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
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HNJ_2015-10-22_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49JGN_2015-11-30_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HPH_2016-05-09_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHR_2016-05-18_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49JFM_2016-06-07_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_50JKS_2016-06-14_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50JQL_2016-06-18_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_49JHN_2016-06-24_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JLT_2016-06-24_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHR_2016-07-14_final.stac-item
2016-07-17 12:13:25	ga_s2am_ard_3-2-1_49JGK_2016-07-17_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGL_2016-10-12_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JKP_2017-03-31_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_50JKQ_2017-04-20_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKT_2017-07-29_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_50JPL_2017-11-27_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49JGL_2018-01-28_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGM_2018-03-09_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_50JPL_2018-03-17_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-07-17_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HMJ_2018-09-06_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMH_2018-09-19_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPK_2018-10-16_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-11-01_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JGK_2018-11-04_final.stac-item
2018-11-15 11:47:04	ga_s2am_ard_3-2-1_50HMH_2018-11-15_final.stac-item
2018-11-18 11:56:16	ga_s2am_ard_3-2-1_50JML_2018-11-18_final.stac-item
2018-12-01 12:04:52	ga_s2am_ard_3-2-1_49JGM_2018-12-01_final.stac-item
2018-12-28 11:56:44	ga_s2am_ard_3-2-1_50HMJ_2018-12-28_final.stac-item
2019-01-04 11:46:47	ga_s2am_ard_3-2-1_50HQH_2019-01-04_final.stac-item
2019-01-04 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2019-01-04_final.stac-item
2019-04-24 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2019-04-24_final.stac-item
2019-05-24 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-05-24_final.stac-item
2019-06-10 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-06-10_final.stac-item
2019-06-16 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-06-16_final.stac-item
2019-07-16 11:56:45	ga_s2am_ard_3-2-1_50HLK_2019-07-16_final.stac-item
2019-07-20 11:36:43	ga_s2am_ard_3-2-1_50HPK_2019-07-20_final.stac-item
2019-09-28 11:37:08	ga_s2am_ard_3-2-1_50HPH_2019-09-28_final.stac-item
2019-12-06 12:05:12	ga_s2am_ard_3-2-1_49JGL_2019-12-06_final.stac-item
2019-12-26 12:05:35	ga_s2am_ard_3-2-1_50JKP_2019-12-26_final.stac-item
2020-01-19 11:46:27	ga_s2am_ard_3-2-1_50HPK_2020-01-19_final.stac-item
2020-02-25 11:36:29	ga_s2am_ard_3-2-1_50HQK_2020-02-25_final.stac-item
2020-04-14 12:05:40	ga_s2am_ard_3-2-1_50JKP_2020-04-14_final.stac-item
2020-04-24 12:05:16	ga_s2am_ard_3-2-1_49JGL_2020-04-24_final.stac-item
2020-05-14 12:06:00	ga_s2am_ard_3-2-1_50JKN_2020-05-14_final.stac-item
2020-05-18 11:46:39	ga_s2am_ard_3-2-1_50HPK_2020-05-18_final.stac-item
2020-06-23 12:04:10	ga_s2am_ard_3-2-1_49KHR_2020-06-23_final.stac-item
2020-08-29 11:56:23	ga_s2am_ard_3-2-1_50JNL_2020-08-29_final.stac-item
2020-09-15 11:46:30	ga_s2am_ard_3-2-1_50JML_2020-09-15_final.stac-item
2020-09-25 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-09-25_final.stac-item
2020-10-01 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-10-01_final.stac-item
2020-12-01 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2020-12-01_final.stac-item
2021-01-23 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-01-23_final.stac-item
2021-03-27 11:56:38	ga_s2am_ard_3-2-1_50HLK_2021-03-27_final.stac-item
2021-04-22 12:14:37	ga_s2am_ard_3-2-1_49JGN_2021-04-22_final.stac-item
2021-04-23 11:46:26	ga_s2am_ard_3-2-1_50HQK_2021-04-23_final.stac-item
2021-05-20 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2021-05-20_final.stac-item
2021-06-02 11:47:11	ga_s2am_ard_3-2-1_50HMH_2021-06-02_final.stac-item
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final
2021-07-31 12:14:24	ga_s2am_ard_3-2-1_49KGP_2021-07-31_final.stac-item
2021-09-10 11:46:08	ga_s2am_ard_3-2-1_50JNM_2021-09-10_final.stac-item
2021-09-10 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-09-10_final
2021-10-20 11:45:45	ga_s2am_ard_3-2-1_50JNP_2021-10-20_final.stac-item
2021-10-20 11:45:56	ga_s2am_ard_3-2-1_50JPN_2021-10-20_final.stac-item
2021-11-25 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2021-11-25_final.stac-item
2021-12-09 11:46:31	ga_s2am_ard_3-2-1_50HNK_2021-12-09_final.stac-item
2021-12-15 12:04:31	ga_s2am_ard_3-2-1_49KGP_2021-12-15_final.stac-item
2021-12-22 11:55:57	ga_s2am_ard_3-2-1_50JLN_2021-12-22_final.stac-item
2022-02-06 12:14:26	ga_s2am_ard_3-2-1_49KGP_2022-02-06_final.stac-item
2022-03-02 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-03-02_final.stac-item
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final.stac-item
2022-05-31 11:56:48	ga_s2am_ard_3-2-1_50HLK_2022-05-31_final.stac-item
2022-07-23 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-07-23_final.stac-item
2022-07-30 11:55:16	ga_s2am_ard_3-2-1_50JNR_2022-07-30_final.stac-item
2022-07-30 11:56:35	ga_s2am_ard_3-2-1_50JLL_2022-07-30_final.stac-item
2022-08-09 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-08-09_final.stac-item
2022-09-25 11:45:14	ga_s2am_ard_3-2-1_50JPR_2022-09-25_final.stac-item
2022-10-01 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-10-01_final.stac-item
2022-10-21 12:05:42	ga_s2am_ard_3-2-1_50JKP_2022-10-21_final.stac-item
2022-12-17 11:56:29	ga_s2am_ard_3-2-1_50HNK_2022-12-17_final.stac-item
2023-02-28 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2023-02-28_final
2023-03-27 11:56:20	ga_s2am_ard_3-2-1_50JML_2023-03-27_final
2023-04-03 11:44:30	ga_s2am_ard_3-2-1_50JRT_2023-04-03_final
2023-04-06 11:56:11	ga_s2am_ard_3-2-1_50JLM_2023-04-06_final
2023-04-29 12:06:04	ga_s2am_ard_3-2-1_50JLM_2023-04-29_final
2023-05-09 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-05-09_final
2023-05-16 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2023-05-16_final
2023-05-23 11:46:33	ga_s2am_ard_3-2-1_50HQK_2023-05-23_final
2023-08-14 11:55:52	ga_s2am_ard_3-2-1_50JKP_2023-08-14_final
2023-09-20 11:46:28	ga_s2am_ard_3-2-1_50JML_2023-09-20_final
2023-09-29 12:13:57	ga_s2am_ard_3-2-1_49KHR_2023-09-29_final
2023-10-16 12:03:58	ga_s2am_ard_3-2-1_49KHR_2023-10-16_final
2023-10-23 11:56:30	ga_s2am_ard_3-2-1_50HNK_2023-10-23_final
2023-12-29 11:46:12	ga_s2am_ard_3-2-1_50JQL_2023-12-29_final
2024-01-04 12:06:01	ga_s2am_ard_3-2-1_50JLM_2024-01-04_final
2024-01-25 11:36:28	ga_s2am_ard_3-2-1_50HQK_2024-01-25_final
2024-01-31 11:57:15	ga_s2am_ard_3-2-1_50HMG_2024-01-31_final
2024-02-14 11:37:04	ga_s2am_ard_3-2-1_50HPH_2024-02-14_final
2024-02-17 11:46:46	ga_s2am_ard_3-2-1_50HPJ_2024-02-17_final
2024-03-24 12:05:02	ga_s2am_ard_3-2-1_49JGM_2024-03-24_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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