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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50KKA_2015-12-17_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50KQC_2016-01-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50KPC_2016-03-03_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51HUD_2016-05-23_final.stac-item
2016-08-31 11:22:38	ga_s2am_ard_3-2-1_51HVC_2016-08-31_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50JMM_2016-09-06_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGM_2016-11-11_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGK_2016-11-21_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JNM_2016-12-15_final.stac-item
2017-03-08 11:56:00	ga_s2am_ard_3-2-1_50JMM_2017-03-08_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JKN_2017-04-07_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JNM_2017-06-26_final.stac-item
2017-07-06 11:56:07	ga_s2am_ard_3-2-1_50JNM_2017-07-06_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50HPH_2017-07-30_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKA_2017-11-19_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JHN_2017-11-26_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HQJ_2018-01-19_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49JGM_2018-04-05_final.stac-item
2018-08-16 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2018-08-16_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNL_2018-09-19_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-10-12_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JNN_2018-10-26_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KMC_2018-10-29_final.stac-item
2019-02-26 11:56:18	ga_s2am_ard_3-2-1_50JML_2019-02-26_final.stac-item
2019-04-07 11:55:54	ga_s2am_ard_3-2-1_50JMN_2019-04-07_final.stac-item
2019-06-20 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-06-20_final.stac-item
2019-07-03 11:46:09	ga_s2am_ard_3-2-1_50JQM_2019-07-03_final.stac-item
2019-07-29 12:05:05	ga_s2am_ard_3-2-1_49JGM_2019-07-29_final.stac-item
2019-08-15 11:53:35	ga_s2am_ard_3-2-1_50KQB_2019-08-15_final.stac-item
2019-10-07 12:04:27	ga_s2am_ard_3-2-1_50KLU_2019-10-07_final.stac-item
2019-10-24 11:56:03	ga_s2am_ard_3-2-1_50JKN_2019-10-24_final.stac-item
2019-11-20 11:47:07	ga_s2am_ard_3-2-1_50HNH_2019-11-20_final.stac-item
2019-12-20 11:43:41	ga_s2am_ard_3-2-1_50KRA_2019-12-20_final.stac-item
2019-12-29 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-12-29_final.stac-item
2020-01-05 12:03:18	ga_s2am_ard_3-2-1_50KMC_2020-01-05_final.stac-item
2020-01-12 11:53:19	ga_s2am_ard_3-2-1_50KNC_2020-01-12_final.stac-item
2020-02-24 12:05:36	ga_s2am_ard_3-2-1_50JKP_2020-02-24_final.stac-item
2020-04-12 11:26:31	ga_s2am_ard_3-2-1_51HUE_2020-04-12_final.stac-item
2020-05-18 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-05-18_final.stac-item
2020-05-31 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-05-31_final.stac-item
2020-07-01 11:26:49	ga_s2am_ard_3-2-1_51HVD_2020-07-01_final.stac-item
2020-07-13 12:05:45	ga_s2am_ard_3-2-1_50JKP_2020-07-13_final.stac-item
2020-07-23 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-07-23_final.stac-item
2020-08-06 11:43:24	ga_s2am_ard_3-2-1_50KRC_2020-08-06_final.stac-item
2020-08-29 11:55:58	ga_s2am_ard_3-2-1_50JMN_2020-08-29_final.stac-item
2020-09-18 11:56:04	ga_s2am_ard_3-2-1_50JKN_2020-09-18_final.stac-item
2020-09-21 12:04:44	ga_s2am_ard_3-2-1_50JLT_2020-09-21_final.stac-item
2020-11-07 11:56:04	ga_s2am_ard_3-2-1_50JKN_2020-11-07_final.stac-item
2020-11-23 12:14:29	ga_s2am_ard_3-2-1_49KGP_2020-11-23_final.stac-item
2020-11-30 12:05:51	ga_s2am_ard_3-2-1_50JLN_2020-11-30_final.stac-item
2021-01-03 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-01-03_final.stac-item
2021-01-10 11:35:51	ga_s2am_ard_3-2-1_50JQN_2021-01-10_final.stac-item
2021-01-16 11:54:09	ga_s2am_ard_3-2-1_50KNV_2021-01-16_final.stac-item
2021-02-28 12:04:39	ga_s2am_ard_3-2-1_50JLT_2021-02-28_final.stac-item
2021-03-10 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-03-10_final.stac-item
2021-03-10 12:06:04	ga_s2am_ard_3-2-1_50JLM_2021-03-10_final.stac-item
2021-03-17 11:56:29	ga_s2am_ard_3-2-1_50HNK_2021-03-17_final.stac-item
2021-05-06 11:55:52	ga_s2am_ard_3-2-1_50JMN_2021-05-06_final.stac-item
2021-07-01 12:14:58	ga_s2am_ard_3-2-1_49JGM_2021-07-01_final.stac-item
2021-08-24 11:53:19	ga_s2am_ard_3-2-1_50KQC_2021-08-24_final.stac-item
2021-09-06 12:04:25	ga_s2am_ard_3-2-1_50KLU_2021-09-06_final.stac-item
2021-10-23 11:54:06	ga_s2am_ard_3-2-1_50KQV_2021-10-23_final.stac-item
2021-10-30 11:47:11	ga_s2am_ard_3-2-1_50HNH_2021-10-30_final.stac-item
2021-11-05 12:05:44	ga_s2am_ard_3-2-1_50JKP_2021-11-05_final.stac-item
2021-11-29 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-11-29_final.stac-item
2021-12-19 11:47:25	ga_s2am_ard_3-2-1_50HMG_2021-12-19_final
2021-12-29 11:43:24	ga_s2am_ard_3-2-1_50KRC_2021-12-29_final.stac-item
2022-01-07 12:15:01	ga_s2am_ard_3-2-1_49JFM_2022-01-07_final.stac-item
2022-01-11 11:53:26	ga_s2am_ard_3-2-1_50KNC_2022-01-11_final.stac-item
2022-02-14 11:36:26	ga_s2am_ard_3-2-1_50JPL_2022-02-14_final.stac-item
2022-02-24 11:36:29	ga_s2am_ard_3-2-1_50JPL_2022-02-24_final.stac-item
2022-03-05 12:05:45	ga_s2am_ard_3-2-1_50JKP_2022-03-05_final.stac-item
2022-03-12 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2022-03-12_final.stac-item
2022-04-11 11:56:53	ga_s2am_ard_3-2-1_50HMJ_2022-04-11_final.stac-item
2022-04-14 12:03:23	ga_s2am_ard_3-2-1_50KNC_2022-04-14_final.stac-item
2022-05-08 11:46:23	ga_s2am_ard_3-2-1_50JPL_2022-05-08_final.stac-item
2022-07-14 11:36:59	ga_s2am_ard_3-2-1_51HTD_2022-07-14_final.stac-item
2022-07-27 11:46:47	ga_s2am_ard_3-2-1_50HNK_2022-07-27_final.stac-item
2022-08-12 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-08-12_final.stac-item
2022-08-29 11:56:35	ga_s2am_ard_3-2-1_50JML_2022-08-29_final.stac-item
2022-09-18 11:56:45	ga_s2am_ard_3-2-1_50HMK_2022-09-18_final.stac-item
2022-10-19 11:26:50	ga_s2am_ard_3-2-1_51HUD_2022-10-19_final.stac-item
2022-12-04 11:46:16	ga_s2am_ard_3-2-1_50JQL_2022-12-04_final.stac-item
2022-12-07 11:56:00	ga_s2am_ard_3-2-1_50JKN_2022-12-07_final.stac-item
2023-02-08 12:04:12	ga_s2am_ard_3-2-1_50KKV_2023-02-08_final
2023-02-15 11:56:15	ga_s2am_ard_3-2-1_50JNL_2023-02-15_final
2023-03-01 11:36:55	ga_s2am_ard_3-2-1_51HUC_2023-03-01_final
2023-05-03 11:46:16	ga_s2am_ard_3-2-1_50JQL_2023-05-03_final
2023-07-22 11:46:42	ga_s2am_ard_3-2-1_50HNK_2023-07-22_final
2023-07-22 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2023-07-22_final
2023-08-21 11:46:14	ga_s2am_ard_3-2-1_50JNM_2023-08-21_final
2023-09-13 11:55:46	ga_s2am_ard_3-2-1_50JLP_2023-09-13_final
2023-11-22 11:56:14	ga_s2am_ard_3-2-1_50JNL_2023-11-22_final
2023-12-29 11:46:12	ga_s2am_ard_3-2-1_50JQL_2023-12-29_final
2024-01-18 11:44:11	ga_s2am_ard_3-2-1_50KQU_2024-01-18_final
2024-01-31 11:56:21	ga_s2am_ard_3-2-1_50JLL_2024-01-31_final
2024-04-01 11:26:42	ga_s2am_ard_3-2-1_51HVD_2024-04-01_final
2024-04-23 12:03:26	ga_s2am_ard_3-2-1_50KMC_2024-04-23_nrt
2024-04-23 12:04:45	ga_s2am_ard_3-2-1_50JKT_2024-04-23_nrt
2024-04-26 12:14:43	ga_s2am_ard_3-2-1_49JGN_2024-04-26_nrt

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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