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
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_51HTD_2015-12-08_final.stac-item
2016-04-10 11:07:07	ga_s2am_ard_3-2-1_51KZS_2016-04-10_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51KYR_2016-11-29_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUS_2016-12-22_final.stac-item
2016-12-23 11:02:53	ga_s2am_ard_3-2-1_52JCP_2016-12-23_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50JQM_2016-12-25_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50KMC_2017-01-20_final.stac-item
2017-02-10 11:26:14	ga_s2am_ard_3-2-1_51KXB_2017-02-10_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_51KUR_2017-03-25_final.stac-item
2017-04-08 11:20:55	ga_s2am_ard_3-2-1_51KWP_2017-04-08_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JML_2017-05-04_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_50KKA_2017-07-12_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_49KHP_2017-10-07_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KQV_2018-01-12_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_51KXV_2018-01-26_final.stac-item
2018-04-12 11:47:43	ga_s2am_ard_3-2-1_50KQC_2018-04-12_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51KYU_2018-05-06_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_50KKA_2018-05-08_final.stac-item
2018-07-05 11:29:39	ga_s2am_ard_3-2-1_51KXV_2018-07-05_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKS_2018-07-14_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HLK_2018-07-21_final.stac-item
2018-07-31 11:53:40	ga_s2am_ard_3-2-1_50HLH_2018-07-31_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_51LUF_2018-08-07_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51KUT_2018-09-03_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51KZR_2018-09-10_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYS_2018-10-10_final.stac-item
2018-10-10 11:16:56	ga_s2am_ard_3-2-1_51KYU_2018-10-10_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_50KKA_2018-10-15_final.stac-item
2018-10-20 11:16:56	ga_s2am_ard_3-2-1_51KZQ_2018-10-20_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52JDQ_2018-10-24_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KTU_2018-10-26_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KZP_2018-10-30_final.stac-item
2018-12-12 11:36:20	ga_s2am_ard_3-2-1_51HUE_2018-12-12_final.stac-item
2018-12-19 11:26:59	ga_s2am_ard_3-2-1_51HTC_2018-12-19_final.stac-item
2019-04-13 12:14:58	ga_s2am_ard_3-2-1_49JGM_2019-04-13_final.stac-item
2019-04-20 12:03:19	ga_s2am_ard_3-2-1_50KMC_2019-04-20_final.stac-item
2019-06-13 11:44:05	ga_s2am_ard_3-2-1_50KRV_2019-06-13_final.stac-item
2019-06-24 11:14:27	ga_s2am_ard_3-2-1_51JZN_2019-06-24_final.stac-item
2019-07-20 11:32:52	ga_s2am_ard_3-2-1_51KVV_2019-07-20_final.stac-item
2019-08-01 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-08-01_final.stac-item
2019-08-22 11:42:44	ga_s2am_ard_3-2-1_51KVV_2019-08-22_final.stac-item
2019-09-02 11:14:21	ga_s2am_ard_3-2-1_52JCT_2019-09-02_final.stac-item
2019-09-15 11:23:42	ga_s2am_ard_3-2-1_51KXR_2019-09-15_final.stac-item
2019-10-01 11:42:58	ga_s2am_ard_3-2-1_51KVU_2019-10-01_final.stac-item
2019-10-24 11:54:34	ga_s2am_ard_3-2-1_50KMU_2019-10-24_final.stac-item
2019-11-07 11:34:17	ga_s2am_ard_3-2-1_51KVP_2019-11-07_final.stac-item
2019-12-17 11:32:20	ga_s2am_ard_3-2-1_51KXA_2019-12-17_final.stac-item
2020-01-30 11:15:11	ga_s2am_ard_3-2-1_52JCP_2020-01-30_final.stac-item
2020-03-03 11:21:21	ga_s2am_ard_3-2-1_51LZE_2020-03-03_final.stac-item
2020-03-13 11:22:48	ga_s2am_ard_3-2-1_51KZU_2020-03-13_final.stac-item
2020-03-15 12:04:45	ga_s2am_ard_3-2-1_50JMS_2020-03-15_final.stac-item
2020-06-26 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-06-26_final.stac-item
2020-09-06 11:14:25	ga_s2am_ard_3-2-1_52JCT_2020-09-06_final.stac-item
2020-10-15 11:42:33	ga_s2am_ard_3-2-1_51KVA_2020-10-15_final.stac-item
2020-10-28 11:57:14	ga_s2am_ard_3-2-1_50HLH_2020-10-28_final.stac-item
2021-01-13 11:41:34	ga_s2am_ard_3-2-1_51LUE_2021-01-13_final.stac-item
2021-01-14 11:15:08	ga_s2am_ard_3-2-1_52JBQ_2021-01-14_final.stac-item
2021-01-17 11:23:50	ga_s2am_ard_3-2-1_51KZQ_2021-01-17_final.stac-item
2021-03-14 11:41:55	ga_s2am_ard_3-2-1_51LWC_2021-03-14_final.stac-item
2021-03-28 11:24:17	ga_s2am_ard_3-2-1_51JZN_2021-03-28_final.stac-item
2021-04-27 11:26:40	ga_s2am_ard_3-2-1_51HVD_2021-04-27_final.stac-item
2021-06-05 11:53:32	ga_s2am_ard_3-2-1_50KMC_2021-06-05_final.stac-item
2021-07-28 12:05:00	ga_s2am_ard_3-2-1_49JHM_2021-07-28_final.stac-item
2021-07-29 11:32:23	ga_s2am_ard_3-2-1_51KVB_2021-07-29_final.stac-item
2021-07-29 11:37:14	ga_s2am_ard_3-2-1_50HQG_2021-07-29_final
2021-08-15 11:24:21	ga_s2am_ard_3-2-1_51JZN_2021-08-15_final.stac-item
2021-11-06 11:32:50	ga_s2am_ard_3-2-1_51KVV_2021-11-06_final.stac-item
2021-11-19 11:43:58	ga_s2am_ard_3-2-1_51KUQ_2021-11-19_final.stac-item
2022-01-25 11:32:15	ga_s2am_ard_3-2-1_51KWB_2022-01-25_final.stac-item
2022-02-14 11:33:09	ga_s2am_ard_3-2-1_51KXT_2022-02-14_final.stac-item
2022-03-02 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-03-02_final.stac-item
2022-03-16 11:33:26	ga_s2am_ard_3-2-1_51KUT_2022-03-16_final.stac-item
2022-07-17 11:44:10	ga_s2am_ard_3-2-1_51KUQ_2022-07-17_final.stac-item
2022-08-09 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-08-09_final.stac-item
2022-08-19 11:53:34	ga_s2am_ard_3-2-1_50KPC_2022-08-19_final.stac-item
2022-11-05 11:14:27	ga_s2am_ard_3-2-1_52JBT_2022-11-05_final.stac-item
2022-11-18 11:22:54	ga_s2am_ard_3-2-1_51KZU_2022-11-18_final.stac-item
2022-11-28 11:22:26	ga_s2am_ard_3-2-1_51KYA_2022-11-28_final.stac-item
2022-12-05 11:14:50	ga_s2am_ard_3-2-1_52JCR_2022-12-05_final.stac-item
2022-12-21 11:32:38	ga_s2am_ard_3-2-1_51KXV_2022-12-21_final.stac-item
2023-01-03 11:41:32	ga_s2am_ard_3-2-1_51LUE_2023-01-03_final.stac-item
2023-01-23 11:43:14	ga_s2am_ard_3-2-1_51KTT_2023-01-23_final.stac-item
2023-01-23 11:43:14	ga_s2am_ard_3-2-1_50KRC_2023-01-23_final.stac-item
2023-02-06 11:23:12	ga_s2am_ard_3-2-1_51KXT_2023-02-06_final
2023-02-15 11:53:14	ga_s2am_ard_3-2-1_50KQC_2023-02-15_nrt.stac-item
2023-02-16 11:23:10	ga_s2am_ard_3-2-1_51KXT_2023-02-16_final
2023-02-18 12:05:07	ga_s2am_ard_3-2-1_50JKR_2023-02-18_nrt.stac-item
2023-04-29 12:03:23	ga_s2am_ard_3-2-1_50KMC_2023-04-29_final
2023-05-30 11:32:54	ga_s2am_ard_3-2-1_51KYU_2023-05-30_final
2023-07-21 12:13:43	ga_s2am_ard_3-2-1_50KKB_2023-07-21_final
2023-08-14 11:52:25	ga_s2am_ard_3-2-1_50KQG_2023-08-14_final
2023-08-21 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-08-21_final
2023-09-21 11:13:27	ga_s2am_ard_3-2-1_51KZS_2023-09-21_final
2023-10-14 11:22:51	ga_s2am_ard_3-2-1_51KZU_2023-10-14_final
2023-10-23 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-10-23_final
2024-02-04 11:33:44	ga_s2am_ard_3-2-1_51KUR_2024-02-04_final
2024-02-21 11:25:55	ga_s2am_ard_3-2-1_51JWG_2024-02-21_final
2024-02-27 11:41:55	ga_s2am_ard_3-2-1_51LWC_2024-02-27_final
2024-03-05 11:35:13	ga_s2am_ard_3-2-1_51JVK_2024-03-05_final
2024-03-15 11:33:59	ga_s2am_ard_3-2-1_51KVQ_2024-03-15_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