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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPG_2015-12-21_final.stac-item
2016-01-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2016-01-19_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50KNB_2016-02-15_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50KPU_2016-03-03_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_51JWL_2016-03-07_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50KNA_2016-04-15_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_50JLQ_2016-05-05_final.stac-item
2016-05-08 12:13:49	ga_s2am_ard_3-2-1_49KHR_2016-05-08_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JRS_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JRT_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51JTN_2016-05-09_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51HUC_2016-05-16_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KPU_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JQN_2016-05-29_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51HUD_2016-06-05_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JMQ_2016-10-09_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JLM_2016-11-01_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPG_2016-11-02_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51JUN_2016-11-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGQ_2016-11-11_final.stac-item
2016-11-19 11:19:19	ga_s2am_ard_3-2-1_51JWM_2016-11-19_final
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51JUN_2016-12-22_final
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_50KNA_2016-12-31_final
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51JUN_2017-01-01_final
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50KRD_2017-01-07_final
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_51HXC_2017-01-25_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JLL_2017-05-27_final
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KGQ_2017-12-16_final
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_51JWN_2017-12-17_final
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KGQ_2017-12-19_final
2018-02-15 11:34:02	ga_s2am_ard_3-2-1_50JRT_2018-02-15_final
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51HXC_2018-04-23_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50HMG_2018-06-21_final.stac-item
2018-07-22 11:25:32	ga_s2am_ard_3-2-1_51JWH_2018-07-22_final
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHS_2018-08-06_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50KQV_2018-08-10_final
2018-10-19 11:47:03	ga_s2am_ard_3-2-1_50KQG_2018-10-19_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JLM_2018-10-22_final
2018-11-08 11:53:56	ga_s2am_ard_3-2-1_50KQV_2018-11-08_final
2018-11-11 12:03:22	ga_s2am_ard_3-2-1_50KLC_2018-11-11_final
2018-11-22 11:34:25	ga_s2am_ard_3-2-1_51JUN_2018-11-22_final
2018-11-25 11:44:23	ga_s2am_ard_3-2-1_51JTN_2018-11-25_final
2018-12-12 11:34:28	ga_s2am_ard_3-2-1_51JTN_2018-12-12_final
2018-12-18 11:52:25	ga_s2am_ard_3-2-1_50KPF_2018-12-18_final.stac-item
2018-12-19 11:24:35	ga_s2am_ard_3-2-1_51JWM_2018-12-19_final
2018-12-22 11:34:21	ga_s2am_ard_3-2-1_51JVN_2018-12-22_final
2019-01-04 11:43:42	ga_s2am_ard_3-2-1_50KRA_2019-01-04_final
2019-01-04 11:43:45	ga_s2am_ard_3-2-1_50KQA_2019-01-04_final
2019-01-04 11:44:00	ga_s2am_ard_3-2-1_50KQV_2019-01-04_final
2019-02-10 11:34:21	ga_s2am_ard_3-2-1_51JVN_2019-02-10_final
2019-02-19 12:04:09	ga_s2am_ard_3-2-1_50KKV_2019-02-19_final
2019-03-08 11:52:53	ga_s2am_ard_3-2-1_50KRD_2019-03-08_final
2019-05-03 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-05-03_final
2019-08-25 11:57:25	ga_s2am_ard_3-2-1_50HLG_2019-08-25_final.stac-item
2019-10-04 11:56:01	ga_s2am_ard_3-2-1_50JKN_2019-10-04_final
2019-10-28 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-10-28_final
2019-11-23 11:55:47	ga_s2am_ard_3-2-1_50JKP_2019-11-23_final
2019-11-24 11:24:30	ga_s2am_ard_3-2-1_51JWN_2019-11-24_final
2019-12-31 11:16:53	ga_s2am_ard_3-2-1_51HWC_2019-12-31_final.stac-item
2020-01-05 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2020-01-05_final
2020-01-09 11:47:15	ga_s2am_ard_3-2-1_50HNG_2020-01-09_final.stac-item
2020-03-12 11:53:13	ga_s2am_ard_3-2-1_50KQC_2020-03-12_final
2020-07-17 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-07-17_final
2020-09-01 12:04:51	ga_s2am_ard_3-2-1_49JGN_2020-09-01_final
2020-11-07 11:53:58	ga_s2am_ard_3-2-1_50KNA_2020-11-07_final
2020-11-07 11:54:01	ga_s2am_ard_3-2-1_50KMA_2020-11-07_final
2020-11-21 11:34:27	ga_s2am_ard_3-2-1_51JWN_2020-11-21_final
2020-11-24 11:44:32	ga_s2am_ard_3-2-1_51JTN_2020-11-24_final
2020-12-20 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2020-12-20_final
2020-12-30 12:03:26	ga_s2am_ard_3-2-1_50KLC_2020-12-30_final
2020-12-30 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2020-12-30_final
2021-01-03 11:44:23	ga_s2am_ard_3-2-1_50KPU_2021-01-03_final
2021-01-06 11:53:43	ga_s2am_ard_3-2-1_50KMB_2021-01-06_final
2021-02-02 11:44:27	ga_s2am_ard_3-2-1_51JUN_2021-02-02_final
2021-02-15 11:52:36	ga_s2am_ard_3-2-1_50KPF_2021-02-15_final.stac-item
2021-03-05 11:16:19	ga_s2am_ard_3-2-1_51JWF_2021-03-05_final
2021-03-10 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2021-03-10_final
2021-08-18 11:34:39	ga_s2am_ard_3-2-1_50JRT_2021-08-18_final
2021-10-13 11:53:04	ga_s2am_ard_3-2-1_50KRD_2021-10-13_final
2021-10-30 11:43:09	ga_s2am_ard_3-2-1_50KRD_2021-10-30_final
2021-11-12 11:53:41	ga_s2am_ard_3-2-1_50KNB_2021-11-12_final
2021-11-12 11:53:45	ga_s2am_ard_3-2-1_50KMB_2021-11-12_final
2021-12-16 11:34:32	ga_s2am_ard_3-2-1_51JUN_2021-12-16_final
2022-02-04 11:37:21	ga_s2am_ard_3-2-1_50HPG_2022-02-04_final.stac-item
2022-02-17 11:44:28	ga_s2am_ard_3-2-1_51JUN_2022-02-17_final
2022-03-06 11:34:43	ga_s2am_ard_3-2-1_51JWM_2022-03-06_final
2022-05-11 11:52:38	ga_s2am_ard_3-2-1_50KQF_2022-05-11_final.stac-item
2023-02-25 11:53:15	ga_s2am_ard_3-2-1_50KQC_2023-02-25_final.stac-item
2023-02-25 11:53:51	ga_s2am_ard_3-2-1_50KQA_2023-02-25_final.stac-item
2023-06-09 11:37:25	ga_s2am_ard_3-2-1_50HPG_2023-06-09_final.stac-item
2023-08-24 11:53:09	ga_s2am_ard_3-2-1_50KQD_2023-08-24_final.stac-item
2023-08-31 11:43:09	ga_s2am_ard_3-2-1_50KRD_2023-08-31_final.stac-item
2023-09-17 11:37:24	ga_s2am_ard_3-2-1_50HPG_2023-09-17_final.stac-item
2023-10-27 11:34:37	ga_s2am_ard_3-2-1_50JRT_2023-10-27_final.stac-item
2023-11-16 11:34:16	ga_s2am_ard_3-2-1_51JWN_2023-11-16_final.stac-item
2023-12-28 12:13:51	ga_s2am_ard_3-2-1_50KKA_2023-12-28_final.stac-item
2024-01-04 12:03:41	ga_s2am_ard_3-2-1_50KNA_2024-01-04_final.stac-item
2024-01-25 11:34:33	ga_s2am_ard_3-2-1_51JWM_2024-01-25_final.stac-item
2024-02-04 11:34:32	ga_s2am_ard_3-2-1_51JTN_2024-02-04_final.stac-item
2024-02-14 11:37:15	ga_s2am_ard_3-2-1_50HQG_2024-02-14_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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