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
2016-03-29 12:14:39	ga_s2am_ard_3-2-1_49JGL_2016-03-29_final.stac-item
2016-03-29 12:14:39	ga_s2am_ard_3-2-1_49JGM_2016-03-29_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49KGQ_2016-04-15_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHP_2016-08-03_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHP_2016-09-12_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-02-22_final
2017-03-01 12:04:35	ga_s2am_ard_3-2-1_49JGL_2017-03-01_final
2017-03-24 12:14:35	ga_s2am_ard_3-2-1_49JGL_2017-03-24_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JHM_2017-06-19_final
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_49JHN_2017-06-19_final
2017-09-10 12:13:33	ga_s2am_ard_3-2-1_49KGQ_2017-09-10_final
2017-10-27 12:04:41	ga_s2am_ard_3-2-1_49JGN_2017-10-27_final
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KHP_2017-12-16_final
2018-01-18 12:14:35	ga_s2am_ard_3-2-1_49JFM_2018-01-18_final
2018-02-07 12:13:40	ga_s2am_ard_3-2-1_49KGR_2018-02-07_final
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-02-17_final
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-03-19_final
2018-04-08 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-04-08_final
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-07-04_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGQ_2018-07-14_final
2019-01-30 12:05:12	ga_s2am_ard_3-2-1_49JGL_2019-01-30_final
2019-02-19 12:05:25	ga_s2am_ard_3-2-1_49JGK_2019-02-19_final
2019-03-11 12:05:10	ga_s2am_ard_3-2-1_49JGL_2019-03-11_final
2019-03-31 12:04:46	ga_s2am_ard_3-2-1_49JGN_2019-03-31_final
2019-05-13 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-05-13_final
2019-06-12 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-06-12_final
2019-06-22 12:14:25	ga_s2am_ard_3-2-1_49KHP_2019-06-22_final
2019-07-19 12:05:02	ga_s2am_ard_3-2-1_49JHM_2019-07-19_final
2019-07-22 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-07-22_final
2019-07-29 12:05:27	ga_s2am_ard_3-2-1_49JGK_2019-07-29_final
2019-08-11 12:14:02	ga_s2am_ard_3-2-1_49KGR_2019-08-11_final
2019-09-07 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2019-09-07_final
2019-09-30 12:14:28	ga_s2am_ard_3-2-1_49KGP_2019-09-30_final
2019-10-27 12:05:00	ga_s2am_ard_3-2-1_49JHM_2019-10-27_final
2020-01-15 12:04:12	ga_s2am_ard_3-2-1_49KGQ_2020-01-15_final
2020-02-14 12:04:23	ga_s2am_ard_3-2-1_49KHP_2020-02-14_final
2020-02-14 12:04:50	ga_s2am_ard_3-2-1_49JHM_2020-02-14_final
2020-02-24 12:04:41	ga_s2am_ard_3-2-1_49JGN_2020-02-24_final
2020-03-05 12:04:14	ga_s2am_ard_3-2-1_49KGQ_2020-03-05_final
2020-03-08 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2020-03-08_final
2020-03-08 12:14:17	ga_s2am_ard_3-2-1_49KHP_2020-03-08_final
2020-03-25 12:04:24	ga_s2am_ard_3-2-1_49KHP_2020-03-25_final
2020-04-07 12:14:38	ga_s2am_ard_3-2-1_49JGN_2020-04-07_final
2020-04-24 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2020-04-24_final
2020-06-06 12:14:48	ga_s2am_ard_3-2-1_49JGN_2020-06-06_final
2020-07-23 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-07-23_final
2020-08-02 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-08-02_final
2020-10-31 12:04:47	ga_s2am_ard_3-2-1_49JHN_2020-10-31_final
2020-11-13 12:14:31	ga_s2am_ard_3-2-1_49KGP_2020-11-13_final
2020-12-10 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-12-10_final
2020-12-13 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2020-12-13_final
2021-02-18 12:04:56	ga_s2am_ard_3-2-1_49JHM_2021-02-18_final
2021-04-22 12:14:04	ga_s2am_ard_3-2-1_49KHQ_2021-04-22_final
2021-10-06 12:04:47	ga_s2am_ard_3-2-1_49JHN_2021-10-06_final
2021-11-15 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-11-15_final
2021-12-15 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-12-15_final
2022-01-24 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-01-24_final
2022-02-26 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2022-02-26_final
2022-03-15 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-03-15_final
2022-06-03 12:05:23	ga_s2am_ard_3-2-1_49JGL_2022-06-03_final
2022-06-06 12:15:18	ga_s2am_ard_3-2-1_49JGL_2022-06-06_final
2022-06-13 12:04:37	ga_s2am_ard_3-2-1_49KHP_2022-06-13_final
2022-06-23 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-06-23_final
2022-06-26 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-06-26_final
2022-07-06 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-07-06_final
2022-07-23 12:04:39	ga_s2am_ard_3-2-1_49KHP_2022-07-23_final
2022-07-26 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2022-07-26_final
2022-08-05 12:15:21	ga_s2am_ard_3-2-1_49JGL_2022-08-05_final
2022-09-14 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2022-09-14_final.stac-item
2022-10-31 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-10-31_final.stac-item
2022-11-20 12:04:43	ga_s2am_ard_3-2-1_49JHN_2022-11-20_final.stac-item
2022-11-20 12:04:47	ga_s2am_ard_3-2-1_49JGN_2022-11-20_final.stac-item
2022-11-23 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2022-11-23_final.stac-item
2022-12-20 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-12-20_final.stac-item
2022-12-23 12:14:57	ga_s2am_ard_3-2-1_49JFM_2022-12-23_final.stac-item
2023-02-11 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-02-11_final.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_final.stac-item
2023-03-10 12:04:23	ga_s2am_ard_3-2-1_49KGP_2023-03-10_final.stac-item
2023-04-19 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-04-19_final.stac-item
2023-04-29 12:04:43	ga_s2am_ard_3-2-1_49JHN_2023-04-29_final.stac-item
2023-05-02 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2023-05-02_final.stac-item
2023-05-09 12:04:32	ga_s2am_ard_3-2-1_49KGP_2023-05-09_final.stac-item
2023-05-19 12:05:31	ga_s2am_ard_3-2-1_49JGK_2023-05-19_final.stac-item
2023-05-29 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2023-05-29_final.stac-item
2023-06-08 12:05:18	ga_s2am_ard_3-2-1_49JGL_2023-06-08_final.stac-item
2023-07-18 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-07-18_final.stac-item
2023-08-17 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-17_final.stac-item
2023-09-06 12:05:02	ga_s2am_ard_3-2-1_49JHM_2023-09-06_final.stac-item
2023-10-16 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-10-16_final.stac-item
2023-10-26 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-10-26_final.stac-item
2023-11-25 12:04:41	ga_s2am_ard_3-2-1_49JGN_2023-11-25_final.stac-item
2023-11-28 12:13:51	ga_s2am_ard_3-2-1_49KGR_2023-11-28_final.stac-item
2023-12-05 12:04:39	ga_s2am_ard_3-2-1_49JGN_2023-12-05_final.stac-item
2024-02-03 12:05:25	ga_s2am_ard_3-2-1_49JGK_2024-02-03_final.stac-item
2024-03-04 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2024-03-04_final.stac-item
2024-03-04 12:04:46	ga_s2am_ard_3-2-1_49JGN_2024-03-04_final.stac-item
2024-03-24 12:04:32	ga_s2am_ard_3-2-1_49KGP_2024-03-24_final.stac-item
2024-03-24 12:05:30	ga_s2am_ard_3-2-1_49JGK_2024-03-24_final.stac-item
2024-03-27 12:14:57	ga_s2am_ard_3-2-1_49JGM_2024-03-27_final.stac-item
2024-04-03 12:04:44	ga_s2am_ard_3-2-1_49JGN_2024-04-03_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

Other products

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