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
2016-04-06 11:33:21	ga_s2am_ard_3-2-1_51JUK_2016-04-06_final.stac-item
2016-05-08 10:28:07	ga_s2am_ard_3-2-1_54JTT_2016-05-08_final.stac-item
2016-05-24 10:55:20	ga_s2am_ard_3-2-1_52JFN_2016-05-24_final.stac-item
2016-09-01 10:48:19	ga_s2am_ard_3-2-1_53KKP_2016-09-01_final.stac-item
2016-09-22 10:25:59	ga_s2am_ard_3-2-1_53HNB_2016-09-22_final.stac-item
2016-10-12 10:19:54	ga_s2am_ard_3-2-1_54HTJ_2016-10-12_final.stac-item
2016-11-23 10:57:14	ga_s2am_ard_3-2-1_52LHK_2016-11-23_final.stac-item
2017-03-09 11:26:01	ga_s2am_ard_3-2-1_51HUE_2017-03-09_final.stac-item
2017-04-30 10:23:09	ga_s2am_ard_3-2-1_53HNC_2017-04-30_final.stac-item
2017-08-19 11:30:19	ga_s2am_ard_3-2-1_51JTH_2017-08-19_final.stac-item
2017-09-24 11:56:03	ga_s2am_ard_3-2-1_50HLK_2017-09-24_final.stac-item
2018-01-02 10:11:25	ga_s2am_ard_3-2-1_54HUF_2018-01-02_final.stac-item
2018-01-15 10:23:20	ga_s2am_ard_3-2-1_53HQB_2018-01-15_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_52LFJ_2018-02-19_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_52JFL_2018-03-25_final.stac-item
2018-05-07 10:57:18	ga_s2am_ard_3-2-1_52JBL_2018-05-07_final.stac-item
2018-05-28 10:27:09	ga_s2am_ard_3-2-1_53JQL_2018-05-28_final.stac-item
2018-06-02 11:17:00	ga_s2am_ard_3-2-1_51KYS_2018-06-02_final.stac-item
2018-08-23 10:17:05	ga_s2am_ard_3-2-1_54HUK_2018-08-23_final.stac-item
2018-09-11 10:47:22	ga_s2am_ard_3-2-1_52JGP_2018-09-11_final.stac-item
2018-09-30 11:16:55	ga_s2am_ard_3-2-1_51KXQ_2018-09-30_final.stac-item
2018-11-01 10:17:02	ga_s2am_ard_3-2-1_53JQK_2018-11-01_final.stac-item
2019-01-23 12:15:16	ga_s2am_ard_3-2-1_49JGK_2019-01-23_final.stac-item
2019-04-14 11:45:41	ga_s2am_ard_3-2-1_50JNP_2019-04-14_final.stac-item
2019-05-31 11:33:05	ga_s2am_ard_3-2-1_51KYT_2019-05-31_final.stac-item
2019-06-02 10:33:52	ga_s2am_ard_3-2-1_53KQP_2019-06-02_final.stac-item
2019-07-22 10:37:04	ga_s2am_ard_3-2-1_53HPA_2019-07-22_final.stac-item
2019-07-26 11:56:09	ga_s2am_ard_3-2-1_50JNM_2019-07-26_final.stac-item
2019-08-09 11:33:13	ga_s2am_ard_3-2-1_51KXT_2019-08-09_final.stac-item
2019-08-31 10:36:59	ga_s2am_ard_3-2-1_53HPA_2019-08-31_final.stac-item
2019-09-01 10:07:01	ga_s2am_ard_3-2-1_54HVF_2019-09-01_final.stac-item
2020-01-11 10:44:59	ga_s2am_ard_3-2-1_53JNJ_2020-01-11_final.stac-item
2020-01-23 11:21:17	ga_s2am_ard_3-2-1_52LBK_2020-01-23_final.stac-item
2020-03-17 11:05:41	ga_s2am_ard_3-2-1_52JEM_2020-03-17_final.stac-item
2020-05-16 11:03:19	ga_s2am_ard_3-2-1_52KEB_2020-05-16_final.stac-item
2020-05-22 11:23:19	ga_s2am_ard_3-2-1_51KXT_2020-05-22_final.stac-item
2020-05-24 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-05-24_final.stac-item
2020-06-01 11:24:12	ga_s2am_ard_3-2-1_52KBU_2020-06-01_final.stac-item
2020-06-22 10:55:40	ga_s2am_ard_3-2-1_52JEN_2020-06-22_final.stac-item
2020-06-28 11:13:59	ga_s2am_ard_3-2-1_51KZQ_2020-06-28_final.stac-item
2020-07-04 11:31:53	ga_s2am_ard_3-2-1_51LZC_2020-07-04_final.stac-item
2020-07-24 11:33:09	ga_s2am_ard_3-2-1_51KWU_2020-07-24_final.stac-item
2020-07-31 11:23:12	ga_s2am_ard_3-2-1_52KBC_2020-07-31_final.stac-item
2020-08-23 11:35:43	ga_s2am_ard_3-2-1_50JQP_2020-08-23_final.stac-item
2020-09-29 11:23:19	ga_s2am_ard_3-2-1_51KXT_2020-09-29_final.stac-item
2020-10-22 11:36:48	ga_s2am_ard_3-2-1_51HUD_2020-10-22_final.stac-item
2020-11-14 11:46:33	ga_s2am_ard_3-2-1_50HQK_2020-11-14_final.stac-item
2020-12-03 10:35:08	ga_s2am_ard_3-2-1_53JNJ_2020-12-03_final.stac-item
2020-12-25 11:11:26	ga_s2am_ard_3-2-1_52LGJ_2020-12-25_final.stac-item
2020-12-28 11:23:28	ga_s2am_ard_3-2-1_51KXS_2020-12-28_final.stac-item
2021-01-22 10:34:04	ga_s2am_ard_3-2-1_53JQN_2021-01-22_final.stac-item
2021-02-12 11:43:50	ga_s2am_ard_3-2-1_50KQA_2021-02-12_final.stac-item
2021-02-19 11:33:23	ga_s2am_ard_3-2-1_51KXS_2021-02-19_final.stac-item
2021-03-22 11:03:55	ga_s2am_ard_3-2-1_52KGU_2021-03-22_final.stac-item
2021-06-14 10:45:12	ga_s2am_ard_3-2-1_53JLJ_2021-06-14_final.stac-item
2021-06-14 10:45:14	ga_s2am_ard_3-2-1_53JKJ_2021-06-14_final.stac-item
2021-08-20 10:33:55	ga_s2am_ard_3-2-1_53KPP_2021-08-20_final.stac-item
2021-08-23 10:44:23	ga_s2am_ard_3-2-1_53JNM_2021-08-23_final.stac-item
2021-09-02 10:45:45	ga_s2am_ard_3-2-1_53JKG_2021-09-02_final.stac-item
2021-09-11 11:16:08	ga_s2am_ard_3-2-1_51JYF_2021-09-11_final.stac-item
2021-09-29 10:33:57	ga_s2am_ard_3-2-1_53KPP_2021-09-29_final.stac-item
2021-10-20 11:46:46	ga_s2am_ard_3-2-1_50HMK_2021-10-20_final.stac-item
2021-11-07 11:03:20	ga_s2am_ard_3-2-1_52KFB_2021-11-07_final.stac-item
2022-01-24 10:24:19	ga_s2am_ard_3-2-1_53JRM_2022-01-24_final.stac-item
2022-01-29 11:12:14	ga_s2am_ard_3-2-1_52KFF_2022-01-29_final.stac-item
2022-02-11 09:48:08	ga_s2am_ard_3-2-1_54GYA_2022-02-11_final.stac-item
2022-04-28 11:43:30	ga_s2am_ard_3-2-1_51KVS_2022-04-28_final.stac-item
2022-05-18 11:44:43	ga_s2am_ard_3-2-1_50JPT_2022-05-18_final.stac-item
2022-06-10 11:53:45	ga_s2am_ard_3-2-1_50KPB_2022-06-10_final.stac-item
2022-08-05 10:34:11	ga_s2am_ard_3-2-1_53JRN_2022-08-05_final.stac-item
2022-08-30 11:24:02	ga_s2am_ard_3-2-1_51KZQ_2022-08-30_final.stac-item
2022-09-16 11:16:15	ga_s2am_ard_3-2-1_52JBL_2022-09-16_final.stac-item
2022-10-31 10:24:52	ga_s2am_ard_3-2-1_54JTQ_2022-10-31_final.stac-item
2022-12-21 11:32:56	ga_s2am_ard_3-2-1_51KWU_2022-12-21_final.stac-item
2022-12-31 11:33:12	ga_s2am_ard_3-2-1_51KWT_2022-12-31_final.stac-item
2023-01-05 10:43:10	ga_s2am_ard_3-2-1_53KMS_2023-01-05_final.stac-item
2023-01-08 10:55:01	ga_s2am_ard_3-2-1_52JFQ_2023-01-08_final.stac-item
2023-01-10 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-01-10_final.stac-item
2023-02-20 11:02:31	ga_s2am_ard_3-2-1_52KFE_2023-02-20_final
2023-03-06 10:42:43	ga_s2am_ard_3-2-1_53KQT_2023-03-06_final
2023-04-02 10:34:35	ga_s2am_ard_3-2-1_53JPL_2023-04-02_final
2023-04-05 10:43:48	ga_s2am_ard_3-2-1_53KPP_2023-04-05_final
2023-04-13 11:47:14	ga_s2am_ard_3-2-1_50HLH_2023-04-13_final
2023-04-15 10:46:06	ga_s2am_ard_3-2-1_53HME_2023-04-15_final
2023-04-23 10:07:36	ga_s2am_ard_3-2-1_54HXC_2023-04-23_final
2023-06-10 11:06:37	ga_s2am_ard_3-2-1_52HBJ_2023-06-10_final
2023-06-27 10:53:50	ga_s2am_ard_3-2-1_52KGV_2023-06-27_final
2023-08-12 11:15:56	ga_s2am_ard_3-2-1_52JBM_2023-08-12_final
2023-09-10 11:46:46	ga_s2am_ard_3-2-1_50HMK_2023-09-10_final
2023-12-01 10:43:58	ga_s2am_ard_3-2-1_53JNN_2023-12-01_final
2023-12-10 11:12:23	ga_s2am_ard_3-2-1_52KFE_2023-12-10_final
2023-12-28 10:34:04	ga_s2am_ard_3-2-1_53JPN_2023-12-28_final
2024-01-05 11:36:07	ga_s2am_ard_3-2-1_51JVF_2024-01-05_final
2024-01-15 11:35:15	ga_s2am_ard_3-2-1_51JUJ_2024-01-15_final
2024-03-06 11:02:16	ga_s2am_ard_3-2-1_52KGF_2024-03-06_final
2024-03-09 11:12:47	ga_s2am_ard_3-2-1_52KED_2024-03-09_final
2024-03-11 11:55:50	ga_s2am_ard_3-2-1_50JNN_2024-03-11_final
2024-03-15 11:36:34	ga_s2am_ard_3-2-1_50HQK_2024-03-15_final
2024-03-16 11:05:52	ga_s2am_ard_3-2-1_52JCM_2024-03-16_final
2024-05-10 10:16:03	ga_s2am_ard_3-2-1_54HWK_2024-05-10_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