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
2015-10-01 12:14:44	ga_s2am_ard_3-2-1_49JGM_2015-10-01_final.stac-item
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHQ_2016-03-06_final.stac-item
2016-05-08 12:14:47	ga_s2am_ard_3-2-1_49JFN_2016-05-08_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JNP_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGM_2016-05-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HQG_2016-06-05_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLM_2016-08-30_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HLH_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HPK_2016-10-26_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HPG_2016-11-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKR_2016-11-11_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HNH_2016-11-15_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2016-12-05_final.stac-item
2017-06-12 12:14:42	ga_s2am_ard_3-2-1_49JGL_2017-06-12_final
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50JPL_2017-07-10_final
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KHS_2017-07-12_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50HNG_2017-07-30_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49JGN_2017-10-07_final
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49JHN_2017-10-07_final
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HNG_2017-11-20_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_50JKQ_2017-12-26_final
2018-01-02 11:56:01	ga_s2am_ard_3-2-1_50HMJ_2018-01-02_final
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HMH_2018-01-12_final
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HLH_2018-02-11_final
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HLH_2018-03-20_final
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JKP_2018-03-23_final
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HLH_2018-03-30_final
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKP_2018-04-05_final
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JPM_2018-04-29_final
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JKN_2018-05-02_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JKN_2018-05-12_final
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JNQ_2018-05-19_final
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HLG_2018-05-19_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKS_2018-05-25_final
2018-06-14 12:02:48	ga_s2am_ard_3-2-1_49KHS_2018-06-14_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLT_2018-06-21_final
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JNR_2018-07-08_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JKN_2018-07-11_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLT_2018-07-11_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JPS_2018-07-11_final
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JLT_2018-08-20_final
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPM_2018-08-27_final
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JMM_2018-09-06_final
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50JPL_2018-10-06_final
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPG_2018-10-16_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50HLH_2018-10-19_final
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLT_2018-10-19_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JNM_2018-10-26_final
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JNR_2018-10-26_final
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HMK_2018-10-26_final
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HLH_2018-10-29_final
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMJ_2018-10-29_final
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JPS_2018-10-29_final
2019-01-07 11:55:37	ga_s2am_ard_3-2-1_50JLP_2019-01-07_final
2019-02-03 11:47:07	ga_s2am_ard_3-2-1_50HMH_2019-02-03_final
2019-02-13 11:47:10	ga_s2am_ard_3-2-1_50HMH_2019-02-13_final
2019-02-16 11:57:06	ga_s2am_ard_3-2-1_50HLH_2019-02-16_final
2019-07-06 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-07-06_final
2019-08-19 11:37:24	ga_s2am_ard_3-2-1_50HPG_2019-08-19_final.stac-item
2019-08-25 11:57:25	ga_s2am_ard_3-2-1_50HLG_2019-08-25_final.stac-item
2019-10-14 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-10-14_final
2019-11-16 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2019-11-16_final
2019-12-03 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2019-12-03_final
2019-12-13 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-12-13_final
2019-12-27 11:37:21	ga_s2am_ard_3-2-1_50HNG_2019-12-27_final.stac-item
2020-02-01 11:56:39	ga_s2am_ard_3-2-1_50HMJ_2020-02-01_final
2020-08-29 11:57:28	ga_s2am_ard_3-2-1_50HLG_2020-08-29_final.stac-item
2020-11-10 12:04:03	ga_s2am_ard_3-2-1_49KHR_2020-11-10_final
2021-01-06 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-01-06_final
2021-01-06 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-01-06_final
2021-01-13 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-13_final
2021-02-02 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-02-02_final
2021-02-11 12:13:38	ga_s2am_ard_3-2-1_49KHS_2021-02-11_final.stac-item
2021-02-15 11:57:19	ga_s2am_ard_3-2-1_50HMG_2021-02-15_final.stac-item
2021-02-28 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-02-28_final
2021-03-10 12:03:44	ga_s2am_ard_3-2-1_49KHS_2021-03-10_final.stac-item
2021-03-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2021-03-20_final
2021-03-27 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-03-27_final
2021-04-29 12:04:43	ga_s2am_ard_3-2-1_49JGN_2021-04-29_final
2021-04-29 12:05:26	ga_s2am_ard_3-2-1_49JGK_2021-04-29_final
2021-04-29 12:05:35	ga_s2am_ard_3-2-1_50JLP_2021-04-29_final
2021-05-02 12:14:54	ga_s2am_ard_3-2-1_49JGM_2021-05-02_final
2021-06-01 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-06-01_final
2021-06-18 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2021-06-18_final
2021-06-28 12:04:33	ga_s2am_ard_3-2-1_49KGP_2021-06-28_final
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final.stac-item
2021-08-21 11:45:14	ga_s2am_ard_3-2-1_50JNR_2021-08-21_final
2021-09-29 12:13:44	ga_s2am_ard_3-2-1_49KHS_2021-09-29_final.stac-item
2021-12-12 11:56:25	ga_s2am_ard_3-2-1_50JLL_2021-12-12_final
2022-02-06 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-02-06_final
2022-08-02 12:03:55	ga_s2am_ard_3-2-1_49KHS_2022-08-02_final.stac-item
2022-09-15 11:46:14	ga_s2am_ard_3-2-1_50JPM_2022-09-15_final.stac-item
2022-09-24 12:15:17	ga_s2am_ard_3-2-1_49JGL_2022-09-24_final.stac-item
2023-01-26 11:57:03	ga_s2am_ard_3-2-1_50HMH_2023-01-26_final.stac-item
2023-02-12 11:47:19	ga_s2am_ard_3-2-1_50HNG_2023-02-12_final.stac-item
2023-06-22 11:46:41	ga_s2am_ard_3-2-1_50HNK_2023-06-22_final.stac-item
2023-10-13 11:56:28	ga_s2am_ard_3-2-1_50HNK_2023-10-13_final.stac-item
2023-10-13 11:57:04	ga_s2am_ard_3-2-1_50HMH_2023-10-13_final.stac-item
2024-01-11 11:57:15	ga_s2am_ard_3-2-1_50HMG_2024-01-11_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

All years