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
2016-01-09 12:16:04	ga_s2am_ard_3-2-1_49JGN_2016-01-09_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49JGL_2016-02-08_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KGQ_2016-06-07_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLJ_2016-06-11_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HNG_2016-06-18_final
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_50JKN_2016-07-14_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_50HPH_2016-07-15_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLN_2016-09-12_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPG_2016-11-02_final
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HNH_2016-11-05_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HMJ_2017-01-14_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HQK_2017-02-03_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHQ_2017-02-12_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JKN_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JLN_2017-05-30_final.stac-item
2017-08-01 12:13:37	ga_s2am_ard_3-2-1_49JGL_2017-08-01_final.stac-item
2017-11-23 11:56:04	ga_s2am_ard_3-2-1_50JML_2017-11-23_final.stac-item
2017-11-26 12:05:06	ga_s2am_ard_3-2-1_50JLN_2017-11-26_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50JLN_2017-12-23_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_50JNR_2017-12-30_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50JLP_2018-01-05_final.stac-item
2018-01-08 12:13:13	ga_s2am_ard_3-2-1_49JFM_2018-01-08_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50JMT_2018-04-02_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HPJ_2018-05-09_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50JPL_2018-05-16_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50JNM_2018-05-19_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKP_2018-07-14_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_50HPH_2018-09-23_final.stac-item
2018-11-21 12:05:19	ga_s2am_ard_3-2-1_50JKQ_2018-11-21_final.stac-item
2019-03-05 11:46:17	ga_s2am_ard_3-2-1_50JNL_2019-03-05_final.stac-item
2019-05-23 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-05-23_final.stac-item
2019-07-22 12:14:46	ga_s2am_ard_3-2-1_49JGN_2019-07-22_final.stac-item
2019-08-02 11:45:29	ga_s2am_ard_3-2-1_50JNQ_2019-08-02_final.stac-item
2019-09-27 12:04:32	ga_s2am_ard_3-2-1_49KGP_2019-09-27_final.stac-item
2019-09-27 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-09-27_final.stac-item
2019-11-10 11:46:36	ga_s2am_ard_3-2-1_50HPK_2019-11-10_final.stac-item
2019-11-13 11:56:28	ga_s2am_ard_3-2-1_50JLL_2019-11-13_final.stac-item
2019-11-27 11:37:06	ga_s2am_ard_3-2-1_50HPH_2019-11-27_final.stac-item
2019-12-20 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2019-12-20_final.stac-item
2020-01-19 11:46:13	ga_s2am_ard_3-2-1_50JPL_2020-01-19_final.stac-item
2020-05-04 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2020-05-04_final.stac-item
2020-05-04 12:04:35	ga_s2am_ard_3-2-1_49KGP_2020-05-04_final.stac-item
2020-05-14 12:06:00	ga_s2am_ard_3-2-1_50JKN_2020-05-14_final.stac-item
2020-07-20 11:55:51	ga_s2am_ard_3-2-1_50JKP_2020-07-20_final.stac-item
2020-07-20 11:56:23	ga_s2am_ard_3-2-1_50JNL_2020-07-20_final.stac-item
2020-07-23 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-07-23_final.stac-item
2020-07-30 11:55:59	ga_s2am_ard_3-2-1_50JMN_2020-07-30_final.stac-item
2020-10-05 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-05_final.stac-item
2020-10-12 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-10-12_final.stac-item
2020-10-25 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-10-25_final.stac-item
2021-02-19 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2021-02-19_final.stac-item
2021-04-29 12:05:49	ga_s2am_ard_3-2-1_50JLN_2021-04-29_final.stac-item
2021-05-09 12:04:53	ga_s2am_ard_3-2-1_50JLS_2021-05-09_final.stac-item
2021-06-15 11:55:42	ga_s2am_ard_3-2-1_50JLP_2021-06-15_final.stac-item
2021-09-13 11:56:19	ga_s2am_ard_3-2-1_50JNL_2021-09-13_final.stac-item
2022-01-11 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-11_final.stac-item
2022-01-31 11:55:06	ga_s2am_ard_3-2-1_50JNR_2022-01-31_final.stac-item
2022-04-07 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-04-07_final.stac-item
2022-04-08 11:47:11	ga_s2am_ard_3-2-1_50HMH_2022-04-08_final.stac-item
2022-04-14 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final.stac-item
2022-04-14 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2022-04-14_final.stac-item
2022-05-01 11:56:04	ga_s2am_ard_3-2-1_50JKN_2022-05-01_final.stac-item
2022-05-08 11:47:11	ga_s2am_ard_3-2-1_50HNH_2022-05-08_final.stac-item
2022-05-25 11:36:41	ga_s2am_ard_3-2-1_50HQK_2022-05-25_final.stac-item
2022-06-03 12:04:36	ga_s2am_ard_3-2-1_49KHP_2022-06-03_final.stac-item
2022-06-10 11:56:27	ga_s2am_ard_3-2-1_50JNL_2022-06-10_final.stac-item
2022-08-09 11:57:06	ga_s2am_ard_3-2-1_50HLJ_2022-08-09_final.stac-item
2022-08-22 12:04:12	ga_s2am_ard_3-2-1_49KHR_2022-08-22_final.stac-item
2022-09-11 12:04:53	ga_s2am_ard_3-2-1_49JHN_2022-09-11_final.stac-item
2022-09-11 12:06:02	ga_s2am_ard_3-2-1_50JLN_2022-09-11_final.stac-item
2022-10-15 11:46:42	ga_s2am_ard_3-2-1_50HNK_2022-10-15_final.stac-item
2022-10-21 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-10-21_final.stac-item
2022-10-25 11:46:11	ga_s2am_ard_3-2-1_50JNM_2022-10-25_final.stac-item
2022-11-01 11:36:30	ga_s2am_ard_3-2-1_50JPL_2022-11-01_final.stac-item
2022-11-13 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-11-13_final.stac-item
2022-11-13 12:14:01	ga_s2am_ard_3-2-1_49KGR_2022-11-13_final.stac-item
2022-12-14 11:47:06	ga_s2am_ard_3-2-1_50HNH_2022-12-14_final.stac-item
2022-12-17 11:55:56	ga_s2am_ard_3-2-1_50JLN_2022-12-17_final.stac-item
2022-12-17 11:56:03	ga_s2am_ard_3-2-1_50JNM_2022-12-17_final.stac-item
2023-01-03 11:46:25	ga_s2am_ard_3-2-1_50JML_2023-01-03_final.stac-item
2023-01-16 11:56:04	ga_s2am_ard_3-2-1_50JMM_2023-01-16_final.stac-item
2023-01-16 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-01-16_final.stac-item
2023-01-19 12:04:37	ga_s2am_ard_3-2-1_50JKT_2023-01-19_final.stac-item
2023-03-01 11:37:04	ga_s2am_ard_3-2-1_50HPH_2023-03-01_final
2023-06-25 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2023-06-25_final
2023-07-12 11:46:31	ga_s2am_ard_3-2-1_50JML_2023-07-12_final
2023-08-01 11:46:31	ga_s2am_ard_3-2-1_50JML_2023-08-01_final
2023-08-27 12:04:52	ga_s2am_ard_3-2-1_49JGN_2023-08-27_final
2023-09-16 12:04:32	ga_s2am_ard_3-2-1_49KHP_2023-09-16_final
2023-10-06 12:06:11	ga_s2am_ard_3-2-1_50JKM_2023-10-06_final
2023-10-09 12:15:10	ga_s2am_ard_3-2-1_49JGL_2023-10-09_final
2023-10-19 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-10-19_final
2023-11-18 12:13:56	ga_s2am_ard_3-2-1_49KGR_2023-11-18_final
2023-11-18 12:14:10	ga_s2am_ard_3-2-1_49KGQ_2023-11-18_final
2023-12-02 11:56:22	ga_s2am_ard_3-2-1_50HNK_2023-12-02_final
2023-12-15 12:06:00	ga_s2am_ard_3-2-1_50JLM_2023-12-15_final
2024-01-07 12:13:54	ga_s2am_ard_3-2-1_49KGR_2024-01-07_final
2024-01-25 11:36:32	ga_s2am_ard_3-2-1_50HPK_2024-01-25_final
2024-03-21 11:56:31	ga_s2am_ard_3-2-1_50HNK_2024-03-21_final
2024-04-30 11:55:49	ga_s2am_ard_3-2-1_50JKP_2024-04-30_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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