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
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_49KHR_2016-01-06_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JLN_2016-02-02_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49KHR_2016-02-15_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JMN_2016-03-03_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JLN_2016-06-24_final.stac-item
2016-07-11 11:56:11	ga_s2am_ard_3-2-1_50JNL_2016-07-11_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HPH_2016-07-15_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JMR_2016-07-21_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JGL_2016-12-01_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HPH_2016-12-05_final
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HNK_2016-12-28_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HNK_2017-02-03_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50JMM_2017-02-03_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_50JKM_2017-03-11_final.stac-item
2017-04-27 11:49:47	ga_s2am_ard_3-2-1_50HNK_2017-04-27_final.stac-item
2017-05-23 12:13:46	ga_s2am_ard_3-2-1_49KHR_2017-05-23_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50HLJ_2017-06-06_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50JLL_2017-07-26_final.stac-item
2017-11-03 11:56:07	ga_s2am_ard_3-2-1_50HMK_2017-11-03_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JLT_2017-12-16_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-28_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JNL_2018-06-08_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPP_2018-06-28_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JLS_2018-07-04_final.stac-item
2018-07-08 11:45:46	ga_s2am_ard_3-2-1_50HNK_2018-07-08_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50JNL_2018-07-28_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JNL_2018-09-06_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPL_2018-09-26_final.stac-item
2018-12-08 11:56:14	ga_s2am_ard_3-2-1_50JML_2018-12-08_final.stac-item
2018-12-25 11:46:48	ga_s2am_ard_3-2-1_50HMJ_2018-12-25_final.stac-item
2019-01-01 11:36:57	ga_s2am_ard_3-2-1_50HQH_2019-01-01_final.stac-item
2019-02-13 11:46:30	ga_s2am_ard_3-2-1_50HPK_2019-02-13_final.stac-item
2019-03-24 12:15:09	ga_s2am_ard_3-2-1_49JGL_2019-03-24_final.stac-item
2019-05-17 11:56:03	ga_s2am_ard_3-2-1_50JKN_2019-05-17_final.stac-item
2019-05-30 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-05-30_final.stac-item
2019-06-16 11:56:29	ga_s2am_ard_3-2-1_50JLL_2019-06-16_final.stac-item
2019-07-09 12:05:46	ga_s2am_ard_3-2-1_50JKP_2019-07-09_final.stac-item
2019-12-26 12:04:34	ga_s2am_ard_3-2-1_50JLT_2019-12-26_final.stac-item
2020-02-01 11:56:03	ga_s2am_ard_3-2-1_50JLM_2020-02-01_final.stac-item
2020-02-08 11:45:42	ga_s2am_ard_3-2-1_50JPN_2020-02-08_final.stac-item
2020-02-18 11:45:48	ga_s2am_ard_3-2-1_50JNN_2020-02-18_final.stac-item
2020-03-02 11:55:30	ga_s2am_ard_3-2-1_50JNP_2020-03-02_final.stac-item
2020-03-02 11:57:05	ga_s2am_ard_3-2-1_50HLH_2020-03-02_final.stac-item
2020-04-08 11:46:06	ga_s2am_ard_3-2-1_50JNM_2020-04-08_final.stac-item
2020-04-15 11:37:06	ga_s2am_ard_3-2-1_50HPH_2020-04-15_final.stac-item
2020-05-14 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-05-14_final.stac-item
2020-07-23 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-07-23_final.stac-item
2020-09-22 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-09-22_final.stac-item
2021-01-06 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-01-06_final.stac-item
2021-02-09 11:37:20	ga_s2am_ard_3-2-1_50HPG_2021-02-09_final
2021-02-28 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-02-28_final.stac-item
2021-03-27 11:56:38	ga_s2am_ard_3-2-1_50HLK_2021-03-27_final.stac-item
2021-04-23 11:46:22	ga_s2am_ard_3-2-1_50JML_2021-04-23_final.stac-item
2021-06-21 12:13:59	ga_s2am_ard_3-2-1_49KGR_2021-06-21_final.stac-item
2021-07-02 11:46:28	ga_s2am_ard_3-2-1_50JML_2021-07-02_final.stac-item
2021-07-02 11:46:32	ga_s2am_ard_3-2-1_50HQK_2021-07-02_final.stac-item
2021-07-11 12:13:57	ga_s2am_ard_3-2-1_49KHR_2021-07-11_final.stac-item
2021-08-04 11:56:21	ga_s2am_ard_3-2-1_50JNL_2021-08-04_final.stac-item
2021-11-28 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-11-28_final.stac-item
2021-12-15 12:05:26	ga_s2am_ard_3-2-1_50JKQ_2021-12-15_final.stac-item
2021-12-29 11:46:28	ga_s2am_ard_3-2-1_50JML_2021-12-29_final.stac-item
2022-01-01 11:55:48	ga_s2am_ard_3-2-1_50JKP_2022-01-01_final.stac-item
2022-02-07 11:46:33	ga_s2am_ard_3-2-1_50HPK_2022-02-07_final.stac-item
2022-02-13 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-13_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_50JKT_2022-04-04_final.stac-item
2022-05-11 11:55:10	ga_s2am_ard_3-2-1_50JNR_2022-05-11_final.stac-item
2022-05-21 11:54:47	ga_s2am_ard_3-2-1_50JMT_2022-05-21_final.stac-item
2022-05-28 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-05-28_final.stac-item
2022-06-23 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-06-23_final.stac-item
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-06-23_final.stac-item
2022-08-09 11:56:05	ga_s2am_ard_3-2-1_50JMN_2022-08-09_final.stac-item
2022-09-02 11:37:00	ga_s2am_ard_3-2-1_50HQJ_2022-09-02_final.stac-item
2022-10-01 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-10-01_final.stac-item
2022-11-04 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2022-11-04_final.stac-item
2022-11-30 12:04:31	ga_s2am_ard_3-2-1_49KGP_2022-11-30_final.stac-item
2022-12-03 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-12-03_final.stac-item
2022-12-07 11:56:30	ga_s2am_ard_3-2-1_50HNK_2022-12-07_final.stac-item
2022-12-20 12:04:41	ga_s2am_ard_3-2-1_50JKT_2022-12-20_final.stac-item
2023-02-11 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-11_nrt.stac-item
2023-03-13 12:14:23	ga_s2am_ard_3-2-1_49KGP_2023-03-13_final
2023-05-29 12:05:12	ga_s2am_ard_3-2-1_50JLR_2023-05-29_final
2023-06-15 11:56:08	ga_s2am_ard_3-2-1_50JNM_2023-06-15_final
2023-06-22 11:47:13	ga_s2am_ard_3-2-1_50HMH_2023-06-22_final
2023-07-02 11:47:07	ga_s2am_ard_3-2-1_50HPH_2023-07-02_final
2023-07-15 11:55:58	ga_s2am_ard_3-2-1_50JMN_2023-07-15_final
2023-08-11 11:45:26	ga_s2am_ard_3-2-1_50JPQ_2023-08-11_final
2023-08-31 11:47:07	ga_s2am_ard_3-2-1_50HPH_2023-08-31_final
2023-09-26 12:04:33	ga_s2am_ard_3-2-1_49KGP_2023-09-26_final
2023-10-17 11:37:02	ga_s2am_ard_3-2-1_50HQH_2023-10-17_final
2023-11-08 12:14:59	ga_s2am_ard_3-2-1_49JFM_2023-11-08_final
2023-11-12 11:55:46	ga_s2am_ard_3-2-1_50JKP_2023-11-12_final
2023-12-22 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2023-12-22_final
2023-12-25 12:06:01	ga_s2am_ard_3-2-1_50JLM_2023-12-25_final
2024-01-08 11:47:13	ga_s2am_ard_3-2-1_50HPG_2024-01-08_final
2024-02-13 12:05:38	ga_s2am_ard_3-2-1_50JKP_2024-02-13_final
2024-03-01 11:55:59	ga_s2am_ard_3-2-1_50JKN_2024-03-01_final
2024-03-07 12:14:57	ga_s2am_ard_3-2-1_49JGM_2024-03-07_final
2024-03-17 12:14:27	ga_s2am_ard_3-2-1_49KGP_2024-03-17_final
2024-04-13 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2024-04-13_final
2024-05-03 12:05:54	ga_s2am_ard_3-2-1_50JLN_2024-05-03_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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