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
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51HTE_2016-12-22_final
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49JGJ_2016-12-31_final
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HPH_2017-01-24_final
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-02-12_final
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HNK_2017-02-16_final
2017-04-01 11:34:45	ga_s2am_ard_3-2-1_51HUD_2017-04-01_final
2017-05-07 11:56:10	ga_s2am_ard_3-2-1_50JNL_2017-05-07_final
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGJ_2017-07-09_final
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JKN_2017-07-16_final
2017-08-08 12:04:43	ga_s2am_ard_3-2-1_50JKQ_2017-08-08_final
2017-08-15 11:56:09	ga_s2am_ard_3-2-1_50HLK_2017-08-15_final
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49JGN_2017-08-21_final
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49JGL_2017-09-27_final
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50KNC_2017-10-17_final
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51HVD_2018-02-12_final
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-02-14_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKT_2018-03-26_final
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_50JQN_2018-03-27_final
2018-04-05 12:02:49	ga_s2am_ard_3-2-1_50KNC_2018-04-05_final
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JKM_2018-05-12_final
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JQM_2018-06-28_final
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JQN_2018-06-28_final
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50JPL_2018-07-08_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JML_2018-07-18_final
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50KRB_2018-07-18_final
2018-09-29 11:48:21	ga_s2am_ard_3-2-1_50KQC_2018-09-29_final
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-10-12_final
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JKR_2018-10-22_final
2018-11-15 11:46:28	ga_s2am_ard_3-2-1_50HPK_2018-11-15_final
2019-01-30 12:04:54	ga_s2am_ard_3-2-1_50JKS_2019-01-30_final
2019-02-09 12:05:49	ga_s2am_ard_3-2-1_50JLN_2019-02-09_final
2019-03-28 11:52:19	ga_s2am_ard_3-2-1_50KQG_2019-03-28_final.stac-item
2019-05-01 11:36:37	ga_s2am_ard_3-2-1_50HQK_2019-05-01_final
2019-05-11 11:37:01	ga_s2am_ard_3-2-1_51HUC_2019-05-11_final
2019-05-28 11:26:43	ga_s2am_ard_3-2-1_51HWD_2019-05-28_final
2019-07-12 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-12_final
2019-08-02 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2019-08-02_final
2019-08-21 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-08-21_final
2019-08-28 12:04:32	ga_s2am_ard_3-2-1_49KGP_2019-08-28_final
2019-09-04 11:56:22	ga_s2am_ard_3-2-1_50JML_2019-09-04_final
2019-10-14 11:53:24	ga_s2am_ard_3-2-1_50KPC_2019-10-14_final
2020-01-05 12:05:35	ga_s2am_ard_3-2-1_50JKP_2020-01-05_final
2020-01-25 12:05:34	ga_s2am_ard_3-2-1_50JKP_2020-01-25_final
2020-02-01 11:56:03	ga_s2am_ard_3-2-1_50JLM_2020-02-01_final
2020-02-25 11:36:33	ga_s2am_ard_3-2-1_50HPK_2020-02-25_final
2020-03-25 12:03:23	ga_s2am_ard_3-2-1_50KLC_2020-03-25_final
2020-04-25 11:35:00	ga_s2am_ard_3-2-1_51JVL_2020-04-25_final
2020-05-22 11:27:04	ga_s2am_ard_3-2-1_51HVC_2020-05-22_final
2020-07-17 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2020-07-17_final
2020-08-05 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-08-05_final
2020-09-01 12:03:49	ga_s2am_ard_3-2-1_50KKB_2020-09-01_final
2020-10-01 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-01_final
2020-10-09 11:26:53	ga_s2am_ard_3-2-1_51HUD_2020-10-09_final
2020-10-19 11:26:41	ga_s2am_ard_3-2-1_51HXD_2020-10-19_final
2020-11-03 12:14:32	ga_s2am_ard_3-2-1_49KGP_2020-11-03_final
2020-11-20 12:04:01	ga_s2am_ard_3-2-1_50KKA_2020-11-20_final
2020-11-23 12:14:29	ga_s2am_ard_3-2-1_49KGP_2020-11-23_final
2021-01-06 11:54:05	ga_s2am_ard_3-2-1_50KPV_2021-01-06_final
2021-02-05 11:55:09	ga_s2am_ard_3-2-1_50JMR_2021-02-05_final
2021-04-26 11:53:14	ga_s2am_ard_3-2-1_50KQC_2021-04-26_final
2021-04-27 11:26:40	ga_s2am_ard_3-2-1_51HVD_2021-04-27_final
2021-04-29 12:04:25	ga_s2am_ard_3-2-1_49KHP_2021-04-29_final
2021-05-27 11:26:59	ga_s2am_ard_3-2-1_51HVC_2021-05-27_final
2021-06-11 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-11_final
2021-06-28 12:05:16	ga_s2am_ard_3-2-1_49JGL_2021-06-28_final
2021-07-31 12:14:26	ga_s2am_ard_3-2-1_49KHP_2021-07-31_final
2021-10-20 11:45:59	ga_s2am_ard_3-2-1_50JNN_2021-10-20_final
2021-12-18 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-12-18_final
2022-01-31 11:55:59	ga_s2am_ard_3-2-1_50JKN_2022-01-31_final
2022-02-07 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2022-02-07_final
2022-03-03 11:26:51	ga_s2am_ard_3-2-1_51HUD_2022-03-03_final
2022-03-10 11:16:26	ga_s2am_ard_3-2-1_51HYE_2022-03-10_final
2022-03-29 11:46:11	ga_s2am_ard_3-2-1_50JNM_2022-03-29_final
2022-04-01 11:55:49	ga_s2am_ard_3-2-1_50JMN_2022-04-01_final
2022-05-12 11:26:09	ga_s2am_ard_3-2-1_51JUG_2022-05-12_final
2022-06-10 11:55:33	ga_s2am_ard_3-2-1_50JMQ_2022-06-10_final
2022-08-29 11:53:33	ga_s2am_ard_3-2-1_50KPC_2022-08-29_final
2022-09-24 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-09-24_final.stac-item
2022-10-11 12:03:50	ga_s2am_ard_3-2-1_50KKB_2022-10-11_final.stac-item
2022-10-19 11:26:50	ga_s2am_ard_3-2-1_51HUD_2022-10-19_final.stac-item
2022-11-04 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2022-11-04_final.stac-item
2022-11-07 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2022-11-07_final.stac-item
2022-11-13 12:14:59	ga_s2am_ard_3-2-1_49JGM_2022-11-13_final.stac-item
2022-12-17 11:57:08	ga_s2am_ard_3-2-1_50HLH_2022-12-17_final.stac-item
2023-01-20 11:37:12	ga_s2am_ard_3-2-1_50HQG_2023-01-20_final.stac-item
2023-02-12 11:43:20	ga_s2am_ard_3-2-1_50KQC_2023-02-12_final.stac-item
2023-02-15 11:56:08	ga_s2am_ard_3-2-1_50JLM_2023-02-15_final.stac-item
2023-02-19 11:36:54	ga_s2am_ard_3-2-1_51HUC_2023-02-19_final.stac-item
2023-03-24 11:46:36	ga_s2am_ard_3-2-1_50HNK_2023-03-24_final.stac-item
2023-05-03 11:43:19	ga_s2am_ard_3-2-1_50KRC_2023-05-03_final.stac-item
2023-06-22 11:47:10	ga_s2am_ard_3-2-1_50HNH_2023-06-22_final.stac-item
2023-09-16 12:05:00	ga_s2am_ard_3-2-1_49JHM_2023-09-16_final.stac-item
2023-10-03 11:56:31	ga_s2am_ard_3-2-1_50HNK_2023-10-03_final.stac-item
2023-11-02 11:56:39	ga_s2am_ard_3-2-1_50HLK_2023-11-02_final.stac-item
2023-11-15 12:05:39	ga_s2am_ard_3-2-1_50JKP_2023-11-15_final.stac-item
2023-12-16 11:36:39	ga_s2am_ard_3-2-1_51HUD_2023-12-16_final.stac-item
2023-12-18 12:14:37	ga_s2am_ard_3-2-1_49JGN_2023-12-18_final.stac-item
2023-12-19 11:44:27	ga_s2am_ard_3-2-1_51JTN_2023-12-19_final.stac-item
2024-04-13 12:03:43	ga_s2am_ard_3-2-1_50KLB_2024-04-13_final.stac-item
2024-04-14 11:36:40	ga_s2am_ard_3-2-1_50HPK_2024-04-14_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

All years