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
2015-11-27 12:03:46	ga_s2am_ard_3-2-1_49KHR_2015-11-27_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_50JKS_2015-11-27_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JLQ_2015-12-07_final.stac-item
2016-01-26 12:04:01	ga_s2am_ard_3-2-1_49KHR_2016-01-26_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGL_2016-01-26_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGM_2016-01-26_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_49JGK_2016-03-06_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JKS_2016-03-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JKT_2016-04-15_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_50JKS_2016-04-25_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMJ_2016-05-09_final.stac-item
2016-05-25 12:04:47	ga_s2am_ard_3-2-1_49JGL_2016-05-25_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JKQ_2016-06-14_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JLR_2016-06-14_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HPK_2016-09-06_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HMJ_2017-01-14_final
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HNJ_2017-01-24_final
2017-03-14 12:13:13	ga_s2am_ard_3-2-1_49KHR_2017-03-14_final
2017-05-13 12:13:38	ga_s2am_ard_3-2-1_49KHS_2017-05-13_final.stac-item
2017-06-09 12:03:49	ga_s2am_ard_3-2-1_49KHQ_2017-06-09_final
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JFM_2017-09-30_final
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KHQ_2017-09-30_final
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-09-30_final
2017-10-14 11:56:06	ga_s2am_ard_3-2-1_50HMK_2017-10-14_final
2017-10-20 12:13:21	ga_s2am_ard_3-2-1_49KHS_2017-10-20_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50HMK_2017-11-13_final
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HMJ_2017-12-10_final
2018-02-01 11:55:56	ga_s2am_ard_3-2-1_50HNK_2018-02-01_final
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNH_2018-02-08_final
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HLJ_2018-03-03_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGM_2018-04-05_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKN_2018-04-05_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKS_2018-04-05_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JLP_2018-04-05_final
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_49JGK_2018-06-14_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-09-12_final
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLR_2018-09-12_final
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-10-02_final
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JKS_2018-10-02_final
2018-12-25 11:46:48	ga_s2am_ard_3-2-1_50HMJ_2018-12-25_final
2019-02-16 11:56:33	ga_s2am_ard_3-2-1_50HMK_2019-02-16_final
2019-02-23 11:46:36	ga_s2am_ard_3-2-1_50HMK_2019-02-23_final
2019-02-23 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2019-02-23_final
2019-03-31 12:05:07	ga_s2am_ard_3-2-1_50JKR_2019-03-31_final
2019-04-04 11:47:15	ga_s2am_ard_3-2-1_50HLH_2019-04-04_final
2019-04-30 12:05:50	ga_s2am_ard_3-2-1_50JKP_2019-04-30_final
2019-09-17 12:05:55	ga_s2am_ard_3-2-1_50JKN_2019-09-17_final
2019-10-31 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-10-31_final
2019-11-13 11:56:32	ga_s2am_ard_3-2-1_50HNK_2019-11-13_final
2019-12-23 11:56:49	ga_s2am_ard_3-2-1_50HLJ_2019-12-23_final
2020-02-18 11:46:37	ga_s2am_ard_3-2-1_50HNK_2020-02-18_final
2020-04-04 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-04-04_final
2020-05-31 11:56:20	ga_s2am_ard_3-2-1_50JKM_2020-05-31_final
2020-06-16 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2020-06-16_final
2020-07-26 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2020-07-26_final
2020-10-04 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-10-04_final
2020-10-04 12:14:22	ga_s2am_ard_3-2-1_49KHP_2020-10-04_final
2020-10-11 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-10-11_final
2020-10-28 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-10-28_final
2020-12-14 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2020-12-14_final
2021-01-19 12:05:09	ga_s2am_ard_3-2-1_49JFM_2021-01-19_final
2021-01-19 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-01-19_final
2021-03-27 11:57:04	ga_s2am_ard_3-2-1_50HLH_2021-03-27_final
2021-04-06 11:56:26	ga_s2am_ard_3-2-1_50HNK_2021-04-06_final
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final
2021-09-16 12:05:13	ga_s2am_ard_3-2-1_50JKR_2021-09-16_final
2021-10-16 12:05:19	ga_s2am_ard_3-2-1_50JLR_2021-10-16_final
2021-10-23 11:57:11	ga_s2am_ard_3-2-1_50HMH_2021-10-23_final
2022-01-21 11:57:09	ga_s2am_ard_3-2-1_50HLH_2022-01-21_final
2022-02-16 12:13:40	ga_s2am_ard_3-2-1_49KHS_2022-02-16_final.stac-item
2022-02-20 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-02-20_final
2022-03-09 11:47:14	ga_s2am_ard_3-2-1_50HMH_2022-03-09_final
2022-03-12 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final
2022-04-08 11:46:54	ga_s2am_ard_3-2-1_50HQH_2022-04-08_final
2022-05-24 12:05:48	ga_s2am_ard_3-2-1_50JKP_2022-05-24_final
2022-07-13 12:06:08	ga_s2am_ard_3-2-1_50JKN_2022-07-13_final
2022-08-02 12:06:06	ga_s2am_ard_3-2-1_50JKN_2022-08-02_final
2022-09-01 12:05:38	ga_s2am_ard_3-2-1_50JKQ_2022-09-01_final.stac-item
2022-09-18 11:57:00	ga_s2am_ard_3-2-1_50HMJ_2022-09-18_final.stac-item
2022-09-21 12:05:48	ga_s2am_ard_3-2-1_50JKP_2022-09-21_final.stac-item
2022-09-28 11:56:47	ga_s2am_ard_3-2-1_50HLK_2022-09-28_final.stac-item
2022-10-18 11:56:33	ga_s2am_ard_3-2-1_50HNK_2022-10-18_final.stac-item
2023-01-19 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-01-19_final.stac-item
2023-04-03 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-04-03_final.stac-item
2023-04-09 12:05:12	ga_s2am_ard_3-2-1_50JKR_2023-04-09_final.stac-item
2023-04-09 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2023-04-09_final.stac-item
2023-05-06 11:57:06	ga_s2am_ard_3-2-1_50HMH_2023-05-06_final.stac-item
2023-05-29 12:05:41	ga_s2am_ard_3-2-1_50JLP_2023-05-29_final.stac-item
2023-06-19 11:37:07	ga_s2am_ard_3-2-1_50HQH_2023-06-19_final.stac-item
2023-07-05 11:56:45	ga_s2am_ard_3-2-1_50HLK_2023-07-05_final.stac-item
2023-09-06 12:05:35	ga_s2am_ard_3-2-1_49JGK_2023-09-06_final.stac-item
2023-09-29 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-09-29_final.stac-item
2023-10-03 11:55:53	ga_s2am_ard_3-2-1_50JKP_2023-10-03_final.stac-item
2023-10-06 12:05:52	ga_s2am_ard_3-2-1_50JLN_2023-10-06_final.stac-item
2023-10-10 11:46:29	ga_s2am_ard_3-2-1_50HQK_2023-10-10_final.stac-item
2023-10-10 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2023-10-10_final.stac-item
2023-10-23 11:56:36	ga_s2am_ard_3-2-1_50HMK_2023-10-23_final.stac-item
2024-01-31 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2024-01-31_final.stac-item
2024-02-10 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-02-10_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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