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
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGN_2016-01-26_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JMN_2016-02-02_final.stac-item
2016-06-21 11:56:09	ga_s2am_ard_3-2-1_50JMM_2016-06-21_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HLK_2016-07-01_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JMM_2016-08-10_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50HLK_2016-08-20_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JMN_2016-08-30_final.stac-item
2016-09-25 12:13:39	ga_s2am_ard_3-2-1_49KGR_2016-09-25_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HPH_2016-10-23_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLP_2016-11-11_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HPG_2016-11-22_final
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLK_2016-12-08_final.stac-item
2017-01-03 12:13:15	ga_s2am_ard_3-2-1_49JGN_2017-01-03_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50JMM_2017-02-03_final.stac-item
2017-04-30 12:04:44	ga_s2am_ard_3-2-1_50JLS_2017-04-30_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_49JHN_2017-05-10_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HMH_2017-05-24_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_49KGR_2017-07-12_final.stac-item
2017-08-21 12:13:36	ga_s2am_ard_3-2-1_49KGQ_2017-08-21_final.stac-item
2017-10-30 12:13:43	ga_s2am_ard_3-2-1_49KHR_2017-10-30_final.stac-item
2017-11-17 11:36:01	ga_s2am_ard_3-2-1_50JPL_2017-11-17_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50HPJ_2017-11-20_final.stac-item
2018-01-02 11:56:01	ga_s2am_ard_3-2-1_50JNL_2018-01-02_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_50JKP_2018-01-25_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50JLQ_2018-02-01_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPP_2018-06-28_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JNN_2018-06-28_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JNL_2018-07-11_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JGN_2018-07-17_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50HQK_2018-09-03_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JNM_2018-09-06_final.stac-item
2018-12-11 12:05:43	ga_s2am_ard_3-2-1_50JLN_2018-12-11_final.stac-item
2019-01-30 12:04:28	ga_s2am_ard_3-2-1_49KGP_2019-01-30_final.stac-item
2019-02-03 11:46:45	ga_s2am_ard_3-2-1_50HPJ_2019-02-03_final.stac-item
2019-02-13 11:46:30	ga_s2am_ard_3-2-1_50HPK_2019-02-13_final.stac-item
2019-04-30 12:05:18	ga_s2am_ard_3-2-1_49JGL_2019-04-30_final.stac-item
2019-05-07 11:56:44	ga_s2am_ard_3-2-1_50HLK_2019-05-07_final.stac-item
2019-07-02 12:14:03	ga_s2am_ard_3-2-1_49KGR_2019-07-02_final.stac-item
2019-07-29 12:05:56	ga_s2am_ard_3-2-1_50JLN_2019-07-29_final.stac-item
2019-09-08 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2019-09-08_final.stac-item
2019-09-28 11:36:39	ga_s2am_ard_3-2-1_50HPK_2019-09-28_final.stac-item
2019-10-04 11:55:44	ga_s2am_ard_3-2-1_50JLP_2019-10-04_final.stac-item
2019-11-06 12:05:44	ga_s2am_ard_3-2-1_50JKP_2019-11-06_final.stac-item
2019-12-03 11:57:08	ga_s2am_ard_3-2-1_50HLH_2019-12-03_final.stac-item
2019-12-27 11:36:43	ga_s2am_ard_3-2-1_50HQJ_2019-12-27_final.stac-item
2020-01-25 12:04:36	ga_s2am_ard_3-2-1_49JHN_2020-01-25_final.stac-item
2020-02-01 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2020-02-01_final.stac-item
2020-02-11 11:55:02	ga_s2am_ard_3-2-1_50JMR_2020-02-11_final.stac-item
2020-03-05 12:06:00	ga_s2am_ard_3-2-1_50JLM_2020-03-05_final.stac-item
2020-03-15 12:05:04	ga_s2am_ard_3-2-1_50JLR_2020-03-15_final.stac-item
2020-05-14 12:05:34	ga_s2am_ard_3-2-1_49JGK_2020-05-14_final.stac-item
2020-07-24 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2020-07-24_final.stac-item
2020-07-27 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-07-27_final.stac-item
2020-09-22 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-09-22_final.stac-item
2020-11-27 11:55:55	ga_s2am_ard_3-2-1_50JKN_2020-11-27_final.stac-item
2020-12-03 12:14:40	ga_s2am_ard_3-2-1_49JGN_2020-12-03_final.stac-item
2021-01-19 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2021-01-19_final.stac-item
2021-02-01 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2021-02-01_final.stac-item
2021-04-03 11:46:27	ga_s2am_ard_3-2-1_50HQK_2021-04-03_final.stac-item
2021-04-06 11:56:14	ga_s2am_ard_3-2-1_50JNL_2021-04-06_final.stac-item
2021-04-16 11:56:05	ga_s2am_ard_3-2-1_50JLM_2021-04-16_final.stac-item
2021-07-05 11:55:49	ga_s2am_ard_3-2-1_50JKP_2021-07-05_final.stac-item
2021-07-25 11:56:33	ga_s2am_ard_3-2-1_50HNK_2021-07-25_final.stac-item
2021-08-27 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-27_final.stac-item
2022-01-17 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-01-17_final.stac-item
2022-03-18 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-18_final.stac-item
2022-05-24 12:04:53	ga_s2am_ard_3-2-1_49JGN_2022-05-24_final.stac-item
2022-06-03 12:05:05	ga_s2am_ard_3-2-1_49JHM_2022-06-03_final.stac-item
2022-06-20 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-06-20_final.stac-item
2022-07-30 11:56:58	ga_s2am_ard_3-2-1_50HMJ_2022-07-30_final.stac-item
2022-08-02 12:05:33	ga_s2am_ard_3-2-1_50JLQ_2022-08-02_final.stac-item
2022-08-05 12:14:05	ga_s2am_ard_3-2-1_49KHR_2022-08-05_final.stac-item
2022-09-11 12:05:51	ga_s2am_ard_3-2-1_50JKP_2022-09-11_final.stac-item
2022-09-12 11:36:59	ga_s2am_ard_3-2-1_50HQJ_2022-09-12_final.stac-item
2022-11-27 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2022-11-27_final.stac-item
2023-01-12 12:14:39	ga_s2am_ard_3-2-1_49JGN_2023-01-12_final.stac-item
2023-01-12 12:15:08	ga_s2am_ard_3-2-1_49JGL_2023-01-12_final.stac-item
2023-02-02 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-02-02_final
2023-02-05 11:55:54	ga_s2am_ard_3-2-1_50JMN_2023-02-05_final
2023-02-18 12:05:09	ga_s2am_ard_3-2-1_49JGL_2023-02-18_final
2023-02-19 11:36:23	ga_s2am_ard_3-2-1_50JPL_2023-02-19_nrt.stac-item
2023-03-03 12:13:55	ga_s2am_ard_3-2-1_49KGR_2023-03-03_final
2023-03-27 11:55:54	ga_s2am_ard_3-2-1_50JLN_2023-03-27_final
2023-04-29 12:04:57	ga_s2am_ard_3-2-1_50JKS_2023-04-29_final
2023-05-20 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2023-05-20_final
2023-05-23 11:44:57	ga_s2am_ard_3-2-1_50JPS_2023-05-23_final
2023-06-08 12:04:46	ga_s2am_ard_3-2-1_50JKT_2023-06-08_final
2023-06-19 11:37:25	ga_s2am_ard_3-2-1_50HPG_2023-06-19_final
2023-07-05 11:56:41	ga_s2am_ard_3-2-1_50HMK_2023-07-05_final
2023-07-31 12:14:47	ga_s2am_ard_3-2-1_49JGN_2023-07-31_final
2023-08-01 11:46:28	ga_s2am_ard_3-2-1_50JNL_2023-08-01_final
2023-09-16 12:05:44	ga_s2am_ard_3-2-1_50JKP_2023-09-16_final
2023-09-23 11:56:06	ga_s2am_ard_3-2-1_50JNM_2023-09-23_final
2023-10-23 11:56:22	ga_s2am_ard_3-2-1_50JLL_2023-10-23_final
2023-11-09 11:46:37	ga_s2am_ard_3-2-1_50HNK_2023-11-09_final
2023-11-25 12:04:34	ga_s2am_ard_3-2-1_50JLT_2023-11-25_final
2023-12-02 11:56:10	ga_s2am_ard_3-2-1_50JNL_2023-12-02_final
2023-12-06 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2023-12-06_final
2024-01-18 11:47:01	ga_s2am_ard_3-2-1_50HMH_2024-01-18_final
2024-04-20 11:56:29	ga_s2am_ard_3-2-1_50JLL_2024-04-20_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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