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
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JML_2016-01-03_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49KHS_2016-02-15_final
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KHR_2016-03-09_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHQ_2016-05-18_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGN_2016-11-01_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHM_2016-11-11_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JNL_2016-11-18_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HMJ_2017-01-24_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_50JKQ_2017-03-21_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JLM_2017-03-31_final.stac-item
2017-04-03 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-04-03_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HMK_2017-04-07_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JLP_2017-06-06_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JNM_2017-06-06_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_50JKT_2017-08-18_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50JMM_2017-11-13_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50HMJ_2017-12-30_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KGR_2018-03-19_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HMK_2018-03-30_final.stac-item
2018-08-13 12:02:49	ga_s2am_ard_3-2-1_49KGQ_2018-08-13_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHM_2018-08-23_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLM_2018-09-02_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50HMJ_2018-09-19_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50JNM_2018-10-16_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JML_2018-10-26_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JMN_2018-10-29_final.stac-item
2018-11-14 12:14:07	ga_s2am_ard_3-2-1_49KGQ_2018-11-14_final.stac-item
2018-11-28 11:56:32	ga_s2am_ard_3-2-1_50HLK_2018-11-28_final.stac-item
2018-12-11 12:04:40	ga_s2am_ard_3-2-1_50JMS_2018-12-11_final.stac-item
2019-01-11 11:36:37	ga_s2am_ard_3-2-1_50HQK_2019-01-11_final.stac-item
2019-01-11 11:36:39	ga_s2am_ard_3-2-1_50HPK_2019-01-11_final.stac-item
2019-02-06 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-02-06_final.stac-item
2019-03-18 11:57:03	ga_s2am_ard_3-2-1_50HMH_2019-03-18_final.stac-item
2019-03-25 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2019-03-25_final.stac-item
2019-05-17 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-05-17_final.stac-item
2019-05-24 11:46:11	ga_s2am_ard_3-2-1_50JNM_2019-05-24_final.stac-item
2019-07-16 11:55:47	ga_s2am_ard_3-2-1_50JLP_2019-07-16_final.stac-item
2019-07-16 11:55:51	ga_s2am_ard_3-2-1_50JKP_2019-07-16_final.stac-item
2019-08-05 11:55:17	ga_s2am_ard_3-2-1_50JLR_2019-08-05_final.stac-item
2019-08-15 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-08-15_final.stac-item
2019-10-11 11:46:11	ga_s2am_ard_3-2-1_50JNM_2019-10-11_final.stac-item
2019-10-24 11:56:07	ga_s2am_ard_3-2-1_50JNM_2019-10-24_final.stac-item
2019-11-03 11:55:56	ga_s2am_ard_3-2-1_50JMN_2019-11-03_final.stac-item
2019-11-16 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-11-16_final.stac-item
2019-12-26 12:05:03	ga_s2am_ard_3-2-1_50JLR_2019-12-26_final.stac-item
2020-01-19 11:45:05	ga_s2am_ard_3-2-1_50JNR_2020-01-19_final.stac-item
2020-01-22 11:55:58	ga_s2am_ard_3-2-1_50JNM_2020-01-22_final.stac-item
2020-03-09 11:46:04	ga_s2am_ard_3-2-1_50JNM_2020-03-09_final.stac-item
2020-03-09 11:46:09	ga_s2am_ard_3-2-1_50JMM_2020-03-09_final.stac-item
2020-03-09 11:46:22	ga_s2am_ard_3-2-1_50JML_2020-03-09_final.stac-item
2020-03-22 11:55:46	ga_s2am_ard_3-2-1_50JNN_2020-03-22_final.stac-item
2020-03-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2020-03-25_final.stac-item
2020-03-29 11:45:07	ga_s2am_ard_3-2-1_50JNR_2020-03-29_final.stac-item
2020-04-01 11:55:38	ga_s2am_ard_3-2-1_50JLP_2020-04-01_final.stac-item
2020-06-13 12:04:24	ga_s2am_ard_3-2-1_49KGQ_2020-06-13_final.stac-item
2020-06-30 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-06-30_final.stac-item
2020-08-26 11:46:14	ga_s2am_ard_3-2-1_50JNM_2020-08-26_final.stac-item
2020-10-18 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-10-18_final.stac-item
2020-11-07 11:56:12	ga_s2am_ard_3-2-1_50JMM_2020-11-07_final.stac-item
2020-11-27 11:56:05	ga_s2am_ard_3-2-1_50JNM_2020-11-27_final.stac-item
2020-12-04 11:46:07	ga_s2am_ard_3-2-1_50JNM_2020-12-04_final.stac-item
2020-12-07 11:55:04	ga_s2am_ard_3-2-1_50JNR_2020-12-07_final.stac-item
2021-01-09 12:04:40	ga_s2am_ard_3-2-1_50JLT_2021-01-09_final.stac-item
2021-02-12 11:47:08	ga_s2am_ard_3-2-1_50HMH_2021-02-12_final.stac-item
2021-04-13 11:45:48	ga_s2am_ard_3-2-1_50JNN_2021-04-13_final.stac-item
2021-04-16 11:55:58	ga_s2am_ard_3-2-1_50JNM_2021-04-16_final.stac-item
2021-04-19 12:04:37	ga_s2am_ard_3-2-1_50JKT_2021-04-19_final.stac-item
2021-06-05 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-06-05_final.stac-item
2021-07-25 11:57:15	ga_s2am_ard_3-2-1_50HMH_2021-07-25_final.stac-item
2021-10-13 11:55:47	ga_s2am_ard_3-2-1_50JLP_2021-10-13_final.stac-item
2021-10-16 12:04:48	ga_s2am_ard_3-2-1_50JKT_2021-10-16_final.stac-item
2021-10-26 12:04:59	ga_s2am_ard_3-2-1_50JLS_2021-10-26_final.stac-item
2021-10-26 12:05:17	ga_s2am_ard_3-2-1_50JKR_2021-10-26_final.stac-item
2021-12-15 12:04:39	ga_s2am_ard_3-2-1_50JLT_2021-12-15_final.stac-item
2021-12-16 11:36:34	ga_s2am_ard_3-2-1_50HQK_2021-12-16_final.stac-item
2022-01-18 11:46:13	ga_s2am_ard_3-2-1_50JMM_2022-01-18_final.stac-item
2022-01-18 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2022-01-18_final.stac-item
2022-01-28 11:46:13	ga_s2am_ard_3-2-1_50JMM_2022-01-28_final.stac-item
2022-02-13 12:04:35	ga_s2am_ard_3-2-1_50JMT_2022-02-13_final.stac-item
2022-02-16 12:14:22	ga_s2am_ard_3-2-1_49KHP_2022-02-16_final.stac-item
2022-04-18 11:46:12	ga_s2am_ard_3-2-1_50JNM_2022-04-18_final.stac-item
2022-08-19 11:55:25	ga_s2am_ard_3-2-1_50JLR_2022-08-19_final.stac-item
2022-11-07 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-11-07_final.stac-item
2023-03-14 11:46:37	ga_s2am_ard_3-2-1_50HMK_2023-03-14_final
2023-03-14 11:47:06	ga_s2am_ard_3-2-1_50HMH_2023-03-14_final
2023-04-19 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2023-04-19_final
2023-05-03 11:47:07	ga_s2am_ard_3-2-1_50HNH_2023-05-03_final
2023-08-27 12:04:45	ga_s2am_ard_3-2-1_50JLT_2023-08-27_final
2023-08-27 12:05:03	ga_s2am_ard_3-2-1_49JHM_2023-08-27_final
2023-09-07 11:37:32	ga_s2am_ard_3-2-1_50HNG_2023-09-07_final
2023-09-26 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2023-09-26_final
2023-09-27 11:36:40	ga_s2am_ard_3-2-1_50HPK_2023-09-27_final
2023-10-16 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2023-10-16_final
2023-10-16 12:05:36	ga_s2am_ard_3-2-1_50JLP_2023-10-16_final
2023-10-26 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2023-10-26_final
2023-12-12 11:55:48	ga_s2am_ard_3-2-1_50JMN_2023-12-12_final
2023-12-25 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-12-25_final
2024-01-11 11:54:35	ga_s2am_ard_3-2-1_50JMT_2024-01-11_final
2024-02-07 11:46:09	ga_s2am_ard_3-2-1_50JMM_2024-02-07_final
2024-03-14 12:03:44	ga_s2am_ard_3-2-1_49KHS_2024-03-14_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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