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
2016-05-01 10:43:19	ga_s2am_ard_3-2-1_53JNM_2016-05-01_final.stac-item
2016-05-07 11:02:16	ga_s2am_ard_3-2-1_52KFB_2016-05-07_final.stac-item
2016-06-25 11:32:00	ga_s2am_ard_3-2-1_50JRT_2016-06-25_final.stac-item
2016-07-06 11:02:14	ga_s2am_ard_3-2-1_52KDV_2016-07-06_final.stac-item
2016-10-12 10:25:59	ga_s2am_ard_3-2-1_53HQE_2016-10-12_final.stac-item
2016-12-06 11:13:53	ga_s2am_ard_3-2-1_51KZP_2016-12-06_final.stac-item
2016-12-23 11:02:53	ga_s2am_ard_3-2-1_52KFU_2016-12-23_final.stac-item
2016-12-26 11:07:06	ga_s2am_ard_3-2-1_52KCA_2016-12-26_final.stac-item
2017-01-02 10:57:17	ga_s2am_ard_3-2-1_52LHM_2017-01-02_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_51JTK_2017-04-21_final.stac-item
2017-10-05 11:21:56	ga_s2am_ard_3-2-1_51HVE_2017-10-05_final.stac-item
2017-10-09 11:02:09	ga_s2am_ard_3-2-1_52KGA_2017-10-09_final.stac-item
2017-11-14 11:22:07	ga_s2am_ard_3-2-1_51HVC_2017-11-14_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JMR_2017-12-03_final.stac-item
2018-01-15 10:23:20	ga_s2am_ard_3-2-1_53HQB_2018-01-15_final.stac-item
2018-01-30 11:12:10	ga_s2am_ard_3-2-1_52KDU_2018-01-30_final.stac-item
2018-03-01 11:11:47	ga_s2am_ard_3-2-1_52HBK_2018-03-01_final.stac-item
2018-03-11 11:12:00	ga_s2am_ard_3-2-1_52KEV_2018-03-11_final.stac-item
2018-04-01 10:37:26	ga_s2am_ard_3-2-1_53HMD_2018-04-01_final.stac-item
2018-04-17 11:04:48	ga_s2am_ard_3-2-1_52JDL_2018-04-17_final.stac-item
2018-04-28 10:27:10	ga_s2am_ard_3-2-1_53JNM_2018-04-28_final.stac-item
2018-06-09 11:13:13	ga_s2am_ard_3-2-1_52KDU_2018-06-09_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HMJ_2018-07-21_final.stac-item
2018-09-15 10:27:04	ga_s2am_ard_3-2-1_53JMJ_2018-09-15_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KZQ_2018-10-10_final.stac-item
2018-11-06 11:15:47	ga_s2am_ard_3-2-1_52JBM_2018-11-06_final.stac-item
2018-11-18 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2018-11-18_final.stac-item
2018-12-26 11:10:36	ga_s2am_ard_3-2-1_52LGM_2018-12-26_final.stac-item
2019-03-11 10:26:31	ga_s2am_ard_3-2-1_53HPC_2019-03-11_final.stac-item
2019-05-24 11:44:56	ga_s2am_ard_3-2-1_50JRS_2019-05-24_final.stac-item
2019-06-02 10:34:28	ga_s2am_ard_3-2-1_53JNM_2019-06-02_final.stac-item
2019-06-26 11:56:09	ga_s2am_ard_3-2-1_50JNM_2019-06-26_final.stac-item
2019-07-28 10:55:50	ga_s2am_ard_3-2-1_52JFM_2019-07-28_final.stac-item
2019-09-19 11:06:10	ga_s2am_ard_3-2-1_52JBL_2019-09-19_final.stac-item
2019-12-01 11:11:29	ga_s2am_ard_3-2-1_52LFJ_2019-12-01_final.stac-item
2020-01-03 11:23:16	ga_s2am_ard_3-2-1_51KZS_2020-01-03_final.stac-item
2020-01-03 11:25:33	ga_s2am_ard_3-2-1_51JXH_2020-01-03_final.stac-item
2020-01-10 11:14:50	ga_s2am_ard_3-2-1_51JYL_2020-01-10_final.stac-item
2020-01-11 10:45:17	ga_s2am_ard_3-2-1_53JMH_2020-01-11_final.stac-item
2020-02-02 11:21:45	ga_s2am_ard_3-2-1_52LBH_2020-02-02_final.stac-item
2020-03-07 11:06:02	ga_s2am_ard_3-2-1_52JCL_2020-03-07_final.stac-item
2020-03-23 11:26:11	ga_s2am_ard_3-2-1_51JVF_2020-03-23_final.stac-item
2020-04-06 11:05:28	ga_s2am_ard_3-2-1_52JEN_2020-04-06_final.stac-item
2020-05-30 10:45:10	ga_s2am_ard_3-2-1_53JNJ_2020-05-30_final.stac-item
2020-06-13 10:26:53	ga_s2am_ard_3-2-1_53HQB_2020-06-13_final.stac-item
2020-07-15 11:06:42	ga_s2am_ard_3-2-1_51HYD_2020-07-15_final.stac-item
2020-08-13 11:37:03	ga_s2am_ard_3-2-1_51HUC_2020-08-13_final.stac-item
2020-10-14 10:37:04	ga_s2am_ard_3-2-1_53HPA_2020-10-14_final.stac-item
2020-12-11 11:33:05	ga_s2am_ard_3-2-1_51KXT_2020-12-11_final.stac-item
2020-12-21 11:32:45	ga_s2am_ard_3-2-1_51KVV_2020-12-21_final.stac-item
2021-01-11 11:06:00	ga_s2am_ard_3-2-1_52JEL_2021-01-11_final.stac-item
2021-01-24 11:15:37	ga_s2am_ard_3-2-1_52JBN_2021-01-24_final.stac-item
2021-02-04 10:46:24	ga_s2am_ard_3-2-1_53HLD_2021-02-04_final.stac-item
2021-02-16 11:25:19	ga_s2am_ard_3-2-1_51JYJ_2021-02-16_final.stac-item
2021-03-02 11:00:30	ga_s2am_ard_3-2-1_52LHN_2021-03-02_final.stac-item
2021-03-22 11:02:32	ga_s2am_ard_3-2-1_52KFE_2021-03-22_final.stac-item
2021-04-06 11:56:36	ga_s2am_ard_3-2-1_50HLK_2021-04-06_final.stac-item
2021-06-28 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-06-28_final.stac-item
2021-08-12 11:16:46	ga_s2am_ard_3-2-1_51HWD_2021-08-12_final.stac-item
2021-10-20 11:46:31	ga_s2am_ard_3-2-1_50JML_2021-10-20_final.stac-item
2021-10-20 11:47:15	ga_s2am_ard_3-2-1_50HMH_2021-10-20_final.stac-item
2022-01-16 11:03:28	ga_s2am_ard_3-2-1_52KGA_2022-01-16_final.stac-item
2022-05-01 11:53:55	ga_s2am_ard_3-2-1_50KPA_2022-05-01_final.stac-item
2022-06-02 10:55:13	ga_s2am_ard_3-2-1_53JLJ_2022-06-02_final.stac-item
2022-06-11 11:22:51	ga_s2am_ard_3-2-1_51KYV_2022-06-11_final.stac-item
2022-06-21 11:22:11	ga_s2am_ard_3-2-1_51LYC_2022-06-21_final.stac-item
2022-07-02 10:55:37	ga_s2am_ard_3-2-1_53JKH_2022-07-02_final.stac-item
2022-07-14 11:36:30	ga_s2am_ard_3-2-1_51JTF_2022-07-14_final.stac-item
2022-07-17 11:46:50	ga_s2am_ard_3-2-1_50HNK_2022-07-17_final.stac-item
2022-08-22 10:26:45	ga_s2am_ard_3-2-1_53HQC_2022-08-22_final.stac-item
2022-08-25 10:36:23	ga_s2am_ard_3-2-1_53HME_2022-08-25_final.stac-item
2022-09-02 11:34:48	ga_s2am_ard_3-2-1_51JTN_2022-09-02_final.stac-item
2022-10-06 11:15:58	ga_s2am_ard_3-2-1_52JBM_2022-10-06_final.stac-item
2022-12-28 11:21:31	ga_s2am_ard_3-2-1_52LDJ_2022-12-28_final.stac-item
2023-01-20 11:33:25	ga_s2am_ard_3-2-1_51KVS_2023-01-20_final.stac-item
2023-02-23 11:10:22	ga_s2am_ard_3-2-1_52LHN_2023-02-23_final
2023-02-23 11:12:03	ga_s2am_ard_3-2-1_52KDG_2023-02-23_final
2023-03-29 10:54:39	ga_s2am_ard_3-2-1_53JKL_2023-03-29_final
2023-04-02 12:14:30	ga_s2am_ard_3-2-1_49KFP_2023-04-02_nrt
2023-05-03 11:43:12	ga_s2am_ard_3-2-1_51KVT_2023-05-03_final
2023-05-06 11:55:59	ga_s2am_ard_3-2-1_50JKN_2023-05-06_final
2023-05-14 11:16:37	ga_s2am_ard_3-2-1_51HYD_2023-05-14_final
2023-05-20 11:35:58	ga_s2am_ard_3-2-1_51JVG_2023-05-20_final
2023-06-18 12:03:37	ga_s2am_ard_3-2-1_50KNB_2023-06-18_final
2023-06-21 10:34:29	ga_s2am_ard_3-2-1_53JNM_2023-06-21_final
2023-06-27 10:54:41	ga_s2am_ard_3-2-1_53JLL_2023-06-27_final
2023-06-27 10:54:59	ga_s2am_ard_3-2-1_53JKK_2023-06-27_final
2023-07-01 10:35:28	ga_s2am_ard_3-2-1_53JNH_2023-07-01_final
2023-07-19 11:33:06	ga_s2am_ard_3-2-1_51KYT_2023-07-19_final
2023-07-26 11:25:36	ga_s2am_ard_3-2-1_51JVJ_2023-07-26_final
2023-08-02 11:15:35	ga_s2am_ard_3-2-1_51JXJ_2023-08-02_final
2023-08-08 11:36:31	ga_s2am_ard_3-2-1_50JPL_2023-08-08_final
2023-11-13 11:25:23	ga_s2am_ard_3-2-1_51JXJ_2023-11-13_final
2023-12-24 10:53:11	ga_s2am_ard_3-2-1_52KHB_2023-12-24_final
2024-01-09 11:11:08	ga_s2am_ard_3-2-1_52LGK_2024-01-09_final
2024-03-06 11:06:07	ga_s2am_ard_3-2-1_52JCL_2024-03-06_final
2024-03-15 11:34:43	ga_s2am_ard_3-2-1_51JVM_2024-03-15_final
2024-03-15 11:36:37	ga_s2am_ard_3-2-1_50HPK_2024-03-15_final
2024-03-16 11:00:45	ga_s2am_ard_3-2-1_52LHM_2024-03-16_final
2024-04-30 10:16:57	ga_s2am_ard_3-2-1_53HQB_2024-04-30_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