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
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLS_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNN_2016-05-29_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JML_2016-08-20_final
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JNN_2016-10-26_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMJ_2016-11-15_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JML_2017-05-27_final.stac-item
2017-06-12 12:14:42	ga_s2am_ard_3-2-1_49JGL_2017-06-12_final.stac-item
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50HMJ_2017-08-12_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_49JGM_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKS_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKT_2017-09-17_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JLT_2017-09-17_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KGP_2017-10-07_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HLH_2018-01-19_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HPK_2018-02-08_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGN_2018-03-09_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-03-09_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMH_2018-03-30_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50JNL_2018-03-30_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKN_2018-04-05_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGL_2018-04-25_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JLP_2018-04-25_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMK_2018-04-29_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JKN_2018-05-02_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKQ_2018-05-25_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JML_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JNL_2018-05-29_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLP_2018-06-11_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLR_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JMT_2018-06-21_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGN_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JHM_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKR_2018-06-24_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49JGL_2018-06-27_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JKN_2018-07-01_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JNQ_2018-07-08_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLQ_2018-07-11_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JMP_2018-07-11_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JMT_2018-07-11_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JNS_2018-07-11_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLJ_2018-07-31_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JLS_2018-08-20_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JMT_2018-08-20_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JNS_2018-08-20_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHP_2018-08-23_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLT_2018-08-30_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JMR_2018-08-30_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JMM_2018-09-06_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JNP_2018-09-26_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMR_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JNT_2018-09-29_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-10-05_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLS_2018-10-09_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKQ_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKT_2018-10-12_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-15_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLS_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JMT_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JNS_2018-10-19_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JLP_2018-10-29_final.stac-item
2018-11-04 12:13:17	ga_s2am_ard_3-2-1_49JGN_2018-11-04_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HPJ_2018-11-05_final.stac-item
2018-11-25 11:46:44	ga_s2am_ard_3-2-1_50HNJ_2018-11-25_final.stac-item
2018-12-08 11:56:46	ga_s2am_ard_3-2-1_50HLJ_2018-12-08_final.stac-item
2018-12-25 11:47:02	ga_s2am_ard_3-2-1_50HMH_2018-12-25_final.stac-item
2018-12-31 12:05:31	ga_s2am_ard_3-2-1_50JLP_2018-12-31_final.stac-item
2019-01-03 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-01-03_final.stac-item
2019-01-07 11:55:34	ga_s2am_ard_3-2-1_50JMP_2019-01-07_final.stac-item
2019-07-26 11:56:13	ga_s2am_ard_3-2-1_50JMM_2019-07-26_final.stac-item
2019-08-28 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-08-28_final.stac-item
2019-09-07 12:06:09	ga_s2am_ard_3-2-1_50JKM_2019-09-07_final.stac-item
2020-03-16 11:37:03	ga_s2am_ard_3-2-1_50HPH_2020-03-16_final.stac-item
2020-04-28 11:46:56	ga_s2am_ard_3-2-1_50HQH_2020-04-28_final.stac-item
2020-11-04 11:46:38	ga_s2am_ard_3-2-1_50HPK_2020-11-04_final.stac-item
2021-01-03 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-01-03_final.stac-item
2021-04-16 11:57:17	ga_s2am_ard_3-2-1_50HLG_2021-04-16_final
2021-04-23 11:46:29	ga_s2am_ard_3-2-1_50HPK_2021-04-23_final.stac-item
2021-04-29 12:04:46	ga_s2am_ard_3-2-1_50JMS_2021-04-29_final.stac-item
2021-05-06 11:55:52	ga_s2am_ard_3-2-1_50JMN_2021-05-06_final.stac-item
2021-05-19 12:05:38	ga_s2am_ard_3-2-1_50JKP_2021-05-19_final.stac-item
2021-06-15 11:54:45	ga_s2am_ard_3-2-1_50JLT_2021-06-15_final.stac-item
2021-06-15 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2021-06-15_final.stac-item
2021-06-15 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-06-15_final.stac-item
2021-06-18 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-06-18_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-07-05 11:54:47	ga_s2am_ard_3-2-1_50JLT_2021-07-05_final.stac-item
2021-07-08 12:05:54	ga_s2am_ard_3-2-1_50JLN_2021-07-08_final.stac-item
2021-07-19 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2021-07-19_final.stac-item
2021-08-17 12:05:16	ga_s2am_ard_3-2-1_50JLR_2021-08-17_final.stac-item
2021-08-27 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-08-27_final.stac-item
2021-09-06 12:03:45	ga_s2am_ard_3-2-1_49KHS_2021-09-06_final
2021-09-26 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2021-09-26_final.stac-item
2022-06-10 11:55:44	ga_s2am_ard_3-2-1_50JNP_2022-06-10_final.stac-item
2022-07-30 11:57:05	ga_s2am_ard_3-2-1_50HMJ_2022-07-30_final.stac-item
2022-08-06 11:46:52	ga_s2am_ard_3-2-1_50HMK_2022-08-06_final.stac-item
2022-10-11 12:05:06	ga_s2am_ard_3-2-1_49JGM_2022-10-11_final.stac-item
2023-04-02 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-04-02_final
2023-06-18 12:06:04	ga_s2am_ard_3-2-1_50JLM_2023-06-18_final
2023-09-06 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-09-06_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

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