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
2015-10-22 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2015-10-22_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KGP_2015-11-30_final.stac-item
2016-01-23 11:56:39	ga_s2am_ard_3-2-1_50HNK_2016-01-23_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGP_2016-03-09_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_49KGR_2016-03-09_final.stac-item
2016-04-25 12:03:51	ga_s2am_ard_3-2-1_49KHR_2016-04-25_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JLS_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JNN_2016-10-29_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPJ_2016-11-02_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JMN_2016-12-28_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KHR_2017-03-14_final.stac-item
2017-03-18 11:51:11	ga_s2am_ard_3-2-1_50JLT_2017-03-18_final.stac-item
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_50HPJ_2017-05-31_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_50HQJ_2017-06-20_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50HMK_2017-07-16_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JKR_2017-10-07_final.stac-item
2017-10-20 12:13:21	ga_s2am_ard_3-2-1_49KGQ_2017-10-20_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JNL_2018-05-02_final.stac-item
2018-05-28 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-28_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HQH_2018-07-25_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLK_2018-07-31_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HMJ_2018-07-31_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JNM_2018-08-20_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-09-02_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHR_2018-09-05_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_50JKR_2018-10-02_final.stac-item
2018-12-05 11:47:01	ga_s2am_ard_3-2-1_50HMH_2018-12-05_final.stac-item
2019-01-07 11:56:06	ga_s2am_ard_3-2-1_50JLM_2019-01-07_final.stac-item
2019-01-20 12:05:11	ga_s2am_ard_3-2-1_49JGL_2019-01-20_final.stac-item
2019-01-23 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-01-23_final.stac-item
2019-02-23 11:47:02	ga_s2am_ard_3-2-1_50HNH_2019-02-23_final.stac-item
2019-03-28 11:56:10	ga_s2am_ard_3-2-1_50JLM_2019-03-28_final.stac-item
2019-05-04 11:47:14	ga_s2am_ard_3-2-1_50HMH_2019-05-04_final.stac-item
2019-05-17 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-05-17_final.stac-item
2019-05-20 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2019-05-20_final.stac-item
2019-09-01 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2019-09-01_final.stac-item
2019-09-01 11:47:07	ga_s2am_ard_3-2-1_50HNH_2019-09-01_final.stac-item
2019-09-04 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2019-09-04_final.stac-item
2019-10-17 12:05:55	ga_s2am_ard_3-2-1_50JLN_2019-10-17_final.stac-item
2019-10-18 11:37:06	ga_s2am_ard_3-2-1_50HQH_2019-10-18_final.stac-item
2019-11-10 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2019-11-10_final.stac-item
2020-01-05 12:05:59	ga_s2am_ard_3-2-1_50JLM_2020-01-05_final.stac-item
2020-02-24 12:05:36	ga_s2am_ard_3-2-1_50JKP_2020-02-24_final.stac-item
2020-03-05 12:04:27	ga_s2am_ard_3-2-1_49KGP_2020-03-05_final.stac-item
2020-03-05 12:04:56	ga_s2am_ard_3-2-1_49JGM_2020-03-05_final.stac-item
2020-03-06 11:36:59	ga_s2am_ard_3-2-1_50HQH_2020-03-06_final.stac-item
2020-04-28 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2020-04-28_final.stac-item
2020-05-08 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2020-05-08_final.stac-item
2020-05-31 11:55:52	ga_s2am_ard_3-2-1_50JKP_2020-05-31_final.stac-item
2020-07-10 11:55:46	ga_s2am_ard_3-2-1_50JLP_2020-07-10_final.stac-item
2020-07-10 11:55:57	ga_s2am_ard_3-2-1_50JMN_2020-07-10_final.stac-item
2020-10-18 11:56:13	ga_s2am_ard_3-2-1_50JMM_2020-10-18_final.stac-item
2020-12-03 12:13:57	ga_s2am_ard_3-2-1_49KGR_2020-12-03_final.stac-item
2021-01-02 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-01-02_final.stac-item
2021-01-23 11:46:38	ga_s2am_ard_3-2-1_50HNK_2021-01-23_final.stac-item
2021-03-27 11:54:53	ga_s2am_ard_3-2-1_50JMS_2021-03-27_final.stac-item
2021-05-19 12:04:14	ga_s2am_ard_3-2-1_49KHQ_2021-05-19_final.stac-item
2021-05-26 11:56:30	ga_s2am_ard_3-2-1_50HNK_2021-05-26_final.stac-item
2021-06-18 12:04:54	ga_s2am_ard_3-2-1_50JLS_2021-06-18_final.stac-item
2021-07-05 11:55:52	ga_s2am_ard_3-2-1_50JNN_2021-07-05_final.stac-item
2021-08-21 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-08-21_final
2021-10-03 11:55:17	ga_s2am_ard_3-2-1_50JLR_2021-10-03_final.stac-item
2021-10-03 11:55:43	ga_s2am_ard_3-2-1_50JMP_2021-10-03_final.stac-item
2021-11-29 11:47:06	ga_s2am_ard_3-2-1_50HNH_2021-11-29_final.stac-item
2021-12-19 11:45:54	ga_s2am_ard_3-2-1_50JNN_2021-12-19_final.stac-item
2022-01-14 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-01-14_final.stac-item
2022-02-07 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2022-02-07_final.stac-item
2022-02-23 12:05:43	ga_s2am_ard_3-2-1_50JKP_2022-02-23_final.stac-item
2022-03-16 11:37:10	ga_s2am_ard_3-2-1_50HPH_2022-03-16_final.stac-item
2022-03-18 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-03-18_final.stac-item
2022-05-14 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-05-14_final.stac-item
2022-06-04 11:36:56	ga_s2am_ard_3-2-1_50HQJ_2022-06-04_final.stac-item
2022-09-02 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-09-02_final.stac-item
2022-12-07 11:56:30	ga_s2am_ard_3-2-1_50HNK_2022-12-07_final.stac-item
2022-12-14 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2022-12-14_final.stac-item
2023-02-21 12:14:24	ga_s2am_ard_3-2-1_49KGP_2023-02-21_nrt.stac-item
2023-02-21 12:14:24	ga_s2am_ard_3-2-1_49KGP_2023-02-21_final
2023-02-28 12:04:32	ga_s2am_ard_3-2-1_49KGP_2023-02-28_final
2023-03-03 12:14:24	ga_s2am_ard_3-2-1_49KGP_2023-03-03_final
2023-04-26 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-26_final
2023-05-12 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-05-12_final
2023-05-13 11:47:02	ga_s2am_ard_3-2-1_50HPH_2023-05-13_final
2023-05-19 12:05:43	ga_s2am_ard_3-2-1_50JKP_2023-05-19_final
2023-06-02 11:46:45	ga_s2am_ard_3-2-1_50HMK_2023-06-02_final
2023-07-01 12:14:35	ga_s2am_ard_3-2-1_49KFP_2023-07-01_nrt
2023-07-02 11:47:22	ga_s2am_ard_3-2-1_50HPG_2023-07-02_final
2023-07-08 12:05:06	ga_s2am_ard_3-2-1_49JGM_2023-07-08_final
2023-08-01 11:47:22	ga_s2am_ard_3-2-1_50HPG_2023-08-01_final
2023-09-06 12:04:51	ga_s2am_ard_3-2-1_49JGN_2023-09-06_final
2023-09-07 11:37:08	ga_s2am_ard_3-2-1_50HQH_2023-09-07_final
2023-10-06 12:06:11	ga_s2am_ard_3-2-1_50JKM_2023-10-06_final
2023-10-23 11:56:08	ga_s2am_ard_3-2-1_50JMM_2023-10-23_final
2023-11-08 12:13:58	ga_s2am_ard_3-2-1_49KGR_2023-11-08_final
2023-12-15 12:04:27	ga_s2am_ard_3-2-1_49KGP_2023-12-15_final
2024-01-25 11:36:32	ga_s2am_ard_3-2-1_50HPK_2024-01-25_final
2024-02-10 11:57:16	ga_s2am_ard_3-2-1_50HMG_2024-02-10_final
2024-02-20 11:55:54	ga_s2am_ard_3-2-1_50JLN_2024-02-20_final
2024-03-14 12:04:31	ga_s2am_ard_3-2-1_49KGP_2024-03-14_final
2024-03-18 11:46:23	ga_s2am_ard_3-2-1_50JNL_2024-03-18_final
2024-04-03 12:04:55	ga_s2am_ard_3-2-1_50JKS_2024-04-03_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

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