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
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HPG_2015-12-21_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KHP_2016-03-09_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50HMJ_2016-05-22_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HMG_2016-07-08_final.stac-item
2016-08-03 12:02:53	ga_s2am_ard_3-2-1_49KHP_2016-08-03_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JMM_2016-10-19_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHS_2016-11-11_final
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLH_2016-11-28_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMK_2016-12-05_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KHP_2016-12-11_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HQJ_2017-01-14_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HQK_2017-01-24_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50JNM_2017-01-24_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50JNM_2017-05-24_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKS_2017-06-19_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50JMN_2017-06-26_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JLR_2017-07-29_final.stac-item
2018-02-11 11:55:28	ga_s2am_ard_3-2-1_50HLK_2018-02-11_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-02-14_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2018-02-17_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HMK_2018-02-18_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HNJ_2018-02-18_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50HQJ_2018-03-20_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JMQ_2018-05-02_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HMK_2018-05-09_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JKP_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JLT_2018-05-22_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JLR_2018-07-01_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-07-04_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50JLP_2018-07-11_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-09-12_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMS_2018-09-29_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HLH_2018-11-05_final.stac-item
2018-11-08 11:56:13	ga_s2am_ard_3-2-1_50JNL_2018-11-08_final.stac-item
2018-11-15 11:47:09	ga_s2am_ard_3-2-1_50HLH_2018-11-15_final.stac-item
2018-11-21 12:05:05	ga_s2am_ard_3-2-1_50JKR_2018-11-21_final.stac-item
2019-01-20 12:05:22	ga_s2am_ard_3-2-1_50JKQ_2019-01-20_final.stac-item
2019-03-15 11:46:05	ga_s2am_ard_3-2-1_50JNM_2019-03-15_final.stac-item
2019-03-25 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2019-03-25_final.stac-item
2019-05-10 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-05-10_final.stac-item
2019-07-23 11:46:18	ga_s2am_ard_3-2-1_50JMM_2019-07-23_final.stac-item
2019-09-04 11:57:06	ga_s2am_ard_3-2-1_50HMH_2019-09-04_final.stac-item
2019-10-04 11:55:26	ga_s2am_ard_3-2-1_50JMQ_2019-10-04_final.stac-item
2019-11-13 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-11-13_final.stac-item
2020-01-09 11:46:35	ga_s2am_ard_3-2-1_50HMK_2020-01-09_final.stac-item
2020-01-09 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2020-01-09_final.stac-item
2020-02-14 12:05:16	ga_s2am_ard_3-2-1_50JLQ_2020-02-14_final.stac-item
2020-06-03 12:05:32	ga_s2am_ard_3-2-1_50JKQ_2020-06-03_final.stac-item
2020-09-04 12:14:50	ga_s2am_ard_3-2-1_49JFN_2020-09-04_final.stac-item
2020-09-21 12:05:02	ga_s2am_ard_3-2-1_49JHM_2020-09-21_final.stac-item
2020-10-01 12:05:03	ga_s2am_ard_3-2-1_50JKS_2020-10-01_final.stac-item
2020-10-18 11:54:50	ga_s2am_ard_3-2-1_50JLT_2020-10-18_final.stac-item
2020-10-28 11:55:58	ga_s2am_ard_3-2-1_50JMN_2020-10-28_final.stac-item
2020-11-07 11:56:34	ga_s2am_ard_3-2-1_50HNK_2020-11-07_final.stac-item
2021-02-18 12:04:56	ga_s2am_ard_3-2-1_50JKS_2021-02-18_final.stac-item
2021-02-22 11:47:24	ga_s2am_ard_3-2-1_50HMG_2021-02-22_final
2021-03-20 12:04:56	ga_s2am_ard_3-2-1_49JHM_2021-03-20_final.stac-item
2021-03-24 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2021-03-24_final.stac-item
2021-04-26 11:56:01	ga_s2am_ard_3-2-1_50JNM_2021-04-26_final.stac-item
2021-05-16 11:57:06	ga_s2am_ard_3-2-1_50HMH_2021-05-16_final.stac-item
2021-09-07 11:37:27	ga_s2am_ard_3-2-1_50HNG_2021-09-07_final
2021-10-03 11:55:14	ga_s2am_ard_3-2-1_50JMR_2021-10-03_final.stac-item
2021-11-05 12:05:01	ga_s2am_ard_3-2-1_50JKS_2021-11-05_final.stac-item
2022-03-09 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-03-09_final.stac-item
2022-04-21 11:55:54	ga_s2am_ard_3-2-1_50JNN_2022-04-21_final.stac-item
2022-05-04 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2022-05-04_final.stac-item
2022-05-31 11:55:46	ga_s2am_ard_3-2-1_50JMP_2022-05-31_final.stac-item
2022-06-07 11:47:03	ga_s2am_ard_3-2-1_50HMJ_2022-06-07_final.stac-item
2022-07-04 11:36:47	ga_s2am_ard_3-2-1_50HQK_2022-07-04_final.stac-item
2022-07-23 12:05:08	ga_s2am_ard_3-2-1_49JHM_2022-07-23_final.stac-item
2022-07-30 11:55:48	ga_s2am_ard_3-2-1_50JMP_2022-07-30_final.stac-item
2022-09-01 12:04:55	ga_s2am_ard_3-2-1_50JKT_2022-09-01_final.stac-item
2022-09-28 11:56:44	ga_s2am_ard_3-2-1_50HMK_2022-09-28_final.stac-item
2022-10-01 12:04:44	ga_s2am_ard_3-2-1_50JMT_2022-10-01_final.stac-item
2022-10-21 12:04:55	ga_s2am_ard_3-2-1_50JKS_2022-10-21_final.stac-item
2022-10-21 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-10-21_final.stac-item
2022-11-07 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-11-07_final.stac-item
2022-12-14 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-12-14_final.stac-item
2022-12-20 12:04:52	ga_s2am_ard_3-2-1_50JLS_2022-12-20_final.stac-item
2022-12-21 11:36:32	ga_s2am_ard_3-2-1_50HQK_2022-12-21_final.stac-item
2023-01-19 12:03:39	ga_s2am_ard_3-2-1_49KHS_2023-01-19_final
2023-01-26 11:54:55	ga_s2am_ard_3-2-1_50JLS_2023-01-26_final.stac-item
2023-01-26 11:55:43	ga_s2am_ard_3-2-1_50JKP_2023-01-26_final.stac-item
2023-01-29 12:03:42	ga_s2am_ard_3-2-1_49KHS_2023-01-29_final
2023-02-08 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2023-02-08_final
2023-03-07 11:54:40	ga_s2am_ard_3-2-1_50JLT_2023-03-07_final
2023-04-23 11:47:09	ga_s2am_ard_3-2-1_50HMH_2023-04-23_final
2023-05-09 12:04:57	ga_s2am_ard_3-2-1_50JKS_2023-05-09_final
2023-05-26 11:54:48	ga_s2am_ard_3-2-1_50JLT_2023-05-26_final
2023-07-15 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-07-15_final
2023-10-20 11:46:08	ga_s2am_ard_3-2-1_50JNM_2023-10-20_final
2023-10-23 11:56:36	ga_s2am_ard_3-2-1_50HMK_2023-10-23_final
2023-12-06 11:36:27	ga_s2am_ard_3-2-1_50HQK_2023-12-06_final
2023-12-12 11:56:32	ga_s2am_ard_3-2-1_50HMK_2023-12-12_final
2023-12-25 12:04:54	ga_s2am_ard_3-2-1_50JKS_2023-12-25_final
2024-01-21 11:56:29	ga_s2am_ard_3-2-1_50HMK_2024-01-21_final
2024-03-28 11:46:13	ga_s2am_ard_3-2-1_50JMM_2024-03-28_final
2024-03-28 11:47:10	ga_s2am_ard_3-2-1_50HMH_2024-03-28_final
2024-04-07 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2024-04-07_final
2024-04-17 11:46:16	ga_s2am_ard_3-2-1_50JMM_2024-04-17_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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