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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49KHR_2015-12-17_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KGC_2016-01-18_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50JNM_2016-01-20_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51KTS_2016-05-29_final.stac-item
2016-09-27 11:07:08	ga_s2am_ard_3-2-1_52LGK_2016-09-27_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_51LUF_2016-10-16_final.stac-item
2016-11-23 11:01:01	ga_s2am_ard_3-2-1_52JEQ_2016-11-23_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50KPC_2017-01-07_final.stac-item
2017-01-19 10:52:06	ga_s2am_ard_3-2-1_52KGA_2017-01-19_final.stac-item
2017-02-14 11:07:06	ga_s2am_ard_3-2-1_52KCA_2017-02-14_final.stac-item
2017-03-12 11:27:30	ga_s2am_ard_3-2-1_51KXS_2017-03-12_final.stac-item
2017-04-02 11:02:44	ga_s2am_ard_3-2-1_52KEA_2017-04-02_final.stac-item
2017-10-10 12:13:43	ga_s2am_ard_3-2-1_50KKA_2017-10-10_final.stac-item
2017-11-18 11:02:08	ga_s2am_ard_3-2-1_52KHF_2017-11-18_final.stac-item
2017-12-30 11:37:45	ga_s2am_ard_3-2-1_51LUE_2017-12-30_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KHD_2018-02-26_final.stac-item
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_51KWS_2018-03-27_final.stac-item
2018-04-06 11:31:45	ga_s2am_ard_3-2-1_51KWV_2018-04-06_final.stac-item
2018-04-10 11:16:00	ga_s2am_ard_3-2-1_52JBL_2018-04-10_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JLM_2018-05-12_final
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HNB_2018-06-04_final.stac-item
2018-07-05 11:29:39	ga_s2am_ard_3-2-1_51KYT_2018-07-05_final.stac-item
2018-07-12 11:19:28	ga_s2am_ard_3-2-1_51KWP_2018-07-12_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52JFR_2018-08-02_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_51KUR_2018-08-07_final.stac-item
2018-09-26 11:34:41	ga_s2am_ard_3-2-1_51KUV_2018-09-26_final.stac-item
2018-10-07 11:07:09	ga_s2am_ard_3-2-1_52LEJ_2018-10-07_final.stac-item
2018-11-15 11:43:23	ga_s2am_ard_3-2-1_51KUS_2018-11-15_final.stac-item
2019-02-10 11:35:38	ga_s2am_ard_3-2-1_51JVH_2019-02-10_final.stac-item
2019-03-29 11:23:02	ga_s2am_ard_3-2-1_52KCC_2019-03-29_final.stac-item
2019-06-11 11:03:19	ga_s2am_ard_3-2-1_52KFB_2019-06-11_final.stac-item
2019-06-17 11:23:06	ga_s2am_ard_3-2-1_52KCC_2019-06-17_final.stac-item
2019-07-10 11:32:31	ga_s2am_ard_3-2-1_51KXA_2019-07-10_final.stac-item
2019-08-26 11:24:03	ga_s2am_ard_3-2-1_51KWQ_2019-08-26_final.stac-item
2019-09-19 11:06:03	ga_s2am_ard_3-2-1_52JDL_2019-09-19_final.stac-item
2019-11-16 12:04:26	ga_s2am_ard_3-2-1_50KLU_2019-11-16_final.stac-item
2019-11-21 11:13:55	ga_s2am_ard_3-2-1_52KBV_2019-11-21_final.stac-item
2019-12-01 11:12:27	ga_s2am_ard_3-2-1_52KFE_2019-12-01_final.stac-item
2019-12-11 11:10:39	ga_s2am_ard_3-2-1_52LGM_2019-12-11_final.stac-item
2019-12-28 11:01:26	ga_s2am_ard_3-2-1_52LGJ_2019-12-28_final.stac-item
2019-12-31 11:13:34	ga_s2am_ard_3-2-1_52KBA_2019-12-31_final.stac-item
2020-05-04 12:05:15	ga_s2am_ard_3-2-1_50JKR_2020-05-04_final.stac-item
2020-06-20 11:56:17	ga_s2am_ard_3-2-1_50JLM_2020-06-20_final.stac-item
2020-07-11 11:22:56	ga_s2am_ard_3-2-1_51KZU_2020-07-11_final.stac-item
2020-08-04 11:05:37	ga_s2am_ard_3-2-1_52JCN_2020-08-04_final.stac-item
2020-08-30 11:23:01	ga_s2am_ard_3-2-1_51KYU_2020-08-30_final.stac-item
2020-09-01 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-09-01_final.stac-item
2020-10-15 11:42:42	ga_s2am_ard_3-2-1_51KVA_2020-10-15_final.stac-item
2020-10-16 11:15:16	ga_s2am_ard_3-2-1_51JYK_2020-10-16_final.stac-item
2020-11-05 11:10:30	ga_s2am_ard_3-2-1_52LHN_2020-11-05_final.stac-item
2020-11-10 10:26:58	ga_s2am_ard_3-2-1_53HNB_2020-11-10_final.stac-item
2020-12-12 11:00:41	ga_s2am_ard_3-2-1_52LHM_2020-12-12_final.stac-item
2021-01-17 11:25:46	ga_s2am_ard_3-2-1_51JYG_2021-01-17_final.stac-item
2021-02-16 11:24:36	ga_s2am_ard_3-2-1_51JYM_2021-02-16_final.stac-item
2021-03-07 11:52:19	ga_s2am_ard_3-2-1_50KQG_2021-03-07_final
2021-04-17 11:23:01	ga_s2am_ard_3-2-1_51KZT_2021-04-17_final.stac-item
2021-04-24 11:13:29	ga_s2am_ard_3-2-1_52KDA_2021-04-24_final.stac-item
2021-04-24 11:15:39	ga_s2am_ard_3-2-1_51JXH_2021-04-24_final.stac-item
2021-07-20 11:05:01	ga_s2am_ard_3-2-1_52JFQ_2021-07-20_final.stac-item
2021-08-08 11:37:14	ga_s2am_ard_3-2-1_50HQH_2021-08-08_final.stac-item
2021-09-28 11:01:24	ga_s2am_ard_3-2-1_52LGK_2021-09-28_final.stac-item
2021-10-24 11:23:41	ga_s2am_ard_3-2-1_51KZR_2021-10-24_final.stac-item
2021-11-13 11:23:23	ga_s2am_ard_3-2-1_51KZS_2021-11-13_final.stac-item
2021-11-28 12:13:39	ga_s2am_ard_3-2-1_50KKB_2021-11-28_final.stac-item
2021-12-10 11:13:28	ga_s2am_ard_3-2-1_52KEA_2021-12-10_final.stac-item
2021-12-12 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-12-12_final
2021-12-27 11:02:02	ga_s2am_ard_3-2-1_52KGG_2021-12-27_final.stac-item
2022-02-28 11:13:31	ga_s2am_ard_3-2-1_52KEA_2022-02-28_final.stac-item
2022-03-07 11:00:52	ga_s2am_ard_3-2-1_52LGM_2022-03-07_final.stac-item
2022-03-07 11:05:17	ga_s2am_ard_3-2-1_52JEP_2022-03-07_final.stac-item
2022-04-06 11:00:50	ga_s2am_ard_3-2-1_52LGM_2022-04-06_final.stac-item
2022-05-02 11:23:40	ga_s2am_ard_3-2-1_51KZR_2022-05-02_final.stac-item
2022-05-09 11:13:37	ga_s2am_ard_3-2-1_52KDA_2022-05-09_final.stac-item
2022-05-22 11:21:39	ga_s2am_ard_3-2-1_52LDJ_2022-05-22_final.stac-item
2022-05-23 10:53:21	ga_s2am_ard_3-2-1_52KHB_2022-05-23_final.stac-item
2022-06-08 11:13:42	ga_s2am_ard_3-2-1_52KDA_2022-06-08_final.stac-item
2022-06-24 11:35:31	ga_s2am_ard_3-2-1_51JWJ_2022-06-24_final.stac-item
2022-07-04 11:33:35	ga_s2am_ard_3-2-1_51KUT_2022-07-04_final.stac-item
2022-08-23 11:32:53	ga_s2am_ard_3-2-1_51KXV_2022-08-23_final.stac-item
2022-09-22 11:32:36	ga_s2am_ard_3-2-1_51KWA_2022-09-22_final.stac-item
2022-09-25 11:44:17	ga_s2am_ard_3-2-1_50KPV_2022-09-25_final.stac-item
2022-10-21 12:04:33	ga_s2am_ard_3-2-1_49KGP_2022-10-21_final.stac-item
2022-10-25 11:43:21	ga_s2am_ard_3-2-1_50KRC_2022-10-25_final.stac-item
2022-10-29 11:22:52	ga_s2am_ard_3-2-1_52KCD_2022-10-29_final.stac-item
2022-11-05 11:15:47	ga_s2am_ard_3-2-1_51JXH_2022-11-05_final.stac-item
2023-01-23 11:43:00	ga_s2am_ard_3-2-1_50KRD_2023-01-23_final.stac-item
2023-02-25 11:53:48	ga_s2am_ard_3-2-1_50KMA_2023-02-25_final
2023-06-06 11:25:24	ga_s2am_ard_3-2-1_51JYJ_2023-06-06_final
2023-07-23 11:16:48	ga_s2am_ard_3-2-1_51HWD_2023-07-23_final
2023-08-25 11:25:48	ga_s2am_ard_3-2-1_51JWH_2023-08-25_final
2023-09-04 11:23:08	ga_s2am_ard_3-2-1_52KCC_2023-09-04_final
2023-09-18 11:05:05	ga_s2am_ard_3-2-1_52JEQ_2023-09-18_final
2023-09-20 11:43:20	ga_s2am_ard_3-2-1_51KTT_2023-09-20_final
2023-10-23 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-10-23_final
2023-10-31 11:12:34	ga_s2am_ard_3-2-1_52KDE_2023-10-31_final
2023-12-29 11:42:06	ga_s2am_ard_3-2-1_51KWB_2023-12-29_final
2024-01-28 11:46:28	ga_s2am_ard_3-2-1_50HPK_2024-01-28_final
2024-03-26 11:00:45	ga_s2am_ard_3-2-1_52LHM_2024-03-26_final
2024-04-20 11:52:23	ga_s2am_ard_3-2-1_50KQG_2024-04-20_final
2024-05-20 11:53:43	ga_s2am_ard_3-2-1_50KMB_2024-05-20_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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