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
2015-12-04 11:57:46	ga_s2am_ard_3-2-1_50LQL_2015-12-04_final
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGK_2016-01-16_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HQK_2016-04-19_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HNH_2016-04-29_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50KRD_2016-05-29_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLM_2016-08-30_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JNM_2016-08-30_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JLN_2016-09-19_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51HTE_2016-10-03_final.stac-item
2016-11-06 11:14:16	ga_s2am_ard_3-2-1_51HWC_2016-11-06_final
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JPQ_2017-06-13_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49JGM_2017-07-12_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JPL_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JUH_2017-09-28_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50JKS_2017-10-17_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50KNC_2017-10-17_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51HUC_2017-11-07_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JLN_2017-12-16_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50KRB_2017-12-30_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_50HQH_2018-01-06_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51HTC_2018-01-06_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51HUC_2018-01-06_final.stac-item
2018-03-24 11:24:03	ga_s2am_ard_3-2-1_51HUE_2018-03-24_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49JGL_2018-03-26_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51HVD_2018-04-23_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50KLB_2018-04-25_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50HQH_2018-05-26_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JPL_2018-06-28_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGM_2018-07-14_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-28_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HUE_2018-08-04_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50KQC_2018-08-20_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKN_2018-08-23_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51JVH_2018-08-24_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HMH_2018-09-06_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JKP_2018-09-09_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HPJ_2018-10-03_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-10-12_final.stac-item
2018-12-31 12:05:34	ga_s2am_ard_3-2-1_50JKP_2018-12-31_final.stac-item
2019-06-20 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-06-20_final.stac-item
2019-07-26 11:53:15	ga_s2am_ard_3-2-1_50KRC_2019-07-26_final.stac-item
2019-08-28 12:04:32	ga_s2am_ard_3-2-1_49KGP_2019-08-28_final.stac-item
2019-10-14 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-10-14_final.stac-item
2020-01-06 11:36:53	ga_s2am_ard_3-2-1_51HUC_2020-01-06_final.stac-item
2020-02-11 11:53:10	ga_s2am_ard_3-2-1_50KQC_2020-02-11_final.stac-item
2020-03-25 12:03:55	ga_s2am_ard_3-2-1_49KHR_2020-03-25_final.stac-item
2020-04-14 12:03:43	ga_s2am_ard_3-2-1_50KKB_2020-04-14_final.stac-item
2020-05-24 12:03:29	ga_s2am_ard_3-2-1_50KMC_2020-05-24_final.stac-item
2020-05-28 11:46:32	ga_s2am_ard_3-2-1_50JML_2020-05-28_final.stac-item
2020-05-31 11:53:27	ga_s2am_ard_3-2-1_50KPC_2020-05-31_final.stac-item
2020-06-23 12:05:46	ga_s2am_ard_3-2-1_50JKP_2020-06-23_final.stac-item
2020-08-13 11:36:25	ga_s2am_ard_3-2-1_50JQL_2020-08-13_final.stac-item
2020-11-27 11:53:11	ga_s2am_ard_3-2-1_50KRC_2020-11-27_final.stac-item
2020-12-04 11:47:08	ga_s2am_ard_3-2-1_50HMH_2020-12-04_final.stac-item
2020-12-21 11:36:59	ga_s2am_ard_3-2-1_51HTC_2020-12-21_final.stac-item
2020-12-24 11:43:03	ga_s2am_ard_3-2-1_50KRD_2020-12-24_final.stac-item
2021-02-08 12:06:03	ga_s2am_ard_3-2-1_50JLM_2021-02-08_final.stac-item
2021-02-19 11:36:42	ga_s2am_ard_3-2-1_51HUD_2021-02-19_final.stac-item
2021-03-30 12:03:57	ga_s2am_ard_3-2-1_49KHR_2021-03-30_final.stac-item
2021-04-27 11:26:29	ga_s2am_ard_3-2-1_51HUE_2021-04-27_final.stac-item
2021-05-06 11:56:09	ga_s2am_ard_3-2-1_50JLM_2021-05-06_final.stac-item
2021-07-15 11:56:33	ga_s2am_ard_3-2-1_50HNK_2021-07-15_final.stac-item
2021-08-08 11:34:39	ga_s2am_ard_3-2-1_51JTN_2021-08-08_final.stac-item
2021-08-22 11:16:43	ga_s2am_ard_3-2-1_51HXD_2021-08-22_final.stac-item
2021-12-02 11:53:31	ga_s2am_ard_3-2-1_50KQB_2021-12-02_final.stac-item
2021-12-12 11:52:36	ga_s2am_ard_3-2-1_50KPF_2021-12-12_final
2022-01-02 11:27:00	ga_s2am_ard_3-2-1_51HVC_2022-01-02_final.stac-item
2022-04-01 11:53:23	ga_s2am_ard_3-2-1_50KPC_2022-04-01_final.stac-item
2022-07-30 11:56:09	ga_s2am_ard_3-2-1_50JKN_2022-07-30_final.stac-item
2022-08-02 12:03:51	ga_s2am_ard_3-2-1_50KLB_2022-08-02_final.stac-item
2022-08-03 11:36:59	ga_s2am_ard_3-2-1_50HQJ_2022-08-03_final.stac-item
2022-08-09 11:54:25	ga_s2am_ard_3-2-1_50KQU_2022-08-09_final.stac-item
2022-08-10 11:26:41	ga_s2am_ard_3-2-1_51HVE_2022-08-10_final.stac-item
2022-08-23 11:36:44	ga_s2am_ard_3-2-1_51HTE_2022-08-23_final.stac-item
2022-09-08 11:53:28	ga_s2am_ard_3-2-1_50KQC_2022-09-08_final.stac-item
2022-09-16 11:16:32	ga_s2am_ard_3-2-1_51HYE_2022-09-16_final.stac-item
2022-10-01 12:03:27	ga_s2am_ard_3-2-1_50KNC_2022-10-01_final.stac-item
2022-10-05 11:43:29	ga_s2am_ard_3-2-1_50KQC_2022-10-05_final.stac-item
2022-10-05 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2022-10-05_final.stac-item
2022-10-18 11:53:24	ga_s2am_ard_3-2-1_50KPC_2022-10-18_final.stac-item
2022-11-10 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-11-10_final.stac-item
2022-11-14 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2022-11-14_final.stac-item
2023-01-03 11:46:18	ga_s2am_ard_3-2-1_50JPL_2023-01-03_final.stac-item
2023-01-13 11:47:22	ga_s2am_ard_3-2-1_50HMG_2023-01-13_final
2023-01-16 11:53:07	ga_s2am_ard_3-2-1_50KRC_2023-01-16_final.stac-item
2023-02-12 11:43:20	ga_s2am_ard_3-2-1_50KQC_2023-02-12_nrt.stac-item
2023-02-28 12:04:58	ga_s2am_ard_3-2-1_49JGM_2023-02-28_final
2023-03-27 11:56:06	ga_s2am_ard_3-2-1_50JMM_2023-03-27_final
2023-04-10 11:37:01	ga_s2am_ard_3-2-1_51HTC_2023-04-10_final
2023-04-16 11:53:17	ga_s2am_ard_3-2-1_50KQC_2023-04-16_final
2023-06-15 11:57:17	ga_s2am_ard_3-2-1_50HLH_2023-06-15_final
2023-07-22 11:43:08	ga_s2am_ard_3-2-1_50KRD_2023-07-22_final
2023-10-11 11:16:39	ga_s2am_ard_3-2-1_51HXD_2023-10-11_final
2023-11-05 12:03:22	ga_s2am_ard_3-2-1_50KMC_2023-11-05_final
2023-12-13 11:27:03	ga_s2am_ard_3-2-1_51HTC_2023-12-13_final
2024-01-01 11:53:18	ga_s2am_ard_3-2-1_50KPC_2024-01-01_final
2024-01-07 12:13:50	ga_s2am_ard_3-2-1_50KKA_2024-01-07_final
2024-01-31 11:53:20	ga_s2am_ard_3-2-1_50KNC_2024-01-31_final
2024-02-24 11:36:22	ga_s2am_ard_3-2-1_51HVE_2024-02-24_final
2024-03-31 11:57:08	ga_s2am_ard_3-2-1_50HLH_2024-03-31_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

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