Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HQG_2015-12-08_final
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGM_2016-01-26_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50JKN_2016-06-11_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JRS_2016-07-08_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_50JQN_2016-08-24_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JKN_2016-08-30_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPG_2016-09-26_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JKN_2016-10-09_final.stac-item
2016-10-15 12:14:37	ga_s2am_ard_3-2-1_49JFM_2016-10-15_final.stac-item
2016-10-29 11:43:41	ga_s2am_ard_3-2-1_50JNT_2016-10-29_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_49JGM_2017-02-19_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50JKS_2017-02-19_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-02-22_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_50KLU_2017-04-20_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HPH_2017-07-03_final.stac-item
2017-10-20 12:14:08	ga_s2am_ard_3-2-1_49JFM_2017-10-20_final.stac-item
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50KMC_2017-10-24_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50JKM_2018-01-12_final.stac-item
2018-02-21 11:50:43	ga_s2am_ard_3-2-1_50KQA_2018-02-21_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_50KRB_2018-03-20_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50HMJ_2018-04-12_final.stac-item
2018-04-15 12:05:11	ga_s2am_ard_3-2-1_49JGJ_2018-04-15_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLL_2018-05-02_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLJ_2018-05-12_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLM_2018-06-01_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JNL_2018-06-08_final.stac-item
2018-06-14 12:02:48	ga_s2am_ard_3-2-1_49KHR_2018-06-14_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-28_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50HLH_2018-09-29_final.stac-item
2018-11-08 11:53:16	ga_s2am_ard_3-2-1_50KPC_2018-11-08_final.stac-item
2018-12-14 12:13:50	ga_s2am_ard_3-2-1_49KGR_2018-12-14_final.stac-item
2018-12-18 11:53:27	ga_s2am_ard_3-2-1_50KPB_2018-12-18_final.stac-item
2018-12-25 11:46:40	ga_s2am_ard_3-2-1_50HPJ_2018-12-25_final.stac-item
2019-01-10 12:05:51	ga_s2am_ard_3-2-1_50JKN_2019-01-10_final.stac-item
2019-02-19 12:03:40	ga_s2am_ard_3-2-1_50KKB_2019-02-19_final.stac-item
2019-03-01 12:04:26	ga_s2am_ard_3-2-1_49KGP_2019-03-01_final.stac-item
2019-03-05 11:45:16	ga_s2am_ard_3-2-1_50JPQ_2019-03-05_final.stac-item
2019-03-05 11:46:28	ga_s2am_ard_3-2-1_50HPK_2019-03-05_final.stac-item
2019-03-14 12:15:16	ga_s2am_ard_3-2-1_49JGK_2019-03-14_final.stac-item
2019-04-01 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-04-01_final.stac-item
2019-05-17 11:56:33	ga_s2am_ard_3-2-1_50HNK_2019-05-17_final.stac-item
2019-07-29 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-07-29_final.stac-item
2019-09-01 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2019-09-01_final.stac-item
2019-09-17 12:03:58	ga_s2am_ard_3-2-1_50KKA_2019-09-17_final.stac-item
2019-12-13 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-12-13_final.stac-item
2019-12-26 12:03:32	ga_s2am_ard_3-2-1_50KMB_2019-12-26_final.stac-item
2020-02-17 12:14:20	ga_s2am_ard_3-2-1_49KGP_2020-02-17_final.stac-item
2020-02-28 11:46:04	ga_s2am_ard_3-2-1_50JNM_2020-02-28_final.stac-item
2020-03-05 12:04:35	ga_s2am_ard_3-2-1_50JLT_2020-03-05_final.stac-item
2020-03-15 12:04:42	ga_s2am_ard_3-2-1_49JGN_2020-03-15_final.stac-item
2020-03-19 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2020-03-19_final.stac-item
2020-04-08 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2020-04-08_final.stac-item
2020-04-11 11:52:18	ga_s2am_ard_3-2-1_50KQG_2020-04-11_final
2020-05-15 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-05-15_final.stac-item
2020-06-26 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-06-26_final.stac-item
2020-07-23 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-07-23_final.stac-item
2020-08-12 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-08-12_final.stac-item
2020-08-29 11:56:09	ga_s2am_ard_3-2-1_50JNM_2020-08-29_final.stac-item
2020-09-04 12:13:59	ga_s2am_ard_3-2-1_49KHR_2020-09-04_final.stac-item
2020-09-11 12:04:03	ga_s2am_ard_3-2-1_49KHR_2020-09-11_final.stac-item
2021-02-05 11:54:25	ga_s2am_ard_3-2-1_50KMU_2021-02-05_final.stac-item
2021-02-15 11:56:39	ga_s2am_ard_3-2-1_50HLK_2021-02-15_final.stac-item
2021-03-10 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-03-10_final.stac-item
2021-05-03 11:46:17	ga_s2am_ard_3-2-1_50JPL_2021-05-03_final.stac-item
2021-06-22 11:44:46	ga_s2am_ard_3-2-1_50JRS_2021-06-22_final.stac-item
2021-09-27 11:36:30	ga_s2am_ard_3-2-1_50JPL_2021-09-27_final.stac-item
2021-10-20 11:45:37	ga_s2am_ard_3-2-1_50JQP_2021-10-20_final.stac-item
2021-12-16 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2021-12-16_final.stac-item
2021-12-25 12:03:25	ga_s2am_ard_3-2-1_50KMC_2021-12-25_final.stac-item
2022-01-04 12:03:43	ga_s2am_ard_3-2-1_50KLB_2022-01-04_final.stac-item
2022-02-03 12:04:46	ga_s2am_ard_3-2-1_49JGN_2022-02-03_final.stac-item
2022-02-14 11:36:26	ga_s2am_ard_3-2-1_50JPL_2022-02-14_final.stac-item
2022-03-16 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2022-03-16_final.stac-item
2022-06-10 11:55:22	ga_s2am_ard_3-2-1_50JLR_2022-06-10_final.stac-item
2022-07-10 11:56:09	ga_s2am_ard_3-2-1_50JLN_2022-07-10_final.stac-item
2022-07-13 12:04:45	ga_s2am_ard_3-2-1_50KLU_2022-07-13_final.stac-item
2022-11-10 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-11-10_final.stac-item
2022-11-11 11:36:30	ga_s2am_ard_3-2-1_50JPL_2022-11-11_final.stac-item
2022-12-20 12:05:25	ga_s2am_ard_3-2-1_50JKQ_2022-12-20_final.stac-item
2022-12-27 11:53:41	ga_s2am_ard_3-2-1_50KMB_2022-12-27_final.stac-item
2022-12-30 12:04:30	ga_s2am_ard_3-2-1_49KGP_2022-12-30_final.stac-item
2023-01-19 12:05:59	ga_s2am_ard_3-2-1_50JLM_2023-01-19_final.stac-item
2023-02-08 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-02-08_final
2023-02-21 12:13:51	ga_s2am_ard_3-2-1_50KKA_2023-02-21_final
2023-03-30 12:03:54	ga_s2am_ard_3-2-1_50KLA_2023-03-30_final
2023-05-09 12:04:30	ga_s2am_ard_3-2-1_49KHP_2023-05-09_final
2023-07-02 11:46:05	ga_s2am_ard_3-2-1_50JQM_2023-07-02_final
2023-07-21 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-07-21_final
2023-07-28 12:03:28	ga_s2am_ard_3-2-1_50KMC_2023-07-28_final
2023-08-21 11:46:21	ga_s2am_ard_3-2-1_50JQL_2023-08-21_final
2023-10-30 11:46:19	ga_s2am_ard_3-2-1_50JPL_2023-10-30_final
2023-12-08 12:14:21	ga_s2am_ard_3-2-1_49KGP_2023-12-08_final
2024-01-08 11:46:11	ga_s2am_ard_3-2-1_50JQL_2024-01-08_final
2024-01-11 11:56:13	ga_s2am_ard_3-2-1_50JNL_2024-01-11_final
2024-01-14 12:03:31	ga_s2am_ard_3-2-1_50KMB_2024-01-14_final
2024-01-31 11:53:13	ga_s2am_ard_3-2-1_50KQC_2024-01-31_final
2024-02-10 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2024-02-10_final
2024-02-13 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-13_final
2024-02-17 11:46:35	ga_s2am_ard_3-2-1_50HNK_2024-02-17_final
2024-02-27 11:44:45	ga_s2am_ard_3-2-1_50JQS_2024-02-27_final

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years