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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGK_2016-01-16_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JLN_2016-09-19_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50JML_2016-09-19_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HPH_2017-01-14_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_49JGM_2017-01-20_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49KHR_2017-03-11_final.stac-item
2017-04-10 12:03:46	ga_s2am_ard_3-2-1_49KHR_2017-04-10_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JML_2017-05-04_final.stac-item
2017-05-11 11:35:01	ga_s2am_ard_3-2-1_50HPK_2017-05-11_final.stac-item
2017-05-20 12:04:45	ga_s2am_ard_3-2-1_49JGM_2017-05-20_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49JGL_2017-06-22_final.stac-item
2017-06-29 12:04:40	ga_s2am_ard_3-2-1_49JGM_2017-06-29_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HNK_2017-07-03_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JKP_2017-09-27_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JLQ_2017-10-07_final.stac-item
2017-12-06 12:04:36	ga_s2am_ard_3-2-1_49JGM_2017-12-06_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGJ_2018-03-06_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HLK_2018-07-21_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-24_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JLN_2018-07-24_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HPK_2018-07-28_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_50HPJ_2018-08-14_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HPK_2018-09-06_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JKP_2018-09-19_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HNH_2018-11-05_final.stac-item
2018-12-12 11:36:29	ga_s2am_ard_3-2-1_50HPK_2018-12-12_final.stac-item
2019-03-08 11:56:16	ga_s2am_ard_3-2-1_50JML_2019-03-08_final.stac-item
2019-03-31 12:05:55	ga_s2am_ard_3-2-1_50JKN_2019-03-31_final.stac-item
2019-04-17 11:56:02	ga_s2am_ard_3-2-1_50JKN_2019-04-17_final.stac-item
2019-06-06 11:55:58	ga_s2am_ard_3-2-1_50JLN_2019-06-06_final.stac-item
2019-06-13 11:46:29	ga_s2am_ard_3-2-1_50JML_2019-06-13_final.stac-item
2019-07-03 11:46:39	ga_s2am_ard_3-2-1_50HPK_2019-07-03_final.stac-item
2019-07-09 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-09_final.stac-item
2019-08-01 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-08-01_final.stac-item
2019-08-05 11:56:34	ga_s2am_ard_3-2-1_50HNK_2019-08-05_final.stac-item
2019-08-22 11:46:28	ga_s2am_ard_3-2-1_50JML_2019-08-22_final.stac-item
2019-10-30 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-10-30_final.stac-item
2019-11-20 11:46:35	ga_s2am_ard_3-2-1_50HPK_2019-11-20_final.stac-item
2020-01-09 11:46:28	ga_s2am_ard_3-2-1_50HPK_2020-01-09_final.stac-item
2020-04-25 11:37:08	ga_s2am_ard_3-2-1_50HPH_2020-04-25_final.stac-item
2020-05-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-05-25_final.stac-item
2020-06-30 11:56:41	ga_s2am_ard_3-2-1_50HMK_2020-06-30_final.stac-item
2020-07-07 11:46:30	ga_s2am_ard_3-2-1_50JML_2020-07-07_final.stac-item
2020-07-14 11:37:11	ga_s2am_ard_3-2-1_50HPH_2020-07-14_final.stac-item
2020-08-26 11:47:12	ga_s2am_ard_3-2-1_50HNH_2020-08-26_final.stac-item
2020-09-25 11:46:48	ga_s2am_ard_3-2-1_50HQJ_2020-09-25_final.stac-item
2020-10-05 11:46:49	ga_s2am_ard_3-2-1_50HQJ_2020-10-05_final.stac-item
2020-11-30 12:03:59	ga_s2am_ard_3-2-1_49KHR_2020-11-30_final.stac-item
2020-12-30 12:05:55	ga_s2am_ard_3-2-1_50JKN_2020-12-30_final.stac-item
2021-01-19 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2021-01-19_final.stac-item
2021-04-10 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-04-10_final.stac-item
2021-04-23 11:46:33	ga_s2am_ard_3-2-1_50HNK_2021-04-23_final.stac-item
2021-05-13 11:46:22	ga_s2am_ard_3-2-1_50JNL_2021-05-13_final.stac-item
2021-07-05 11:56:43	ga_s2am_ard_3-2-1_50HLK_2021-07-05_final.stac-item
2021-07-25 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2021-07-25_final.stac-item
2021-08-17 12:05:58	ga_s2am_ard_3-2-1_50JKN_2021-08-17_final.stac-item
2021-09-10 11:47:02	ga_s2am_ard_3-2-1_50HPH_2021-09-10_final.stac-item
2021-09-26 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-09-26_final.stac-item
2021-09-30 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2021-09-30_final.stac-item
2021-12-09 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2021-12-09_final.stac-item
2022-02-04 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2022-02-04_final.stac-item
2022-02-13 12:06:09	ga_s2am_ard_3-2-1_50JKM_2022-02-13_final.stac-item
2022-03-08 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-03-08_final.stac-item
2022-03-18 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-03-18_final.stac-item
2022-04-07 12:14:28	ga_s2am_ard_3-2-1_49KGP_2022-04-07_final.stac-item
2022-04-11 11:55:44	ga_s2am_ard_3-2-1_50JLP_2022-04-11_final.stac-item
2022-05-21 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-05-21_final.stac-item
2022-06-13 12:04:24	ga_s2am_ard_3-2-1_49KHQ_2022-06-13_final.stac-item
2022-07-13 12:04:55	ga_s2am_ard_3-2-1_50JKT_2022-07-13_final.stac-item
2022-09-08 11:56:19	ga_s2am_ard_3-2-1_50JMM_2022-09-08_final.stac-item
2022-09-12 11:37:02	ga_s2am_ard_3-2-1_50HPJ_2022-09-12_final.stac-item
2022-09-15 11:46:47	ga_s2am_ard_3-2-1_50HNK_2022-09-15_final.stac-item
2022-10-21 12:05:57	ga_s2am_ard_3-2-1_50JKN_2022-10-21_final.stac-item
2022-10-31 12:04:46	ga_s2am_ard_3-2-1_49JHN_2022-10-31_final.stac-item
2023-01-09 12:04:44	ga_s2am_ard_3-2-1_49JGN_2023-01-09_final.stac-item
2023-02-22 11:47:14	ga_s2am_ard_3-2-1_50HPG_2023-02-22_final
2023-03-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-03-17_final
2023-04-16 11:55:53	ga_s2am_ard_3-2-1_50JMN_2023-04-16_final
2023-05-19 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2023-05-19_final
2023-06-09 11:37:21	ga_s2am_ard_3-2-1_50HQG_2023-06-09_final
2023-06-18 12:06:08	ga_s2am_ard_3-2-1_50JLM_2023-06-18_final
2023-06-21 12:15:14	ga_s2am_ard_3-2-1_49JGL_2023-06-21_final
2023-07-05 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-07-05_final
2023-07-21 12:15:04	ga_s2am_ard_3-2-1_49JFM_2023-07-21_final
2023-07-31 12:15:05	ga_s2am_ard_3-2-1_49JFM_2023-07-31_final
2023-08-01 11:46:39	ga_s2am_ard_3-2-1_50HPK_2023-08-01_final
2023-08-21 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-21_final
2023-09-07 11:36:43	ga_s2am_ard_3-2-1_50HPK_2023-09-07_final
2023-09-09 12:14:32	ga_s2am_ard_3-2-1_49KGP_2023-09-09_final
2023-09-23 11:56:09	ga_s2am_ard_3-2-1_50JMM_2023-09-23_final
2023-10-10 11:46:47	ga_s2am_ard_3-2-1_50HPJ_2023-10-10_final
2023-10-13 11:55:48	ga_s2am_ard_3-2-1_50JLN_2023-10-13_final
2023-11-02 11:55:50	ga_s2am_ard_3-2-1_50JKN_2023-11-02_final
2023-11-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-11-22_final
2023-11-25 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-11-25_final
2023-11-29 11:46:29	ga_s2am_ard_3-2-1_50HNK_2023-11-29_final
2023-12-05 12:05:37	ga_s2am_ard_3-2-1_49JGJ_2023-12-05_final
2023-12-22 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2023-12-22_final
2024-03-14 12:05:41	ga_s2am_ard_3-2-1_50JKP_2024-03-14_final
2024-04-14 11:37:19	ga_s2am_ard_3-2-1_50HQG_2024-04-14_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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