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
2016-06-06 11:05:23	ga_s2am_ard_3-2-1_52JDN_2016-06-06_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HPH_2016-07-28_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JMM_2016-08-20_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51KWP_2016-10-30_final.stac-item
2016-11-23 11:01:01	ga_s2am_ard_3-2-1_52LGH_2016-11-23_final.stac-item
2016-12-26 11:07:06	ga_s2am_ard_3-2-1_52KEC_2016-12-26_final.stac-item
2016-12-26 11:14:08	ga_s2am_ard_3-2-1_52JDT_2016-12-26_final.stac-item
2017-01-02 11:02:35	ga_s2am_ard_3-2-1_52KDV_2017-01-02_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52JBT_2017-01-25_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KPV_2017-02-13_final.stac-item
2017-02-14 11:07:06	ga_s2am_ard_3-2-1_52LEH_2017-02-14_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_52LDJ_2017-04-28_final.stac-item
2017-09-22 11:11:57	ga_s2am_ard_3-2-1_51HYE_2017-09-22_final.stac-item
2017-10-04 11:51:53	ga_s2am_ard_3-2-1_50JKM_2017-10-04_final.stac-item
2017-10-06 10:53:13	ga_s2am_ard_3-2-1_52JHS_2017-10-06_final.stac-item
2017-10-09 11:02:09	ga_s2am_ard_3-2-1_52JET_2017-10-09_final.stac-item
2017-12-04 11:22:04	ga_s2am_ard_3-2-1_51HUC_2017-12-04_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_52LBK_2018-01-13_final.stac-item
2018-01-27 10:57:11	ga_s2am_ard_3-2-1_52KHG_2018-01-27_final.stac-item
2018-01-30 11:12:10	ga_s2am_ard_3-2-1_51KZP_2018-01-30_final.stac-item
2018-04-22 11:53:56	ga_s2am_ard_3-2-1_50JNM_2018-04-22_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51JTF_2018-05-06_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKM_2018-05-25_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_50JQM_2018-06-05_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQL_2018-06-18_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_52JGM_2018-10-28_final.stac-item
2018-11-01 12:05:28	ga_s2am_ard_3-2-1_50JKP_2018-11-01_final.stac-item
2018-11-06 11:15:35	ga_s2am_ard_3-2-1_51JYH_2018-11-06_final.stac-item
2018-12-09 11:24:32	ga_s2am_ard_3-2-1_51JXM_2018-12-09_final.stac-item
2018-12-16 11:15:57	ga_s2am_ard_3-2-1_52JBL_2018-12-16_final.stac-item
2019-01-25 11:11:33	ga_s2am_ard_3-2-1_52LDJ_2019-01-25_final.stac-item
2019-02-02 12:14:57	ga_s2am_ard_3-2-1_49JFM_2019-02-02_final.stac-item
2019-03-11 12:06:05	ga_s2am_ard_3-2-1_50JKM_2019-03-11_final.stac-item
2019-04-14 11:45:27	ga_s2am_ard_3-2-1_50JNQ_2019-04-14_final.stac-item
2019-06-17 11:25:09	ga_s2am_ard_3-2-1_51JYK_2019-06-17_final.stac-item
2019-06-26 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-06-26_final.stac-item
2019-11-30 11:44:12	ga_s2am_ard_3-2-1_50KQU_2019-11-30_final.stac-item
2019-12-04 11:27:00	ga_s2am_ard_3-2-1_51HUC_2019-12-04_final.stac-item
2019-12-14 11:21:31	ga_s2am_ard_3-2-1_52LCJ_2019-12-14_final.stac-item
2020-03-03 11:23:54	ga_s2am_ard_3-2-1_51KWQ_2020-03-03_final.stac-item
2020-04-28 11:43:35	ga_s2am_ard_3-2-1_51KTS_2020-04-28_final.stac-item
2020-07-17 11:45:19	ga_s2am_ard_3-2-1_51JTK_2020-07-17_final.stac-item
2020-08-03 11:36:52	ga_s2am_ard_3-2-1_51HTD_2020-08-03_final.stac-item
2020-08-21 10:56:06	ga_s2am_ard_3-2-1_52JFL_2020-08-21_final.stac-item
2020-11-14 11:47:10	ga_s2am_ard_3-2-1_50HNH_2020-11-14_final.stac-item
2020-11-25 11:13:41	ga_s2am_ard_3-2-1_52KBA_2020-11-25_final.stac-item
2020-12-02 11:03:41	ga_s2am_ard_3-2-1_52KGV_2020-12-02_final.stac-item
2020-12-12 11:02:51	ga_s2am_ard_3-2-1_52KHC_2020-12-12_final.stac-item
2021-03-22 11:04:46	ga_s2am_ard_3-2-1_52JER_2021-03-22_final.stac-item
2021-06-02 11:43:44	ga_s2am_ard_3-2-1_51KUR_2021-06-02_final.stac-item
2021-06-03 11:16:38	ga_s2am_ard_3-2-1_51HYD_2021-06-03_final.stac-item
2021-08-05 11:23:03	ga_s2am_ard_3-2-1_51KXU_2021-08-05_final.stac-item
2021-10-20 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2021-10-20_final.stac-item
2021-10-27 11:36:43	ga_s2am_ard_3-2-1_50HPK_2021-10-27_final.stac-item
2021-11-20 11:15:07	ga_s2am_ard_3-2-1_52JBQ_2021-11-20_final.stac-item
2021-12-04 10:55:45	ga_s2am_ard_3-2-1_52JFM_2021-12-04_final.stac-item
2021-12-09 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2021-12-09_final.stac-item
2022-01-16 11:03:23	ga_s2am_ard_3-2-1_52KHA_2022-01-16_final.stac-item
2022-01-16 11:05:49	ga_s2am_ard_3-2-1_52JDM_2022-01-16_final.stac-item
2022-02-01 11:23:54	ga_s2am_ard_3-2-1_51KYQ_2022-02-01_final.stac-item
2022-02-01 11:25:38	ga_s2am_ard_3-2-1_51JXH_2022-02-01_final.stac-item
2022-03-07 11:04:59	ga_s2am_ard_3-2-1_52JCR_2022-03-07_final.stac-item
2022-03-19 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2022-03-19_final.stac-item
2022-04-02 11:25:43	ga_s2am_ard_3-2-1_51JVH_2022-04-02_final.stac-item
2022-04-12 11:25:48	ga_s2am_ard_3-2-1_51JVH_2022-04-12_final.stac-item
2022-04-28 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2022-04-28_final.stac-item
2022-05-22 11:25:49	ga_s2am_ard_3-2-1_51JWH_2022-05-22_final.stac-item
2022-05-24 12:05:22	ga_s2am_ard_3-2-1_49JGL_2022-05-24_final.stac-item
2022-05-27 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-05-27_final.stac-item
2022-06-02 10:53:51	ga_s2am_ard_3-2-1_52KHV_2022-06-02_final.stac-item
2022-06-17 11:46:12	ga_s2am_ard_3-2-1_50JQM_2022-06-17_final.stac-item
2022-06-28 11:12:01	ga_s2am_ard_3-2-1_52LEH_2022-06-28_final.stac-item
2022-09-28 11:55:17	ga_s2am_ard_3-2-1_50JMR_2022-09-28_final.stac-item
2022-10-02 11:32:18	ga_s2am_ard_3-2-1_51KXB_2022-10-02_final.stac-item
2022-10-06 11:16:00	ga_s2am_ard_3-2-1_51JYG_2022-10-06_final.stac-item
2022-10-10 10:56:10	ga_s2am_ard_3-2-1_52JEL_2022-10-10_final.stac-item
2022-10-11 12:06:15	ga_s2am_ard_3-2-1_50JKM_2022-10-11_final.stac-item
2022-11-21 11:33:42	ga_s2am_ard_3-2-1_51KWR_2022-11-21_final.stac-item
2022-11-22 11:03:27	ga_s2am_ard_3-2-1_52KGA_2022-11-22_final.stac-item
2023-01-07 11:22:59	ga_s2am_ard_3-2-1_51KXU_2023-01-07_final.stac-item
2023-01-17 11:21:04	ga_s2am_ard_3-2-1_52LBL_2023-01-17_nrt.stac-item
2023-01-24 11:11:41	ga_s2am_ard_3-2-1_52LFH_2023-01-24_final.stac-item
2023-01-27 11:23:47	ga_s2am_ard_3-2-1_51KZQ_2023-01-27_final.stac-item
2023-02-22 11:42:25	ga_s2am_ard_3-2-1_51KVA_2023-02-22_nrt.stac-item
2023-02-23 11:13:02	ga_s2am_ard_3-2-1_52KDC_2023-02-23_final
2023-03-31 11:35:35	ga_s2am_ard_3-2-1_50JQP_2023-03-31_final
2023-04-01 11:03:55	ga_s2am_ard_3-2-1_52KGU_2023-04-01_final
2023-04-13 11:42:46	ga_s2am_ard_3-2-1_51KUV_2023-04-13_final
2023-04-13 11:44:43	ga_s2am_ard_3-2-1_50JQS_2023-04-13_final
2023-04-14 11:13:30	ga_s2am_ard_3-2-1_52KEA_2023-04-14_final
2023-06-26 11:26:33	ga_s2am_ard_3-2-1_51HVE_2023-06-26_final
2023-07-05 11:57:19	ga_s2am_ard_3-2-1_49HGC_2023-07-05_nrt
2023-09-13 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2023-09-13_final
2023-11-12 11:56:17	ga_s2am_ard_3-2-1_50JNL_2023-11-12_final
2024-01-05 11:36:16	ga_s2am_ard_3-2-1_50JQL_2024-01-05_final
2024-01-19 11:11:25	ga_s2am_ard_3-2-1_52LEJ_2024-01-19_final
2024-01-22 11:23:14	ga_s2am_ard_3-2-1_51KZS_2024-01-22_final
2024-03-02 11:23:10	ga_s2am_ard_3-2-1_51KYT_2024-03-02_final
2024-03-03 10:52:45	ga_s2am_ard_3-2-1_52KHD_2024-03-03_final
2024-03-06 11:05:09	ga_s2am_ard_3-2-1_52JCQ_2024-03-06_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

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