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
2015-10-01 12:14:44	ga_s2am_ard_3-2-1_49JGM_2015-10-01_final.stac-item
2015-10-08 12:03:08	ga_s2am_ard_3-2-1_50JKP_2015-10-08_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HNH_2015-12-21_final.stac-item
2015-12-27 12:05:25	ga_s2am_ard_3-2-1_49JGM_2015-12-27_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HQJ_2016-01-07_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNM_2016-03-03_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_50HPJ_2016-04-06_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KNC_2016-05-22_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKS_2016-07-24_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_50KKA_2016-09-25_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMG_2016-11-15_final
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JLR_2017-01-30_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JNN_2017-07-16_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50JLN_2017-10-17_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50JKP_2017-11-06_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGM_2017-11-26_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50HPH_2017-12-10_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNH_2018-05-09_final.stac-item
2018-05-15 12:02:52	ga_s2am_ard_3-2-1_50KMC_2018-05-15_final.stac-item
2018-11-25 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2018-11-25_final.stac-item
2018-12-08 11:53:48	ga_s2am_ard_3-2-1_50KMA_2018-12-08_final.stac-item
2018-12-14 12:14:47	ga_s2am_ard_3-2-1_49JGM_2018-12-14_final.stac-item
2019-02-26 11:56:13	ga_s2am_ard_3-2-1_50JNL_2019-02-26_final.stac-item
2019-03-01 12:03:36	ga_s2am_ard_3-2-1_50KLB_2019-03-01_final.stac-item
2019-04-20 12:05:00	ga_s2am_ard_3-2-1_50JKS_2019-04-20_final.stac-item
2019-04-23 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-04-23_final.stac-item
2019-04-23 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-04-23_final.stac-item
2019-05-11 11:36:23	ga_s2am_ard_3-2-1_50JQL_2019-05-11_final.stac-item
2019-05-30 12:05:43	ga_s2am_ard_3-2-1_50JKP_2019-05-30_final.stac-item
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-07-23 11:46:28	ga_s2am_ard_3-2-1_50JNL_2019-07-23_final.stac-item
2019-10-17 12:04:46	ga_s2am_ard_3-2-1_50JKT_2019-10-17_final.stac-item
2019-12-07 11:36:35	ga_s2am_ard_3-2-1_50HPK_2019-12-07_final.stac-item
2020-02-04 12:03:51	ga_s2am_ard_3-2-1_49KHR_2020-02-04_final.stac-item
2020-02-05 11:36:25	ga_s2am_ard_3-2-1_50HQK_2020-02-05_final.stac-item
2020-02-07 12:13:46	ga_s2am_ard_3-2-1_49KHR_2020-02-07_final.stac-item
2020-02-14 12:05:22	ga_s2am_ard_3-2-1_49JGK_2020-02-14_final.stac-item
2020-03-02 11:53:20	ga_s2am_ard_3-2-1_50KNC_2020-03-02_final.stac-item
2020-03-02 11:55:55	ga_s2am_ard_3-2-1_50JKN_2020-03-02_final.stac-item
2020-03-16 11:36:30	ga_s2am_ard_3-2-1_50HQK_2020-03-16_final.stac-item
2020-04-24 12:05:28	ga_s2am_ard_3-2-1_50JKQ_2020-04-24_final.stac-item
2020-05-07 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2020-05-07_final.stac-item
2020-05-18 11:47:12	ga_s2am_ard_3-2-1_50HNH_2020-05-18_final.stac-item
2020-07-23 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-07-23_final.stac-item
2020-07-23 12:05:46	ga_s2am_ard_3-2-1_50JKP_2020-07-23_final.stac-item
2020-10-08 11:56:17	ga_s2am_ard_3-2-1_50JLM_2020-10-08_final.stac-item
2020-10-15 11:46:21	ga_s2am_ard_3-2-1_50JQL_2020-10-15_final.stac-item
2020-11-07 11:56:45	ga_s2am_ard_3-2-1_50HLK_2020-11-07_final.stac-item
2021-01-03 11:43:21	ga_s2am_ard_3-2-1_50KQC_2021-01-03_final.stac-item
2021-01-03 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-01-03_final.stac-item
2021-01-16 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-01-16_final.stac-item
2021-01-23 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-01-23_final.stac-item
2021-02-02 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-02-02_final
2021-05-16 11:55:59	ga_s2am_ard_3-2-1_50JKN_2021-05-16_final.stac-item
2021-07-19 11:35:54	ga_s2am_ard_3-2-1_50JQN_2021-07-19_final.stac-item
2021-07-25 11:53:50	ga_s2am_ard_3-2-1_50KQA_2021-07-25_final.stac-item
2021-09-07 11:37:13	ga_s2am_ard_3-2-1_50HPH_2021-09-07_final.stac-item
2021-09-16 12:04:29	ga_s2am_ard_3-2-1_50KKU_2021-09-16_final.stac-item
2021-09-29 12:14:32	ga_s2am_ard_3-2-1_49KGP_2021-09-29_final.stac-item
2021-10-23 11:56:09	ga_s2am_ard_3-2-1_50JNM_2021-10-23_final.stac-item
2021-11-18 12:13:54	ga_s2am_ard_3-2-1_50KKA_2021-11-18_final.stac-item
2021-11-19 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-11-19_final.stac-item
2021-12-19 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-12-19_final.stac-item
2021-12-25 12:05:57	ga_s2am_ard_3-2-1_50JKN_2021-12-25_final.stac-item
2022-01-01 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-01_final.stac-item
2022-01-11 11:53:44	ga_s2am_ard_3-2-1_50KMB_2022-01-11_final.stac-item
2022-01-11 11:56:01	ga_s2am_ard_3-2-1_50JKN_2022-01-11_final.stac-item
2022-01-27 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-01-27_final.stac-item
2022-03-02 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-03-02_final.stac-item
2022-04-25 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2022-04-25_final.stac-item
2022-06-20 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-06-20_final.stac-item
2022-07-16 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-07-16_final.stac-item
2022-07-17 11:45:17	ga_s2am_ard_3-2-1_50JQR_2022-07-17_final.stac-item
2022-07-20 11:55:53	ga_s2am_ard_3-2-1_50JLP_2022-07-20_final.stac-item
2022-09-02 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-09-02_final.stac-item
2022-09-18 11:53:26	ga_s2am_ard_3-2-1_50KQC_2022-09-18_final.stac-item
2022-09-18 11:56:45	ga_s2am_ard_3-2-1_50HMK_2022-09-18_final.stac-item
2022-12-07 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2022-12-07_final.stac-item
2022-12-20 12:04:38	ga_s2am_ard_3-2-1_50JLT_2022-12-20_final.stac-item
2023-01-06 11:55:45	ga_s2am_ard_3-2-1_50JKP_2023-01-06_final.stac-item
2023-02-01 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-02-01_final.stac-item
2023-02-01 12:13:57	ga_s2am_ard_3-2-1_49KGR_2023-02-01_final
2023-02-22 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-02-22_nrt.stac-item
2023-02-22 11:46:27	ga_s2am_ard_3-2-1_50HQK_2023-02-22_final
2023-04-23 11:47:23	ga_s2am_ard_3-2-1_50HMG_2023-04-23_final
2023-04-29 12:04:31	ga_s2am_ard_3-2-1_49KGP_2023-04-29_final
2023-05-23 11:46:22	ga_s2am_ard_3-2-1_50JPL_2023-05-23_final
2023-06-01 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-06-01_final
2023-07-12 11:46:24	ga_s2am_ard_3-2-1_50JPL_2023-07-12_final
2023-07-21 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-07-21_final
2023-08-01 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-01_final
2023-09-27 11:37:09	ga_s2am_ard_3-2-1_50HPH_2023-09-27_final
2023-10-26 12:04:31	ga_s2am_ard_3-2-1_49KGP_2023-10-26_final
2023-12-08 12:15:05	ga_s2am_ard_3-2-1_49JGL_2023-12-08_final
2023-12-22 11:56:04	ga_s2am_ard_3-2-1_50JMM_2023-12-22_final
2024-01-01 11:53:21	ga_s2am_ard_3-2-1_50KNC_2024-01-01_final
2024-01-04 12:03:55	ga_s2am_ard_3-2-1_50KKA_2024-01-04_final
2024-01-24 12:03:31	ga_s2am_ard_3-2-1_50KMB_2024-01-24_final
2024-03-08 11:45:12	ga_s2am_ard_3-2-1_50JNR_2024-03-08_final
2024-03-08 11:47:03	ga_s2am_ard_3-2-1_50HPH_2024-03-08_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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