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
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50KKA_2016-04-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49JGN_2016-05-15_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50JMN_2016-12-08_final.stac-item
2017-01-13 12:14:33	ga_s2am_ard_3-2-1_49JGM_2017-01-13_final.stac-item
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50JMS_2017-02-16_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_49JGM_2017-02-22_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50KQC_2017-07-16_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50JKP_2017-07-29_final.stac-item
2017-08-18 12:02:50	ga_s2am_ard_3-2-1_49JHN_2017-08-18_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JLQ_2017-08-25_final.stac-item
2017-09-30 12:13:43	ga_s2am_ard_3-2-1_49JGM_2017-09-30_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_49JGN_2017-10-10_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JLL_2017-12-03_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGM_2018-03-06_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_49JGL_2018-05-15_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JLM_2018-07-21_final.stac-item
2018-10-02 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-10-02_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_50HPJ_2018-10-03_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50KLU_2018-10-12_final.stac-item
2018-11-08 11:57:05	ga_s2am_ard_3-2-1_50HLH_2018-11-08_final.stac-item
2018-11-18 11:56:24	ga_s2am_ard_3-2-1_50HNK_2018-11-18_final.stac-item
2018-12-22 11:36:44	ga_s2am_ard_3-2-1_50HPJ_2018-12-22_final.stac-item
2019-01-17 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-01-17_final.stac-item
2019-03-05 11:46:38	ga_s2am_ard_3-2-1_50HQJ_2019-03-05_final.stac-item
2019-03-25 11:46:18	ga_s2am_ard_3-2-1_50JPL_2019-03-25_final.stac-item
2019-04-14 11:46:55	ga_s2am_ard_3-2-1_50HQH_2019-04-14_final.stac-item
2019-05-01 11:36:37	ga_s2am_ard_3-2-1_50HQK_2019-05-01_final.stac-item
2019-06-16 11:56:25	ga_s2am_ard_3-2-1_50JML_2019-06-16_final.stac-item
2019-08-08 12:05:05	ga_s2am_ard_3-2-1_49JGM_2019-08-08_final.stac-item
2019-08-19 11:36:40	ga_s2am_ard_3-2-1_50HPK_2019-08-19_final.stac-item
2019-08-28 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-08-28_final.stac-item
2019-08-31 12:13:55	ga_s2am_ard_3-2-1_50KKA_2019-08-31_final.stac-item
2019-10-18 11:36:23	ga_s2am_ard_3-2-1_50JQL_2019-10-18_final.stac-item
2019-11-16 12:03:46	ga_s2am_ard_3-2-1_50KKB_2019-11-16_final.stac-item
2019-12-30 11:43:16	ga_s2am_ard_3-2-1_50KQC_2019-12-30_final.stac-item
2020-01-05 12:05:09	ga_s2am_ard_3-2-1_49JGL_2020-01-05_final.stac-item
2020-02-24 12:05:06	ga_s2am_ard_3-2-1_50JKR_2020-02-24_final.stac-item
2020-03-05 12:04:00	ga_s2am_ard_3-2-1_50KKA_2020-03-05_final.stac-item
2020-03-15 12:03:16	ga_s2am_ard_3-2-1_50KNC_2020-03-15_final.stac-item
2020-03-15 12:04:53	ga_s2am_ard_3-2-1_49JHM_2020-03-15_final.stac-item
2020-04-21 11:53:43	ga_s2am_ard_3-2-1_50KMB_2020-04-21_final.stac-item
2020-04-24 12:03:28	ga_s2am_ard_3-2-1_50KLC_2020-04-24_final.stac-item
2020-04-28 11:47:05	ga_s2am_ard_3-2-1_50HPH_2020-04-28_final.stac-item
2020-05-18 11:47:15	ga_s2am_ard_3-2-1_50HMH_2020-05-18_final.stac-item
2020-07-06 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-07-06_final.stac-item
2020-07-17 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2020-07-17_final.stac-item
2020-07-23 12:04:19	ga_s2am_ard_3-2-1_50KKV_2020-07-23_final.stac-item
2020-11-04 11:46:31	ga_s2am_ard_3-2-1_50JML_2020-11-04_final.stac-item
2020-12-10 12:05:11	ga_s2am_ard_3-2-1_49JGL_2020-12-10_final.stac-item
2021-01-06 11:54:05	ga_s2am_ard_3-2-1_50KPV_2021-01-06_final.stac-item
2021-02-08 12:05:07	ga_s2am_ard_3-2-1_50JLR_2021-02-08_final.stac-item
2021-02-25 11:52:37	ga_s2am_ard_3-2-1_50KPF_2021-02-25_final
2021-03-20 12:03:37	ga_s2am_ard_3-2-1_50KMB_2021-03-20_final.stac-item
2021-05-03 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2021-05-03_final.stac-item
2021-05-06 11:56:16	ga_s2am_ard_3-2-1_50JNL_2021-05-06_final.stac-item
2021-05-09 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-05-09_final.stac-item
2021-05-12 12:13:58	ga_s2am_ard_3-2-1_49KGR_2021-05-12_final.stac-item
2021-06-02 11:47:07	ga_s2am_ard_3-2-1_50HNH_2021-06-02_final.stac-item
2021-06-21 12:14:28	ga_s2am_ard_3-2-1_49KGP_2021-06-21_final.stac-item
2021-06-25 11:55:58	ga_s2am_ard_3-2-1_50JLN_2021-06-25_final.stac-item
2021-07-02 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-07-02_final.stac-item
2021-07-12 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-07-12_final
2021-07-15 11:56:14	ga_s2am_ard_3-2-1_50JLM_2021-07-15_final.stac-item
2021-09-26 12:04:03	ga_s2am_ard_3-2-1_49KHR_2021-09-26_final.stac-item
2021-10-10 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2021-10-10_final.stac-item
2021-10-10 11:47:26	ga_s2am_ard_3-2-1_50HNG_2021-10-10_final
2021-10-27 11:35:55	ga_s2am_ard_3-2-1_50JQN_2021-10-27_final.stac-item
2021-12-05 12:04:42	ga_s2am_ard_3-2-1_50JKT_2021-12-05_final.stac-item
2022-01-11 11:53:26	ga_s2am_ard_3-2-1_50KNC_2022-01-11_final.stac-item
2022-02-13 12:05:00	ga_s2am_ard_3-2-1_49JGM_2022-02-13_final.stac-item
2022-03-09 11:46:38	ga_s2am_ard_3-2-1_50HPK_2022-03-09_final.stac-item
2022-03-19 11:46:37	ga_s2am_ard_3-2-1_50HPK_2022-03-19_final.stac-item
2022-03-22 11:53:24	ga_s2am_ard_3-2-1_50KPC_2022-03-22_final.stac-item
2022-04-24 12:04:33	ga_s2am_ard_3-2-1_50KKU_2022-04-24_final.stac-item
2022-06-30 11:53:34	ga_s2am_ard_3-2-1_50KPC_2022-06-30_final.stac-item
2022-07-10 11:56:02	ga_s2am_ard_3-2-1_50JNN_2022-07-10_final.stac-item
2022-08-02 12:05:11	ga_s2am_ard_3-2-1_49JGM_2022-08-02_final.stac-item
2022-09-21 12:03:48	ga_s2am_ard_3-2-1_50KLB_2022-09-21_final.stac-item
2022-09-25 11:46:33	ga_s2am_ard_3-2-1_50JML_2022-09-25_final.stac-item
2022-10-31 12:05:01	ga_s2am_ard_3-2-1_49JHM_2022-10-31_final.stac-item
2022-12-07 11:56:41	ga_s2am_ard_3-2-1_50HLK_2022-12-07_final.stac-item
2022-12-30 12:03:40	ga_s2am_ard_3-2-1_50KLB_2022-12-30_final.stac-item
2023-02-22 11:46:49	ga_s2am_ard_3-2-1_50HNJ_2023-02-22_nrt.stac-item
2023-02-22 11:46:49	ga_s2am_ard_3-2-1_50HNJ_2023-02-22_final
2023-03-13 12:13:50	ga_s2am_ard_3-2-1_50KKA_2023-03-13_final
2023-04-03 11:47:06	ga_s2am_ard_3-2-1_50HNH_2023-04-03_final
2023-04-06 11:57:09	ga_s2am_ard_3-2-1_50HLH_2023-04-06_final
2023-05-29 12:04:25	ga_s2am_ard_3-2-1_50KMU_2023-05-29_final
2023-05-29 12:04:35	ga_s2am_ard_3-2-1_49KGP_2023-05-29_final
2023-06-11 12:14:31	ga_s2am_ard_3-2-1_49KGP_2023-06-11_final
2023-06-22 11:47:06	ga_s2am_ard_3-2-1_50HPH_2023-06-22_final
2023-06-28 12:04:48	ga_s2am_ard_3-2-1_49JGN_2023-06-28_final
2023-07-05 11:56:27	ga_s2am_ard_3-2-1_50JML_2023-07-05_final
2023-07-28 12:04:30	ga_s2am_ard_3-2-1_50KLU_2023-07-28_final
2023-08-18 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2023-08-18_final
2023-09-03 11:55:00	ga_s2am_ard_3-2-1_50JMS_2023-09-03_final
2023-10-29 12:14:27	ga_s2am_ard_3-2-1_49KGP_2023-10-29_final
2023-12-25 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-12-25_final
2024-01-24 12:05:08	ga_s2am_ard_3-2-1_49JGL_2024-01-24_final
2024-02-20 11:55:40	ga_s2am_ard_3-2-1_50JLP_2024-02-20_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

All years