:57	ga_s2am_ard_3-2-1_55GFM_2024-03-15_final.stac-item
2024-04-05 09:28:54	ga_s2am_ard_3-2-1_55GFM_2024-04-04_final.stac-item
2024-05-05 09:29:00	ga_s2am_ard_3-2-1_55GFM_2024-05-04_nrt.stac-item
2024-05-15 09:29:01	ga_s2am_ard_3-2-1_55GFM_2024-05-14_nrt.stac-item
2024-05-25 09:28:56	ga_s2am_ard_3-2-1_55GFM_2024-05-24_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

Other products

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