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_49JHN_2015-12-17_final.stac-item
2016-01-01 11:14:13	ga_s2am_ard_3-2-1_51KZQ_2016-01-01_final.stac-item
2016-05-26 11:36:09	ga_s2am_ard_3-2-1_50JQL_2016-05-26_final.stac-item
2016-10-27 11:09:33	ga_s2am_ard_3-2-1_52KFC_2016-10-27_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHR_2016-11-11_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51LYD_2016-12-12_final.stac-item
2017-01-14 11:34:53	ga_s2am_ard_3-2-1_51JUM_2017-01-14_final.stac-item
2017-03-16 11:12:06	ga_s2am_ard_3-2-1_52KBU_2017-03-16_final.stac-item
2017-04-15 11:12:01	ga_s2am_ard_3-2-1_51HXE_2017-04-15_final.stac-item
2017-04-22 11:03:00	ga_s2am_ard_3-2-1_52JEL_2017-04-22_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HLH_2017-05-04_final.stac-item
2017-05-12 11:03:02	ga_s2am_ard_3-2-1_52KEV_2017-05-12_final.stac-item
2017-05-22 11:02:14	ga_s2am_ard_3-2-1_52KGD_2017-05-22_final.stac-item
2017-05-25 11:12:04	ga_s2am_ard_3-2-1_51HYE_2017-05-25_final.stac-item
2017-06-28 10:53:13	ga_s2am_ard_3-2-1_53JLM_2017-06-28_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_51KUT_2017-10-11_final.stac-item
2017-12-04 11:22:04	ga_s2am_ard_3-2-1_51KZP_2017-12-04_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51KUR_2018-02-25_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_52LDJ_2018-04-23_final.stac-item
2018-04-27 10:57:18	ga_s2am_ard_3-2-1_52KFB_2018-04-27_final.stac-item
2018-08-08 11:07:12	ga_s2am_ard_3-2-1_51KZR_2018-08-08_final.stac-item
2018-09-22 10:17:01	ga_s2am_ard_3-2-1_53HNB_2018-09-22_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KUR_2018-11-02_final.stac-item
2019-01-07 11:55:54	ga_s2am_ard_3-2-1_50JKN_2019-01-07_final.stac-item
2019-02-27 11:24:00	ga_s2am_ard_3-2-1_51KZP_2019-02-27_final.stac-item
2019-03-09 11:24:09	ga_s2am_ard_3-2-1_51KWP_2019-03-09_final.stac-item
2019-04-24 11:46:05	ga_s2am_ard_3-2-1_51JTG_2019-04-24_final.stac-item
2019-05-21 11:32:54	ga_s2am_ard_3-2-1_51KYU_2019-05-21_final.stac-item
2019-06-07 11:24:00	ga_s2am_ard_3-2-1_51KZP_2019-06-07_final.stac-item
2019-07-28 10:55:59	ga_s2am_ard_3-2-1_53JKF_2019-07-28_final.stac-item
2019-11-24 11:22:52	ga_s2am_ard_3-2-1_52KBD_2019-11-24_final.stac-item
2019-12-04 11:22:54	ga_s2am_ard_3-2-1_51KYU_2019-12-04_final.stac-item
2019-12-17 11:32:31	ga_s2am_ard_3-2-1_51KYV_2019-12-17_final.stac-item
2020-03-07 11:03:45	ga_s2am_ard_3-2-1_52KEV_2020-03-07_final.stac-item
2020-03-15 12:03:19	ga_s2am_ard_3-2-1_50KMC_2020-03-15_final.stac-item
2020-03-15 12:04:21	ga_s2am_ard_3-2-1_50KLU_2020-03-15_final.stac-item
2020-06-03 12:04:20	ga_s2am_ard_3-2-1_50KKV_2020-06-03_final.stac-item
2020-08-16 11:43:24	ga_s2am_ard_3-2-1_51KTT_2020-08-16_final.stac-item
2020-09-24 10:36:26	ga_s2am_ard_3-2-1_53HND_2020-09-24_final.stac-item
2020-10-03 11:03:25	ga_s2am_ard_3-2-1_52KEB_2020-10-03_final.stac-item
2020-11-21 11:33:29	ga_s2am_ard_3-2-1_51KWS_2020-11-21_final.stac-item
2020-12-23 12:14:44	ga_s2am_ard_3-2-1_49JFN_2020-12-23_final.stac-item
2021-02-13 11:12:48	ga_s2am_ard_3-2-1_52KDD_2021-02-13_final.stac-item
2021-02-21 12:14:26	ga_s2am_ard_3-2-1_49KGP_2021-02-21_final.stac-item
2021-03-12 11:02:54	ga_s2am_ard_3-2-1_52KHC_2021-03-12_final.stac-item
2021-03-28 11:25:11	ga_s2am_ard_3-2-1_51JWK_2021-03-28_final.stac-item
2021-05-13 11:43:03	ga_s2am_ard_3-2-1_51KTU_2021-05-13_final.stac-item
2021-06-09 11:34:37	ga_s2am_ard_3-2-1_50JRT_2021-06-09_final.stac-item
2021-07-21 12:14:30	ga_s2am_ard_3-2-1_49KGP_2021-07-21_final.stac-item
2021-09-07 11:31:49	ga_s2am_ard_3-2-1_51LZC_2021-09-07_final.stac-item
2021-09-17 11:36:50	ga_s2am_ard_3-2-1_50HQJ_2021-09-17_final.stac-item
2021-10-01 11:13:44	ga_s2am_ard_3-2-1_51KZR_2021-10-01_final.stac-item
2021-10-13 11:56:45	ga_s2am_ard_3-2-1_50HLK_2021-10-13_final.stac-item
2021-10-24 11:23:12	ga_s2am_ard_3-2-1_51KZT_2021-10-24_final.stac-item
2021-11-12 11:56:16	ga_s2am_ard_3-2-1_50JKM_2021-11-12_final.stac-item
2021-12-15 12:04:42	ga_s2am_ard_3-2-1_50JKT_2021-12-15_final.stac-item
2021-12-16 11:37:03	ga_s2am_ard_3-2-1_50HQH_2021-12-16_final.stac-item
2022-01-16 11:06:24	ga_s2am_ard_3-2-1_52HBK_2022-01-16_final.stac-item
2022-02-08 11:15:42	ga_s2am_ard_3-2-1_51JXH_2022-02-08_final.stac-item
2022-02-10 11:52:36	ga_s2am_ard_3-2-1_50KPF_2022-02-10_final
2022-03-25 10:26:56	ga_s2am_ard_3-2-1_53HNB_2022-03-25_final.stac-item
2022-04-22 11:26:22	ga_s2am_ard_3-2-1_51JUF_2022-04-22_final.stac-item
2022-05-24 12:04:25	ga_s2am_ard_3-2-1_49KGQ_2022-05-24_final.stac-item
2022-07-07 11:43:22	ga_s2am_ard_3-2-1_51KTT_2022-07-07_final.stac-item
2022-07-16 10:34:26	ga_s2am_ard_3-2-1_53JNN_2022-07-16_final.stac-item
2022-07-21 11:25:45	ga_s2am_ard_3-2-1_51JYH_2022-07-21_final.stac-item
2022-08-17 11:15:37	ga_s2am_ard_3-2-1_51JYJ_2022-08-17_final.stac-item
2022-08-26 11:44:11	ga_s2am_ard_3-2-1_51KUQ_2022-08-26_final
2022-09-19 11:22:50	ga_s2am_ard_3-2-1_51KYV_2022-09-19_final.stac-item
2022-11-11 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2022-11-11_final.stac-item
2022-11-20 10:26:33	ga_s2am_ard_3-2-1_53HQC_2022-11-20_final.stac-item
2022-11-25 11:15:42	ga_s2am_ard_3-2-1_51JXH_2022-11-25_final.stac-item
2022-11-28 11:24:04	ga_s2am_ard_3-2-1_52KBU_2022-11-28_final.stac-item
2022-12-27 11:53:09	ga_s2am_ard_3-2-1_50KRC_2022-12-27_final.stac-item
2022-12-28 11:24:00	ga_s2am_ard_3-2-1_51KWQ_2022-12-28_final.stac-item
2023-02-27 10:52:17	ga_s2am_ard_3-2-1_52KHF_2023-02-27_final
2023-03-04 11:43:21	ga_s2am_ard_3-2-1_51KVS_2023-03-04_final
2023-03-08 11:22:51	ga_s2am_ard_3-2-1_51KYU_2023-03-08_final
2023-03-25 11:14:07	ga_s2am_ard_3-2-1_51KZP_2023-03-25_final
2023-04-21 11:05:14	ga_s2am_ard_3-2-1_52JEP_2023-04-21_final
2023-04-29 12:04:46	ga_s2am_ard_3-2-1_49JGN_2023-04-29_final
2023-05-01 11:03:40	ga_s2am_ard_3-2-1_52KEA_2023-05-01_final
2023-05-17 11:22:24	ga_s2am_ard_3-2-1_52KBF_2023-05-17_final
2023-06-16 11:24:06	ga_s2am_ard_3-2-1_51KWQ_2023-06-16_final
2023-06-18 10:26:22	ga_s2am_ard_3-2-1_53HQD_2023-06-18_final
2023-07-10 11:04:48	ga_s2am_ard_3-2-1_52JFR_2023-07-10_final
2023-07-23 11:13:44	ga_s2am_ard_3-2-1_52KBA_2023-07-23_final
2023-10-06 10:26:30	ga_s2am_ard_3-2-1_53HPD_2023-10-06_final
2023-10-21 11:16:34	ga_s2am_ard_3-2-1_52HBJ_2023-10-21_nrt
2023-12-16 11:36:42	ga_s2am_ard_3-2-1_51HTD_2023-12-16_final
2024-01-05 11:35:52	ga_s2am_ard_3-2-1_51JVG_2024-01-05_final
2024-01-11 11:55:01	ga_s2am_ard_3-2-1_50JNR_2024-01-11_final
2024-01-15 11:32:55	ga_s2am_ard_3-2-1_51KYT_2024-01-15_final
2024-02-03 10:26:32	ga_s2am_ard_3-2-1_53HPC_2024-02-03_final
2024-02-21 11:23:11	ga_s2am_ard_3-2-1_51KXT_2024-02-21_final
2024-03-09 11:15:30	ga_s2am_ard_3-2-1_51JXJ_2024-03-09_final
2024-03-25 11:33:03	ga_s2am_ard_3-2-1_51KYT_2024-03-25_final
2024-04-14 11:33:03	ga_s2am_ard_3-2-1_51KVU_2024-04-14_final
2024-04-17 11:43:28	ga_s2am_ard_3-2-1_51KVS_2024-04-17_final
2024-05-28 11:13:06	ga_s2am_ard_3-2-1_52KDC_2024-05-28_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

All years