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
2015-11-14 11:54:02	ga_s2am_ard_3-2-1_50HLJ_2015-11-14_final.stac-item
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHR_2016-03-06_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-03-06_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JMR_2016-04-02_final.stac-item
2016-04-25 12:03:51	ga_s2am_ard_3-2-1_50KKA_2016-04-25_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HMK_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JPT_2016-05-09_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50JRT_2016-05-16_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JQT_2016-05-22_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JML_2017-05-27_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50KLA_2017-07-09_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50JKR_2017-09-07_final.stac-item
2017-09-17 12:04:38	ga_s2am_ard_3-2-1_50JKT_2017-09-17_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHP_2017-10-07_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50KKV_2017-10-07_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JGL_2017-10-17_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HMK_2017-12-03_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49KHP_2018-03-09_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_50KKV_2018-03-09_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HMH_2018-03-13_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMH_2018-03-30_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JKP_2018-04-25_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JNL_2018-04-29_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JNM_2018-04-29_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50JPN_2018-04-29_final.stac-item
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50JPN_2018-05-19_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLQ_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLR_2018-05-22_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JPN_2018-05-29_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKP_2018-06-24_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPT_2018-06-28_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-24_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JGL_2018-08-06_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50KLU_2018-08-10_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGN_2018-08-23_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JNP_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPQ_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JQQ_2018-08-27_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HNK_2018-09-06_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JPM_2018-09-06_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50KLU_2018-09-09_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPM_2018-09-26_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLP_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLS_2018-09-29_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-10-05_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JPS_2018-10-06_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLP_2018-10-09_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50JLR_2018-10-09_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KLU_2018-10-09_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_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_50JKS_2018-10-12_final.stac-item
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_50JNN_2018-10-16_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JLP_2018-10-19_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50KMU_2018-10-19_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JPS_2018-10-26_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HLH_2018-10-29_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMH_2018-10-29_final.stac-item
2018-11-08 11:57:01	ga_s2am_ard_3-2-1_50HMH_2018-11-08_final.stac-item
2018-12-21 12:03:47	ga_s2am_ard_3-2-1_50KLA_2018-12-21_final.stac-item
2018-12-28 11:54:41	ga_s2am_ard_3-2-1_50JPS_2018-12-28_final.stac-item
2019-01-03 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2019-01-03_final.stac-item
2019-01-03 12:14:36	ga_s2am_ard_3-2-1_49JGN_2019-01-03_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-04 11:44:39	ga_s2am_ard_3-2-1_50JRS_2019-01-04_final.stac-item
2019-01-04 11:44:58	ga_s2am_ard_3-2-1_50JQR_2019-01-04_final.stac-item
2019-01-04 11:46:53	ga_s2am_ard_3-2-1_50HMJ_2019-01-04_final.stac-item
2019-01-07 11:54:53	ga_s2am_ard_3-2-1_50JLS_2019-01-07_final.stac-item
2019-01-07 11:55:22	ga_s2am_ard_3-2-1_50JLQ_2019-01-07_final.stac-item
2019-10-14 11:56:07	ga_s2am_ard_3-2-1_50JNM_2019-10-14_final.stac-item
2021-01-03 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-01-03_final
2021-02-02 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2021-02-02_final.stac-item
2021-03-21 11:37:25	ga_s2am_ard_3-2-1_50HNG_2021-03-21_final
2021-04-16 11:57:14	ga_s2am_ard_3-2-1_50HMG_2021-04-16_final
2021-04-23 11:45:46	ga_s2am_ard_3-2-1_50JPN_2021-04-23_final.stac-item
2021-04-23 11:46:33	ga_s2am_ard_3-2-1_50HNK_2021-04-23_final.stac-item
2021-04-23 11:47:17	ga_s2am_ard_3-2-1_50HNG_2021-04-23_final
2021-04-29 12:03:35	ga_s2am_ard_3-2-1_50KMB_2021-04-29_final.stac-item
2021-04-29 12:04:22	ga_s2am_ard_3-2-1_50KLU_2021-04-29_final.stac-item
2021-04-29 12:05:12	ga_s2am_ard_3-2-1_49JGL_2021-04-29_final.stac-item
2021-04-30 11:37:18	ga_s2am_ard_3-2-1_50HPG_2021-04-30_final
2021-05-26 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-05-26_final.stac-item
2021-06-05 11:57:24	ga_s2am_ard_3-2-1_50HLG_2021-06-05_final
2021-06-15 11:54:34	ga_s2am_ard_3-2-1_50JPT_2021-06-15_final.stac-item
2021-06-15 11:54:48	ga_s2am_ard_3-2-1_50JPS_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 12:05:14	ga_s2am_ard_3-2-1_50JLR_2021-06-18_final.stac-item
2021-06-22 11:45:12	ga_s2am_ard_3-2-1_50JNR_2021-06-22_final.stac-item
2021-07-09 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2021-07-09_final.stac-item
2021-07-09 11:37:21	ga_s2am_ard_3-2-1_50HQG_2021-07-09_final
2021-08-01 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-08-01_final
2021-08-17 12:04:01	ga_s2am_ard_3-2-1_50KKA_2021-08-17_final.stac-item
2021-08-17 12:04:48	ga_s2am_ard_3-2-1_49JGN_2021-08-17_final.stac-item
2021-08-17 12:05:03	ga_s2am_ard_3-2-1_49JGM_2021-08-17_final.stac-item
2021-08-21 11:45:27	ga_s2am_ard_3-2-1_50JNQ_2021-08-21_final.stac-item
2022-06-20 11:57:03	ga_s2am_ard_3-2-1_50HMJ_2022-06-20_final.stac-item
2022-09-08 11:57:20	ga_s2am_ard_3-2-1_50HLH_2022-09-08_final.stac-item
2022-12-17 11:57:05	ga_s2am_ard_3-2-1_50HMH_2022-12-17_final.stac-item
2023-10-03 11:57:08	ga_s2am_ard_3-2-1_50HMH_2023-10-03_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

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