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
2016-06-17 12:13:46	ga_s2am_ard_3-2-1_49KHR_2016-06-17_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JMR_2016-07-21_final.stac-item
2016-08-06 12:13:25	ga_s2am_ard_3-2-1_49KGP_2016-08-06_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49KHQ_2016-08-23_final.stac-item
2016-10-15 12:13:39	ga_s2am_ard_3-2-1_49KHR_2016-10-15_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGM_2016-10-22_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGL_2016-11-21_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49KHR_2016-12-04_final.stac-item
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49KHP_2017-02-12_final.stac-item
2017-02-22 12:15:07	ga_s2am_ard_3-2-1_49JGL_2017-02-22_final.stac-item
2017-03-11 12:02:41	ga_s2am_ard_3-2-1_49JGM_2017-03-11_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_49JGM_2017-04-10_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49JGM_2017-04-20_final.stac-item
2017-07-19 12:04:43	ga_s2am_ard_3-2-1_50JKS_2017-07-19_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_49KGP_2017-07-29_final.stac-item
2017-08-08 12:04:43	ga_s2am_ard_3-2-1_49JGK_2017-08-08_final.stac-item
2017-10-30 12:14:41	ga_s2am_ard_3-2-1_49JGL_2017-10-30_final.stac-item
2017-11-09 12:13:20	ga_s2am_ard_3-2-1_49JGM_2017-11-09_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_50JPL_2017-12-17_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KGR_2018-01-28_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50JKN_2018-02-24_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_49KHR_2018-03-26_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JKN_2018-07-01_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKQ_2018-07-04_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JKN_2018-09-19_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50HLH_2018-10-09_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_49JGK_2018-10-22_final.stac-item
2018-11-18 11:56:19	ga_s2am_ard_3-2-1_50JLL_2018-11-18_final.stac-item
2018-11-21 12:04:24	ga_s2am_ard_3-2-1_49KGP_2018-11-21_final.stac-item
2018-12-02 11:36:54	ga_s2am_ard_3-2-1_50HQH_2018-12-02_final.stac-item
2018-12-21 12:05:32	ga_s2am_ard_3-2-1_50JKP_2018-12-21_final.stac-item
2019-02-19 12:05:37	ga_s2am_ard_3-2-1_50JKP_2019-02-19_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_49KHR_2019-03-04_final.stac-item
2019-05-07 11:56:03	ga_s2am_ard_3-2-1_50JKN_2019-05-07_final.stac-item
2019-07-30 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-07-30_final.stac-item
2019-09-04 11:55:42	ga_s2am_ard_3-2-1_50JLP_2019-09-04_final.stac-item
2020-02-04 12:06:00	ga_s2am_ard_3-2-1_50JKM_2020-02-04_final.stac-item
2020-02-18 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2020-02-18_final.stac-item
2020-03-05 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-03-05_final.stac-item
2020-04-07 12:13:55	ga_s2am_ard_3-2-1_49KGR_2020-04-07_final.stac-item
2020-05-01 11:56:43	ga_s2am_ard_3-2-1_50HLK_2020-05-01_final.stac-item
2020-05-11 11:56:34	ga_s2am_ard_3-2-1_50HNK_2020-05-11_final.stac-item
2020-05-21 11:55:55	ga_s2am_ard_3-2-1_50JNN_2020-05-21_final.stac-item
2020-06-03 12:05:44	ga_s2am_ard_3-2-1_50JLP_2020-06-03_final.stac-item
2020-06-10 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-06-10_final.stac-item
2020-06-23 12:05:32	ga_s2am_ard_3-2-1_50JKQ_2020-06-23_final.stac-item
2020-06-27 11:46:28	ga_s2am_ard_3-2-1_50JNL_2020-06-27_final.stac-item
2020-07-13 12:04:03	ga_s2am_ard_3-2-1_49KHR_2020-07-13_final.stac-item
2020-08-05 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-08-05_final.stac-item
2020-10-04 12:14:33	ga_s2am_ard_3-2-1_49KGP_2020-10-04_final.stac-item
2020-12-07 11:55:57	ga_s2am_ard_3-2-1_50JKN_2020-12-07_final.stac-item
2020-12-14 11:46:59	ga_s2am_ard_3-2-1_50HPH_2020-12-14_final.stac-item
2021-01-03 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-03_final.stac-item
2021-01-06 11:55:57	ga_s2am_ard_3-2-1_50JLN_2021-01-06_final.stac-item
2021-01-19 12:05:52	ga_s2am_ard_3-2-1_50JLN_2021-01-19_final.stac-item
2021-01-30 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-01-30_final
2021-03-04 11:45:54	ga_s2am_ard_3-2-1_50JNN_2021-03-04_final.stac-item
2021-04-09 12:05:33	ga_s2am_ard_3-2-1_50JLP_2021-04-09_final.stac-item
2021-05-09 12:04:53	ga_s2am_ard_3-2-1_50JLS_2021-05-09_final.stac-item
2021-06-11 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-06-11_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-09-03 11:56:37	ga_s2am_ard_3-2-1_50HMK_2021-09-03_final.stac-item
2021-09-30 11:46:38	ga_s2am_ard_3-2-1_50HPK_2021-09-30_final.stac-item
2022-01-24 12:05:41	ga_s2am_ard_3-2-1_50JKP_2022-01-24_final.stac-item
2022-02-03 12:05:00	ga_s2am_ard_3-2-1_49JGM_2022-02-03_final.stac-item
2022-02-20 11:56:01	ga_s2am_ard_3-2-1_50JKN_2022-02-20_final.stac-item
2022-04-24 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-04-24_final.stac-item
2022-06-06 12:14:49	ga_s2am_ard_3-2-1_49JGN_2022-06-06_final.stac-item
2022-08-12 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-08-12_final.stac-item
2022-09-08 11:56:15	ga_s2am_ard_3-2-1_50JNM_2022-09-08_final.stac-item
2022-10-05 11:46:01	ga_s2am_ard_3-2-1_50JNN_2022-10-05_final.stac-item
2022-10-24 12:15:02	ga_s2am_ard_3-2-1_49JFM_2022-10-24_final.stac-item
2023-01-16 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-01-16_final.stac-item
2023-04-02 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2023-04-02_final
2023-04-09 12:05:38	ga_s2am_ard_3-2-1_50JLP_2023-04-09_final
2023-04-10 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2023-04-10_final
2023-04-12 12:13:55	ga_s2am_ard_3-2-1_49KHR_2023-04-12_final
2023-04-29 12:04:31	ga_s2am_ard_3-2-1_49KGP_2023-04-29_final
2023-07-01 12:15:15	ga_s2am_ard_3-2-1_49JGL_2023-07-01_final
2023-07-05 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2023-07-05_final
2023-07-12 11:46:46	ga_s2am_ard_3-2-1_50HMK_2023-07-12_final
2023-07-18 12:04:58	ga_s2am_ard_3-2-1_50JLS_2023-07-18_final
2023-07-28 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2023-07-28_final
2023-08-28 11:37:12	ga_s2am_ard_3-2-1_50HPH_2023-08-28_final
2023-08-31 11:47:07	ga_s2am_ard_3-2-1_50HPH_2023-08-31_final
2023-10-07 11:37:07	ga_s2am_ard_3-2-1_50HPH_2023-10-07_final
2023-10-23 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2023-10-23_final
2023-11-05 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-11-05_final
2023-12-09 11:47:19	ga_s2am_ard_3-2-1_50HMG_2023-12-09_final
2023-12-15 12:04:56	ga_s2am_ard_3-2-1_49JGM_2023-12-15_final
2024-01-17 12:15:02	ga_s2am_ard_3-2-1_49JGL_2024-01-17_final
2024-01-31 11:56:25	ga_s2am_ard_3-2-1_50HNK_2024-01-31_final
2024-02-06 12:15:06	ga_s2am_ard_3-2-1_49JGL_2024-02-06_final
2024-02-07 11:46:04	ga_s2am_ard_3-2-1_50JNM_2024-02-07_final
2024-02-17 11:47:04	ga_s2am_ard_3-2-1_50HNH_2024-02-17_final
2024-03-11 11:56:04	ga_s2am_ard_3-2-1_50JNM_2024-03-11_final
2024-03-14 12:05:51	ga_s2am_ard_3-2-1_50JLN_2024-03-14_final
2024-04-17 11:47:27	ga_s2am_ard_3-2-1_50HMG_2024-04-17_final
2024-04-20 11:57:23	ga_s2am_ard_3-2-1_50HMG_2024-04-20_final
2024-06-02 12:06:08	ga_s2am_ard_3-2-1_50JLM_2024-06-02_nrt

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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