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
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_50HMJ_2015-11-21_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51JUF_2015-12-25_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50JQM_2016-02-06_final.stac-item
2016-02-10 11:11:39	ga_s2am_ard_3-2-1_51HWC_2016-02-10_final
2016-03-15 10:47:26	ga_s2am_ard_3-2-1_52JFT_2016-03-15_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_49JGL_2016-03-16_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KWA_2016-04-06_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_51HXE_2016-04-10_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_49JGL_2016-04-15_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JNP_2016-04-19_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50KQA_2016-04-19_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51JWN_2016-04-23_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HQK_2016-04-29_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50KQA_2016-04-29_final.stac-item
2016-05-04 10:52:08	ga_s2am_ard_3-2-1_52JEL_2016-05-04_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HLG_2016-05-09_final
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JML_2016-05-09_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50JQM_2016-05-16_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLQ_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNR_2016-05-29_final.stac-item
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_50KLC_2016-06-04_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JLR_2016-07-21_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMK_2016-10-09_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50HLH_2016-12-15_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HLH_2017-01-14_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50HMH_2017-02-26_final.stac-item
2017-05-01 11:36:06	ga_s2am_ard_3-2-1_51JVF_2017-05-01_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51KWB_2017-09-08_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50HLH_2018-01-19_final.stac-item
2018-01-23 11:26:03	ga_s2am_ard_3-2-1_51HWE_2018-01-23_final.stac-item
2018-01-23 11:26:03	ga_s2am_ard_3-2-1_51JUF_2018-01-23_final.stac-item
2018-02-21 11:54:34	ga_s2am_ard_3-2-1_50HLH_2018-02-21_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51LUE_2018-04-29_final.stac-item
2018-05-26 11:27:41	ga_s2am_ard_3-2-1_51LXD_2018-05-26_final.stac-item
2018-09-13 11:26:17	ga_s2am_ard_3-2-1_51KXS_2018-09-13_final.stac-item
2019-04-14 11:41:20	ga_s2am_ard_3-2-1_51LUF_2019-04-14_final.stac-item
2019-05-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-05-04_final.stac-item
2019-06-06 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2019-06-06_final.stac-item
2019-08-16 11:23:30	ga_s2am_ard_3-2-1_52KCA_2019-08-16_final.stac-item
2019-11-16 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2019-11-16_final.stac-item
2019-12-23 11:57:00	ga_s2am_ard_3-2-1_50HMH_2019-12-23_final.stac-item
2019-12-30 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-12-30_final.stac-item
2020-01-10 11:14:32	ga_s2am_ard_3-2-1_51JZM_2020-01-10_final.stac-item
2020-01-16 11:36:26	ga_s2am_ard_3-2-1_51HUE_2020-01-16_final.stac-item
2020-02-08 11:47:02	ga_s2am_ard_3-2-1_50HMH_2020-02-08_final.stac-item
2020-02-28 11:41:28	ga_s2am_ard_3-2-1_51LUE_2020-02-28_final.stac-item
2020-04-04 12:06:00	ga_s2am_ard_3-2-1_50JLM_2020-04-04_final.stac-item
2020-05-25 11:33:03	ga_s2am_ard_3-2-1_51KWU_2020-05-25_final.stac-item
2020-05-25 11:33:09	ga_s2am_ard_3-2-1_51KXT_2020-05-25_final.stac-item
2020-06-08 11:13:34	ga_s2am_ard_3-2-1_52KBB_2020-06-08_final.stac-item
2020-06-08 11:13:35	ga_s2am_ard_3-2-1_51KZS_2020-06-08_final.stac-item
2020-06-08 11:13:46	ga_s2am_ard_3-2-1_52KBA_2020-06-08_final.stac-item
2020-07-04 11:34:20	ga_s2am_ard_3-2-1_51JXN_2020-07-04_final.stac-item
2020-07-11 11:23:25	ga_s2am_ard_3-2-1_52KBB_2020-07-11_final.stac-item
2020-07-28 11:13:34	ga_s2am_ard_3-2-1_51KZS_2020-07-28_final.stac-item
2021-01-19 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2021-01-19_final.stac-item
2021-01-20 11:36:11	ga_s2am_ard_3-2-1_51JVF_2021-01-20_final.stac-item
2021-01-23 11:47:10	ga_s2am_ard_3-2-1_50HMH_2021-01-23_final.stac-item
2021-03-11 11:37:17	ga_s2am_ard_3-2-1_50HQG_2021-03-11_final
2021-03-24 11:45:45	ga_s2am_ard_3-2-1_50JQN_2021-03-24_final.stac-item
2021-04-09 12:04:09	ga_s2am_ard_3-2-1_49KHQ_2021-04-09_final.stac-item
2021-04-23 11:46:03	ga_s2am_ard_3-2-1_51JTF_2021-04-23_final.stac-item
2021-05-08 10:56:03	ga_s2am_ard_3-2-1_52JEL_2021-05-08_final.stac-item
2021-07-22 11:42:49	ga_s2am_ard_3-2-1_51KUV_2021-07-22_final.stac-item
2021-09-08 11:06:03	ga_s2am_ard_3-2-1_52JDL_2021-09-08_final.stac-item
2021-09-09 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-09-09_final
2021-09-24 11:23:31	ga_s2am_ard_3-2-1_52KCA_2021-09-24_final.stac-item
2021-10-01 11:15:37	ga_s2am_ard_3-2-1_52JCN_2021-10-01_final.stac-item
2022-01-12 11:26:53	ga_s2am_ard_3-2-1_51HVC_2022-01-12_final.stac-item
2022-04-02 11:23:23	ga_s2am_ard_3-2-1_51KZS_2022-04-02_final.stac-item
2022-04-14 12:05:58	ga_s2am_ard_3-2-1_50JKN_2022-04-14_final.stac-item
2022-05-22 11:23:28	ga_s2am_ard_3-2-1_51KZS_2022-05-22_final.stac-item
2022-07-25 11:05:23	ga_s2am_ard_3-2-1_52JFP_2022-07-25_final.stac-item
2022-08-09 11:57:03	ga_s2am_ard_3-2-1_50HMJ_2022-08-09_final.stac-item
2022-09-02 11:36:26	ga_s2am_ard_3-2-1_51JUF_2022-09-02_final.stac-item
2022-09-03 11:05:13	ga_s2am_ard_3-2-1_52JEQ_2022-09-03_final.stac-item
2022-09-13 11:04:53	ga_s2am_ard_3-2-1_52JFR_2022-09-13_final.stac-item
2022-09-13 11:05:08	ga_s2am_ard_3-2-1_52JFQ_2022-09-13_final.stac-item
2022-09-22 11:31:35	ga_s2am_ard_3-2-1_51LXE_2022-09-22_final
2022-09-23 11:04:54	ga_s2am_ard_3-2-1_52JER_2022-09-23_final.stac-item
2023-01-07 11:22:08	ga_s2am_ard_3-2-1_51KZB_2023-01-07_final.stac-item
2023-01-20 11:36:05	ga_s2am_ard_3-2-1_51JVF_2023-01-20_final.stac-item
2023-01-20 11:36:18	ga_s2am_ard_3-2-1_51HVE_2023-01-20_final.stac-item
2023-01-26 11:57:06	ga_s2am_ard_3-2-1_50HLH_2023-01-26_final.stac-item
2023-02-25 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-02-25_final
2023-04-03 11:45:28	ga_s2am_ard_3-2-1_51JTJ_2023-04-03_final
2023-04-07 11:25:57	ga_s2am_ard_3-2-1_51JWG_2023-04-07_final
2023-04-09 12:05:38	ga_s2am_ard_3-2-1_50JLP_2023-04-09_final
2023-05-23 11:43:18	ga_s2am_ard_3-2-1_51KUT_2023-05-23_final
2023-05-27 11:23:24	ga_s2am_ard_3-2-1_52KBB_2023-05-27_final
2023-05-29 12:05:44	ga_s2am_ard_3-2-1_50JKP_2023-05-29_final
2023-06-16 11:23:40	ga_s2am_ard_3-2-1_51KZR_2023-06-16_final
2023-09-08 11:05:31	ga_s2am_ard_3-2-1_52JFN_2023-09-08_final
2023-09-08 11:05:43	ga_s2am_ard_3-2-1_52JFM_2023-09-08_final
2023-09-08 11:06:08	ga_s2am_ard_3-2-1_52JDL_2023-09-08_final
2023-09-17 11:36:14	ga_s2am_ard_3-2-1_51JVF_2023-09-17_final
2023-09-18 11:04:38	ga_s2am_ard_3-2-1_52JGR_2023-09-18_final
2023-09-21 11:14:48	ga_s2am_ard_3-2-1_52JDR_2023-09-21_final
2023-09-27 11:36:26	ga_s2am_ard_3-2-1_51HVE_2023-09-27_final
2023-10-16 12:04:59	ga_s2am_ard_3-2-1_49JGM_2023-10-16_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