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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_49JGL_2015-10-28_final.stac-item
2016-04-29 11:47:17	ga_s2am_ard_3-2-1_50HNG_2016-04-29_final.stac-item
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50JLM_2016-06-21_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50JNM_2016-11-15_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KGP_2016-12-04_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JNQ_2017-02-16_final
2017-03-04 12:13:36	ga_s2am_ard_3-2-1_49KGR_2017-03-04_final
2017-07-23 11:45:09	ga_s2am_ard_3-2-1_50HQK_2017-07-23_final
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50JPP_2017-08-12_final
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2017-11-19_final
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50JPL_2017-11-27_final
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50JNL_2017-12-10_final
2018-01-05 12:05:28	ga_s2am_ard_3-2-1_50JLM_2018-01-05_final
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HNJ_2018-01-19_final
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50JPM_2018-01-19_final
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50HNK_2018-03-23_final
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2018-04-25_final
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50HQK_2018-05-06_final
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNK_2018-05-09_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLH_2018-05-22_final
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKA_2018-07-14_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KHR_2018-09-02_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKN_2018-09-02_final
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHQ_2018-10-12_final
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-11-01_final
2018-11-21 12:04:39	ga_s2am_ard_3-2-1_49JGN_2018-11-21_final
2018-12-05 11:46:58	ga_s2am_ard_3-2-1_50HNH_2018-12-05_final
2019-02-09 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-02-09_final
2019-02-09 12:05:43	ga_s2am_ard_3-2-1_50JLN_2019-02-09_final
2019-02-23 11:46:26	ga_s2am_ard_3-2-1_50HQK_2019-02-23_final
2019-02-23 11:46:48	ga_s2am_ard_3-2-1_50HNJ_2019-02-23_final
2019-03-31 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-03-31_final
2019-05-21 11:36:41	ga_s2am_ard_3-2-1_50HPK_2019-05-21_final
2019-06-13 11:46:44	ga_s2am_ard_3-2-1_50HMK_2019-06-13_final
2019-07-02 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-02_final
2019-08-19 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-08-19_final
2019-10-01 11:46:17	ga_s2am_ard_3-2-1_50JQL_2019-10-01_final
2019-11-20 11:46:42	ga_s2am_ard_3-2-1_50HMK_2019-11-20_final
2019-12-07 11:36:17	ga_s2am_ard_3-2-1_50JQL_2019-12-07_final
2019-12-16 12:05:09	ga_s2am_ard_3-2-1_49JGL_2019-12-16_final
2020-01-08 12:15:01	ga_s2am_ard_3-2-1_49JGL_2020-01-08_final
2020-01-09 11:45:45	ga_s2am_ard_3-2-1_50JPN_2020-01-09_final
2020-02-07 12:14:19	ga_s2am_ard_3-2-1_49KGP_2020-02-07_final
2020-02-08 11:44:30	ga_s2am_ard_3-2-1_50JPT_2020-02-08_final
2020-04-08 11:46:06	ga_s2am_ard_3-2-1_50JNM_2020-04-08_final
2020-04-17 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2020-04-17_final
2020-06-10 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-06-10_final
2020-07-26 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-07-26_final
2020-07-27 11:46:54	ga_s2am_ard_3-2-1_50HPJ_2020-07-27_final
2020-09-11 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2020-09-11_final
2020-10-14 12:14:47	ga_s2am_ard_3-2-1_49JGN_2020-10-14_final
2020-12-21 11:37:05	ga_s2am_ard_3-2-1_50HPH_2020-12-21_final
2020-12-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-12-30_final
2021-01-06 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-01-06_final
2021-03-20 12:05:50	ga_s2am_ard_3-2-1_50JLN_2021-03-20_final
2021-04-19 12:04:23	ga_s2am_ard_3-2-1_49KHP_2021-04-19_final
2021-09-16 12:04:29	ga_s2am_ard_3-2-1_50KKU_2021-09-16_final
2021-10-17 11:37:12	ga_s2am_ard_3-2-1_50HPH_2021-10-17_final
2022-01-07 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2022-01-07_final
2022-01-18 11:46:09	ga_s2am_ard_3-2-1_50JNM_2022-01-18_final
2022-01-31 11:56:18	ga_s2am_ard_3-2-1_50JNL_2022-01-31_final
2022-02-27 11:46:37	ga_s2am_ard_3-2-1_50HPK_2022-02-27_final
2022-04-04 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2022-04-04_final
2022-04-27 12:14:46	ga_s2am_ard_3-2-1_49JGN_2022-04-27_final
2022-04-28 11:46:28	ga_s2am_ard_3-2-1_50JNL_2022-04-28_final
2022-05-11 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-05-11_final
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final
2022-05-14 12:04:43	ga_s2am_ard_3-2-1_50JLT_2022-05-14_final
2022-05-15 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-05-15_final
2022-05-31 11:55:28	ga_s2am_ard_3-2-1_50JNQ_2022-05-31_final
2022-06-27 11:47:22	ga_s2am_ard_3-2-1_50HMH_2022-06-27_final
2022-08-02 12:05:36	ga_s2am_ard_3-2-1_50JKQ_2022-08-02_final
2022-09-28 11:55:02	ga_s2am_ard_3-2-1_50JMS_2022-09-28_final.stac-item
2022-10-01 12:05:59	ga_s2am_ard_3-2-1_50JLN_2022-10-01_final.stac-item
2022-10-28 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-10-28_final.stac-item
2022-11-27 11:56:17	ga_s2am_ard_3-2-1_50JNL_2022-11-27_final.stac-item
2023-02-11 12:15:09	ga_s2am_ard_3-2-1_49JGL_2023-02-11_final.stac-item
2023-02-18 12:04:28	ga_s2am_ard_3-2-1_49KGP_2023-02-18_final.stac-item
2023-03-10 12:04:29	ga_s2am_ard_3-2-1_50JKT_2023-03-10_final.stac-item
2023-04-03 11:46:33	ga_s2am_ard_3-2-1_50HPK_2023-04-03_final.stac-item
2023-04-16 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-04-16_final.stac-item
2023-04-23 11:45:06	ga_s2am_ard_3-2-1_50JPR_2023-04-23_final.stac-item
2023-06-02 11:46:45	ga_s2am_ard_3-2-1_50HMK_2023-06-02_final.stac-item
2023-07-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-07-01_final.stac-item
2023-07-12 11:46:24	ga_s2am_ard_3-2-1_50JPL_2023-07-12_final.stac-item
2023-07-28 12:04:36	ga_s2am_ard_3-2-1_49KGP_2023-07-28_final.stac-item
2023-08-24 11:56:05	ga_s2am_ard_3-2-1_50JKN_2023-08-24_final.stac-item
2023-09-19 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-09-19_final.stac-item
2023-09-20 11:46:21	ga_s2am_ard_3-2-1_50JPL_2023-09-20_final.stac-item
2023-09-27 11:37:05	ga_s2am_ard_3-2-1_50HQH_2023-09-27_final.stac-item
2023-10-26 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-10-26_final.stac-item
2023-10-27 11:36:38	ga_s2am_ard_3-2-1_50HPK_2023-10-27_final.stac-item
2023-11-09 11:47:02	ga_s2am_ard_3-2-1_50HPH_2023-11-09_final.stac-item
2023-11-15 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-11-15_final.stac-item
2023-11-19 11:46:20	ga_s2am_ard_3-2-1_50JNL_2023-11-19_final.stac-item
2023-12-18 12:13:54	ga_s2am_ard_3-2-1_49KGR_2023-12-18_final.stac-item
2024-01-11 11:57:04	ga_s2am_ard_3-2-1_50HLH_2024-01-11_final.stac-item
2024-02-07 11:46:15	ga_s2am_ard_3-2-1_50JPL_2024-02-07_final.stac-item
2024-02-20 11:55:54	ga_s2am_ard_3-2-1_50JLN_2024-02-20_final.stac-item
2024-03-01 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2024-03-01_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