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
2016-01-31 11:12:11	ga_s2am_ard_3-2-1_52KEA_2016-01-31_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_50KKB_2016-02-08_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_51JTL_2016-03-07_final.stac-item
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_50HPK_2016-04-06_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51JYM_2016-05-30_final.stac-item
2016-05-31 10:38:44	ga_s2am_ard_3-2-1_53JPL_2016-05-31_final.stac-item
2016-08-16 10:28:09	ga_s2am_ard_3-2-1_53JRM_2016-08-16_final.stac-item
2016-09-28 10:38:39	ga_s2am_ard_3-2-1_53KQT_2016-09-28_final.stac-item
2016-11-10 10:52:15	ga_s2am_ard_3-2-1_53KMT_2016-11-10_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51LZC_2016-11-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LWC_2016-12-22_final.stac-item
2016-12-30 10:48:09	ga_s2am_ard_3-2-1_53KKB_2016-12-30_final.stac-item
2017-01-13 10:32:45	ga_s2am_ard_3-2-1_53KPP_2017-01-13_final.stac-item
2017-01-24 11:35:42	ga_s2am_ard_3-2-1_50KQC_2017-01-24_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50JPN_2017-03-25_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50JQR_2017-03-25_final.stac-item
2017-04-06 10:43:05	ga_s2am_ard_3-2-1_53JNN_2017-04-06_final.stac-item
2017-04-19 10:52:17	ga_s2am_ard_3-2-1_52KGV_2017-04-19_final.stac-item
2017-08-20 11:03:00	ga_s2am_ard_3-2-1_52JFM_2017-08-20_final.stac-item
2018-01-27 10:57:11	ga_s2am_ard_3-2-1_52KEC_2018-01-27_final.stac-item
2018-03-19 10:35:43	ga_s2am_ard_3-2-1_53HNC_2018-03-19_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53JLJ_2018-03-25_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_52JGL_2018-10-28_final.stac-item
2018-11-13 11:01:33	ga_s2am_ard_3-2-1_53LLC_2018-11-13_final.stac-item
2018-11-13 11:06:01	ga_s2am_ard_3-2-1_52JCL_2018-11-13_final.stac-item
2019-01-06 10:44:15	ga_s2am_ard_3-2-1_53JNM_2019-01-06_final.stac-item
2019-01-24 11:46:37	ga_s2am_ard_3-2-1_50HMK_2019-01-24_final.stac-item
2019-02-07 11:23:25	ga_s2am_ard_3-2-1_51KXS_2019-02-07_final.stac-item
2019-03-06 11:10:19	ga_s2am_ard_3-2-1_52LHN_2019-03-06_final.stac-item
2019-03-11 10:25:15	ga_s2am_ard_3-2-1_53JQH_2019-03-11_final.stac-item
2019-03-16 11:10:21	ga_s2am_ard_3-2-1_52LHN_2019-03-16_final.stac-item
2019-06-27 11:26:22	ga_s2am_ard_3-2-1_51JUF_2019-06-27_final.stac-item
2019-07-02 10:34:04	ga_s2am_ard_3-2-1_53JRN_2019-07-02_final.stac-item
2019-11-20 11:46:31	ga_s2am_ard_3-2-1_50HQK_2019-11-20_final.stac-item
2019-12-06 12:05:41	ga_s2am_ard_3-2-1_49JGJ_2019-12-06_final.stac-item
2019-12-22 10:44:00	ga_s2am_ard_3-2-1_53JNN_2019-12-22_final.stac-item
2020-01-10 11:15:33	ga_s2am_ard_3-2-1_51JYH_2020-01-10_final.stac-item
2020-01-11 10:40:48	ga_s2am_ard_3-2-1_53LPF_2020-01-11_final.stac-item
2020-02-12 11:22:02	ga_s2am_ard_3-2-1_51KZB_2020-02-12_final.stac-item
2020-02-21 11:55:36	ga_s2am_ard_3-2-1_50JLP_2020-02-21_final.stac-item
2020-04-07 10:33:43	ga_s2am_ard_3-2-1_53KRP_2020-04-07_final.stac-item
2020-04-19 11:16:06	ga_s2am_ard_3-2-1_52JBL_2020-04-19_final.stac-item
2020-05-20 10:43:02	ga_s2am_ard_3-2-1_53KMT_2020-05-20_final.stac-item
2020-05-30 10:45:53	ga_s2am_ard_3-2-1_52JGM_2020-05-30_final.stac-item
2020-06-02 10:56:10	ga_s2am_ard_3-2-1_52JEL_2020-06-02_final.stac-item
2020-07-07 11:42:50	ga_s2am_ard_3-2-1_51KUV_2020-07-07_final.stac-item
2020-09-11 12:03:23	ga_s2am_ard_3-2-1_50KNC_2020-09-11_final.stac-item
2020-09-14 12:15:24	ga_s2am_ard_3-2-1_49JGK_2020-09-14_final.stac-item
2020-11-30 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2020-11-30_final.stac-item
2021-02-04 10:45:14	ga_s2am_ard_3-2-1_53JKJ_2021-02-04_final.stac-item
2021-02-07 10:51:30	ga_s2am_ard_3-2-1_53LPC_2021-02-07_final
2021-02-22 11:42:47	ga_s2am_ard_3-2-1_51KUV_2021-02-22_final.stac-item
2021-03-07 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-03-07_final.stac-item
2021-04-16 11:56:08	ga_s2am_ard_3-2-1_50JKM_2021-04-16_final.stac-item
2021-05-29 10:26:55	ga_s2am_ard_3-2-1_53HNB_2021-05-29_final.stac-item
2021-05-29 12:03:21	ga_s2am_ard_3-2-1_50KNC_2021-05-29_final.stac-item
2021-08-17 10:24:21	ga_s2am_ard_3-2-1_53JRM_2021-08-17_final.stac-item
2021-09-29 10:34:08	ga_s2am_ard_3-2-1_53JQN_2021-09-29_final.stac-item
2021-10-27 11:33:07	ga_s2am_ard_3-2-1_51KYT_2021-10-27_final.stac-item
2022-01-16 11:03:32	ga_s2am_ard_3-2-1_52KFA_2022-01-16_final.stac-item
2022-03-25 12:05:12	ga_s2am_ard_3-2-1_50JLR_2022-03-25_final.stac-item
2022-04-22 11:26:34	ga_s2am_ard_3-2-1_51HVE_2022-04-22_final.stac-item
2022-05-19 11:16:46	ga_s2am_ard_3-2-1_51HXD_2022-05-19_final.stac-item
2022-05-28 11:43:32	ga_s2am_ard_3-2-1_51KVS_2022-05-28_final.stac-item
2022-06-01 11:25:35	ga_s2am_ard_3-2-1_51JWJ_2022-06-01_final.stac-item
2022-06-02 10:55:11	ga_s2am_ard_3-2-1_52JGQ_2022-06-02_final.stac-item
2022-06-17 11:45:25	ga_s2am_ard_3-2-1_51JTK_2022-06-17_final.stac-item
2022-07-23 12:05:55	ga_s2am_ard_3-2-1_49JGJ_2022-07-23_final.stac-item
2022-08-18 10:46:18	ga_s2am_ard_3-2-1_53HME_2022-08-18_final.stac-item
2022-10-22 11:36:59	ga_s2am_ard_3-2-1_51HUC_2022-10-22_final.stac-item
2022-10-29 11:24:47	ga_s2am_ard_3-2-1_52JBR_2022-10-29_final.stac-item
2022-11-20 10:26:47	ga_s2am_ard_3-2-1_53HQB_2022-11-20_final.stac-item
2022-11-22 11:03:09	ga_s2am_ard_3-2-1_52KHB_2022-11-22_final.stac-item
2022-11-23 10:34:34	ga_s2am_ard_3-2-1_53JQL_2022-11-23_final.stac-item
2022-12-25 11:11:14	ga_s2am_ard_3-2-1_52LFK_2022-12-25_final.stac-item
2022-12-29 10:55:21	ga_s2am_ard_3-2-1_52JEP_2022-12-29_final.stac-item
2023-01-28 10:51:29	ga_s2am_ard_3-2-1_53LPC_2023-01-28_final.stac-item
2023-02-02 11:41:57	ga_s2am_ard_3-2-1_51LVC_2023-02-02_final
2023-04-01 11:04:49	ga_s2am_ard_3-2-1_52JDR_2023-04-01_final
2023-04-15 10:45:08	ga_s2am_ard_3-2-1_53JMJ_2023-04-15_final
2023-04-29 10:26:47	ga_s2am_ard_3-2-1_53HQB_2023-04-29_final
2023-05-02 10:34:33	ga_s2am_ard_3-2-1_53JQL_2023-05-02_final
2023-05-20 11:32:22	ga_s2am_ard_3-2-1_51KVB_2023-05-20_final
2023-06-01 10:36:50	ga_s2am_ard_3-2-1_53HPB_2023-06-01_final
2023-06-04 10:44:28	ga_s2am_ard_3-2-1_53JMM_2023-06-04_final
2023-06-10 11:06:37	ga_s2am_ard_3-2-1_52HBJ_2023-06-10_final
2023-06-15 11:57:10	ga_s2am_ard_3-2-1_50HLH_2023-06-15_final
2023-06-29 11:31:22	ga_s2am_ard_3-2-1_52LBK_2023-06-29_final
2023-07-19 11:35:55	ga_s2am_ard_3-2-1_50JQN_2023-07-19_final
2023-07-26 11:26:12	ga_s2am_ard_3-2-1_51JXF_2023-07-26_final
2023-09-03 11:55:18	ga_s2am_ard_3-2-1_50JLR_2023-09-03_final
2023-09-20 11:47:12	ga_s2am_ard_3-2-1_50HMH_2023-09-20_final
2023-10-22 10:43:48	ga_s2am_ard_3-2-1_53KPP_2023-10-22_final
2023-12-18 10:36:28	ga_s2am_ard_3-2-1_53HPC_2023-12-18_final
2023-12-28 10:34:30	ga_s2am_ard_3-2-1_53JQL_2023-12-28_final
2023-12-31 10:43:49	ga_s2am_ard_3-2-1_53KPP_2023-12-31_final
2024-01-09 11:11:11	ga_s2am_ard_3-2-1_52LFK_2024-01-09_final
2024-01-09 11:12:42	ga_s2am_ard_3-2-1_52KED_2024-01-09_final
2024-01-13 10:51:37	ga_s2am_ard_3-2-1_53LLC_2024-01-13_final
2024-03-06 11:01:39	ga_s2am_ard_3-2-1_53LLC_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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