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
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_50HPH_2015-12-08_final.stac-item
2016-07-24 12:04:46	ga_s2am_ard_3-2-1_50JKS_2016-07-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KGP_2016-11-24_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50HNK_2017-01-07_final.stac-item
2017-02-20 11:36:27	ga_s2am_ard_3-2-1_50HPH_2017-02-20_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50KKV_2017-03-31_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49JGM_2017-04-20_final.stac-item
2017-04-23 12:13:36	ga_s2am_ard_3-2-1_49KGP_2017-04-23_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50KRC_2017-05-17_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50KMU_2017-06-06_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_51HUC_2017-07-10_final.stac-item
2017-11-13 11:54:29	ga_s2am_ard_3-2-1_50JNM_2017-11-13_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50KRD_2017-11-20_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50KNA_2017-11-26_final.stac-item
2017-11-29 12:13:16	ga_s2am_ard_3-2-1_49JGM_2017-11-29_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JNM_2018-02-08_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-03-06_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2018-03-19_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKP_2018-03-26_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49JGM_2018-03-29_final.stac-item
2018-03-30 11:39:33	ga_s2am_ard_3-2-1_50KRC_2018-03-30_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-18_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50KRC_2018-06-01_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50HQJ_2018-06-15_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HMK_2018-08-27_final.stac-item
2018-12-11 12:05:21	ga_s2am_ard_3-2-1_49JGK_2018-12-11_final.stac-item
2018-12-21 12:04:37	ga_s2am_ard_3-2-1_49JGN_2018-12-21_final.stac-item
2019-01-07 11:55:51	ga_s2am_ard_3-2-1_50JLN_2019-01-07_final.stac-item
2019-01-07 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2019-01-07_final.stac-item
2019-01-13 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-13_final.stac-item
2019-01-17 11:54:07	ga_s2am_ard_3-2-1_50KMV_2019-01-17_final.stac-item
2019-02-10 11:36:45	ga_s2am_ard_3-2-1_50HQJ_2019-02-10_final.stac-item
2019-05-17 11:53:35	ga_s2am_ard_3-2-1_50KMC_2019-05-17_final.stac-item
2019-06-12 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-06-12_final.stac-item
2019-06-19 12:04:28	ga_s2am_ard_3-2-1_50KLU_2019-06-19_final.stac-item
2019-07-16 11:56:05	ga_s2am_ard_3-2-1_50JKN_2019-07-16_final.stac-item
2019-07-26 11:53:22	ga_s2am_ard_3-2-1_50KQC_2019-07-26_final.stac-item
2019-07-27 11:26:52	ga_s2am_ard_3-2-1_51HUD_2019-07-27_final.stac-item
2019-08-18 12:03:44	ga_s2am_ard_3-2-1_50KLB_2019-08-18_final.stac-item
2019-08-28 12:04:00	ga_s2am_ard_3-2-1_49KHR_2019-08-28_final.stac-item
2019-09-21 11:46:37	ga_s2am_ard_3-2-1_50HNK_2019-09-21_final.stac-item
2019-10-04 11:56:10	ga_s2am_ard_3-2-1_50JMM_2019-10-04_final.stac-item
2019-10-11 11:43:08	ga_s2am_ard_3-2-1_50KRD_2019-10-11_final.stac-item
2019-11-23 11:53:36	ga_s2am_ard_3-2-1_50KPB_2019-11-23_final.stac-item
2019-12-10 11:43:18	ga_s2am_ard_3-2-1_50KQC_2019-12-10_final.stac-item
2019-12-23 11:53:25	ga_s2am_ard_3-2-1_50KMC_2019-12-23_final.stac-item
2020-01-02 11:56:05	ga_s2am_ard_3-2-1_50JLM_2020-01-02_final.stac-item
2020-01-05 12:05:50	ga_s2am_ard_3-2-1_50JKN_2020-01-05_final.stac-item
2020-01-16 11:36:14	ga_s2am_ard_3-2-1_50JQL_2020-01-16_final.stac-item
2020-02-04 12:04:16	ga_s2am_ard_3-2-1_50KLU_2020-02-04_final.stac-item
2020-02-18 11:45:44	ga_s2am_ard_3-2-1_50JPN_2020-02-18_final.stac-item
2020-02-24 12:03:54	ga_s2am_ard_3-2-1_49KHR_2020-02-24_final.stac-item
2020-03-09 11:46:30	ga_s2am_ard_3-2-1_50HPK_2020-03-09_final.stac-item
2020-04-07 12:13:51	ga_s2am_ard_3-2-1_50KKA_2020-04-07_final.stac-item
2020-04-17 12:14:56	ga_s2am_ard_3-2-1_49JGM_2020-04-17_final.stac-item
2020-05-11 11:53:29	ga_s2am_ard_3-2-1_50KNC_2020-05-11_final.stac-item
2020-08-22 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-08-22_final.stac-item
2020-12-07 11:55:57	ga_s2am_ard_3-2-1_50JKN_2020-12-07_final.stac-item
2021-01-06 11:52:35	ga_s2am_ard_3-2-1_50KQF_2021-01-06_final
2021-04-06 11:57:02	ga_s2am_ard_3-2-1_50HMH_2021-04-06_final.stac-item
2021-04-09 12:04:20	ga_s2am_ard_3-2-1_50KLU_2021-04-09_final.stac-item
2021-04-29 12:04:37	ga_s2am_ard_3-2-1_50JLT_2021-04-29_final.stac-item
2021-07-08 12:04:27	ga_s2am_ard_3-2-1_50KLU_2021-07-08_final.stac-item
2021-08-04 11:52:37	ga_s2am_ard_3-2-1_50KQF_2021-08-04_final
2021-08-17 12:05:54	ga_s2am_ard_3-2-1_50JLN_2021-08-17_final.stac-item
2021-10-03 11:56:45	ga_s2am_ard_3-2-1_50HLK_2021-10-03_final.stac-item
2022-01-11 11:56:31	ga_s2am_ard_3-2-1_50HNK_2022-01-11_final.stac-item
2022-02-07 11:46:08	ga_s2am_ard_3-2-1_50JNM_2022-02-07_final.stac-item
2022-02-13 12:05:15	ga_s2am_ard_3-2-1_49JGL_2022-02-13_final.stac-item
2022-03-08 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-08_final.stac-item
2022-05-15 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2022-05-15_final.stac-item
2022-05-31 11:56:48	ga_s2am_ard_3-2-1_50HLK_2022-05-31_final.stac-item
2022-06-04 11:36:54	ga_s2am_ard_3-2-1_51HTD_2022-06-04_final.stac-item
2022-09-14 12:14:51	ga_s2am_ard_3-2-1_49JGN_2022-09-14_final.stac-item
2022-10-28 11:53:21	ga_s2am_ard_3-2-1_50KQC_2022-10-28_final.stac-item
2022-11-30 12:03:41	ga_s2am_ard_3-2-1_50KLB_2022-11-30_final.stac-item
2022-12-31 11:36:42	ga_s2am_ard_3-2-1_51HUD_2022-12-31_final.stac-item
2023-01-19 12:05:59	ga_s2am_ard_3-2-1_50JLM_2023-01-19_final.stac-item
2023-01-26 11:56:15	ga_s2am_ard_3-2-1_50JNL_2023-01-26_final.stac-item
2023-04-29 12:03:38	ga_s2am_ard_3-2-1_50KMB_2023-04-29_final
2023-04-30 11:36:34	ga_s2am_ard_3-2-1_50HQK_2023-04-30_final
2023-05-03 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-03_final
2023-05-19 12:06:06	ga_s2am_ard_3-2-1_50JLM_2023-05-19_final
2023-06-08 12:04:43	ga_s2am_ard_3-2-1_50JLT_2023-06-08_final
2023-07-31 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2023-07-31_final
2023-08-21 11:46:19	ga_s2am_ard_3-2-1_50JMM_2023-08-21_final
2023-10-03 11:55:48	ga_s2am_ard_3-2-1_50JKP_2023-10-03_final
2023-12-15 12:04:35	ga_s2am_ard_3-2-1_50JLT_2023-12-15_final
2023-12-22 11:56:36	ga_s2am_ard_3-2-1_50HLK_2023-12-22_final
2023-12-26 11:36:23	ga_s2am_ard_3-2-1_50JPL_2023-12-26_final
2024-01-04 12:04:28	ga_s2am_ard_3-2-1_49KGP_2024-01-04_final
2024-02-07 11:47:17	ga_s2am_ard_3-2-1_50HNG_2024-02-07_final
2024-02-10 11:56:07	ga_s2am_ard_3-2-1_50JLM_2024-02-10_final
2024-02-10 11:57:05	ga_s2am_ard_3-2-1_50HLH_2024-02-10_final
2024-02-13 12:04:10	ga_s2am_ard_3-2-1_50KKV_2024-02-13_final
2024-02-27 11:46:14	ga_s2am_ard_3-2-1_50JQL_2024-02-27_final
2024-04-14 11:36:34	ga_s2am_ard_3-2-1_51HTE_2024-04-14_final
2024-05-26 12:14:56	ga_s2am_ard_3-2-1_49JGM_2024-05-26_nrt
2024-05-31 11:27:05	ga_s2am_ard_3-2-1_51HUC_2024-05-31_nrt
2024-06-02 12:03:30	ga_s2am_ard_3-2-1_50KLC_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

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