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_49JGL_2015-12-17_final.stac-item
2016-01-26 12:05:20	ga_s2am_ard_3-2-1_49JGK_2016-01-26_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50JQL_2016-04-19_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50KMC_2016-05-15_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_50KKA_2016-10-05_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50JLT_2017-05-10_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50JKP_2017-06-19_final.stac-item
2017-06-26 11:49:44	ga_s2am_ard_3-2-1_50KQC_2017-06-26_final.stac-item
2017-08-19 11:30:19	ga_s2am_ard_3-2-1_50JPL_2017-08-19_final.stac-item
2017-10-18 11:36:29	ga_s2am_ard_3-2-1_51HUC_2017-10-18_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_49JGL_2017-11-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KNC_2018-01-12_final.stac-item
2018-01-15 12:03:40	ga_s2am_ard_3-2-1_49KHR_2018-01-15_final.stac-item
2018-01-25 12:04:03	ga_s2am_ard_3-2-1_49JGK_2018-01-25_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50KKB_2018-03-26_final.stac-item
2018-04-06 11:31:45	ga_s2am_ard_3-2-1_51HUC_2018-04-06_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JLM_2018-05-25_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JLS_2018-07-04_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HPH_2018-09-06_final.stac-item
2018-11-05 11:45:30	ga_s2am_ard_3-2-1_50HPK_2018-11-05_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_50KKU_2018-11-11_final.stac-item
2018-11-18 11:53:11	ga_s2am_ard_3-2-1_50KQC_2018-11-18_final.stac-item
2018-12-05 11:46:35	ga_s2am_ard_3-2-1_50HQJ_2018-12-05_final.stac-item
2019-03-08 11:56:24	ga_s2am_ard_3-2-1_50HNK_2019-03-08_final.stac-item
2019-03-14 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-03-14_final.stac-item
2019-03-21 12:05:13	ga_s2am_ard_3-2-1_49JGL_2019-03-21_final.stac-item
2019-03-31 12:04:13	ga_s2am_ard_3-2-1_50KKV_2019-03-31_final.stac-item
2019-06-06 11:55:48	ga_s2am_ard_3-2-1_50JLP_2019-06-06_final.stac-item
2019-06-16 11:57:09	ga_s2am_ard_3-2-1_50HMH_2019-06-16_final.stac-item
2019-07-03 11:46:20	ga_s2am_ard_3-2-1_50JQL_2019-07-03_final.stac-item
2019-09-04 11:56:18	ga_s2am_ard_3-2-1_50JNL_2019-09-04_final.stac-item
2019-09-05 11:26:32	ga_s2am_ard_3-2-1_51HUE_2019-09-05_final.stac-item
2019-09-08 11:36:37	ga_s2am_ard_3-2-1_50HPK_2019-09-08_final.stac-item
2019-09-10 12:13:53	ga_s2am_ard_3-2-1_50KKA_2019-09-10_final.stac-item
2019-10-31 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-10-31_final.stac-item
2019-11-21 11:16:41	ga_s2am_ard_3-2-1_51HXD_2019-11-21_final.stac-item
2019-12-09 12:13:51	ga_s2am_ard_3-2-1_50KKA_2019-12-09_final.stac-item
2019-12-09 12:14:38	ga_s2am_ard_3-2-1_49JGN_2019-12-09_final.stac-item
2019-12-10 11:46:12	ga_s2am_ard_3-2-1_50JQL_2019-12-10_final.stac-item
2019-12-31 11:16:31	ga_s2am_ard_3-2-1_51HYD_2019-12-31_final.stac-item
2020-01-19 11:43:15	ga_s2am_ard_3-2-1_50KQC_2020-01-19_final.stac-item
2020-02-01 11:56:18	ga_s2am_ard_3-2-1_50JLL_2020-02-01_final.stac-item
2020-04-01 11:53:07	ga_s2am_ard_3-2-1_50KRC_2020-04-01_final.stac-item
2020-04-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2020-04-18_final.stac-item
2020-04-21 11:53:43	ga_s2am_ard_3-2-1_50KMB_2020-04-21_final.stac-item
2020-05-04 12:05:01	ga_s2am_ard_3-2-1_50JKS_2020-05-04_final.stac-item
2020-06-17 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-06-17_final.stac-item
2020-07-06 12:15:00	ga_s2am_ard_3-2-1_49JGM_2020-07-06_final.stac-item
2020-08-19 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-08-19_final.stac-item
2020-09-28 11:52:40	ga_s2am_ard_3-2-1_50KQF_2020-09-28_final
2020-10-01 12:04:04	ga_s2am_ard_3-2-1_50KKA_2020-10-01_final.stac-item
2020-10-31 12:05:06	ga_s2am_ard_3-2-1_49JGM_2020-10-31_final.stac-item
2020-11-28 11:26:30	ga_s2am_ard_3-2-1_51HVE_2020-11-28_final.stac-item
2020-11-30 12:03:44	ga_s2am_ard_3-2-1_50KKB_2020-11-30_final.stac-item
2020-12-04 11:46:32	ga_s2am_ard_3-2-1_50HPK_2020-12-04_final.stac-item
2021-01-03 11:45:50	ga_s2am_ard_3-2-1_50JPN_2021-01-03_final.stac-item
2021-01-30 11:37:01	ga_s2am_ard_3-2-1_51HTC_2021-01-30_final.stac-item
2021-02-05 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-02-05_final.stac-item
2021-02-19 11:37:06	ga_s2am_ard_3-2-1_50HPH_2021-02-19_final.stac-item
2021-03-17 11:53:20	ga_s2am_ard_3-2-1_50KPC_2021-03-17_final.stac-item
2021-04-16 11:56:19	ga_s2am_ard_3-2-1_50JLL_2021-04-16_final.stac-item
2021-05-16 11:52:34	ga_s2am_ard_3-2-1_50KQF_2021-05-16_final
2021-05-30 11:37:04	ga_s2am_ard_3-2-1_50HQH_2021-05-30_final.stac-item
2021-07-05 11:53:13	ga_s2am_ard_3-2-1_50KRC_2021-07-05_final.stac-item
2021-07-09 11:37:21	ga_s2am_ard_3-2-1_50HQG_2021-07-09_final
2021-07-25 11:56:21	ga_s2am_ard_3-2-1_50JNL_2021-07-25_final.stac-item
2021-07-28 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-28_final.stac-item
2021-09-09 12:13:40	ga_s2am_ard_3-2-1_49KHS_2021-09-09_final
2021-09-10 11:45:46	ga_s2am_ard_3-2-1_50JQN_2021-09-10_final.stac-item
2021-10-29 12:14:03	ga_s2am_ard_3-2-1_49KGR_2021-10-29_final.stac-item
2021-10-30 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2021-10-30_final.stac-item
2021-12-12 11:53:30	ga_s2am_ard_3-2-1_50KMC_2021-12-12_final.stac-item
2022-01-08 11:44:11	ga_s2am_ard_3-2-1_50KPV_2022-01-08_final.stac-item
2022-01-15 11:37:02	ga_s2am_ard_3-2-1_51HTC_2022-01-15_final.stac-item
2022-02-24 11:36:54	ga_s2am_ard_3-2-1_50HPJ_2022-02-24_final.stac-item
2022-03-22 11:53:14	ga_s2am_ard_3-2-1_50KRC_2022-03-22_final.stac-item
2022-03-22 11:56:02	ga_s2am_ard_3-2-1_50JKN_2022-03-22_final.stac-item
2022-03-29 11:45:56	ga_s2am_ard_3-2-1_50JNN_2022-03-29_final.stac-item
2022-06-23 12:04:11	ga_s2am_ard_3-2-1_50KKA_2022-06-23_final.stac-item
2022-06-23 12:04:41	ga_s2am_ard_3-2-1_49KGP_2022-06-23_final.stac-item
2022-07-20 11:56:16	ga_s2am_ard_3-2-1_50JNM_2022-07-20_final.stac-item
2022-08-06 11:45:08	ga_s2am_ard_3-2-1_51JTL_2022-08-06_final.stac-item
2022-10-01 12:04:06	ga_s2am_ard_3-2-1_49KHR_2022-10-01_final.stac-item
2022-10-31 12:03:37	ga_s2am_ard_3-2-1_50KNB_2022-10-31_final.stac-item
2022-11-14 11:46:18	ga_s2am_ard_3-2-1_50JQL_2022-11-14_final.stac-item
2022-11-17 11:55:04	ga_s2am_ard_3-2-1_50JPR_2022-11-17_final.stac-item
2022-11-18 11:27:03	ga_s2am_ard_3-2-1_51HUC_2022-11-18_final.stac-item
2022-11-20 12:03:42	ga_s2am_ard_3-2-1_50KLB_2022-11-20_final.stac-item
2022-11-24 11:46:25	ga_s2am_ard_3-2-1_50JML_2022-11-24_final.stac-item
2022-12-17 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2022-12-17_final.stac-item
2022-12-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2022-12-20_final.stac-item
2023-01-26 11:55:10	ga_s2am_ard_3-2-1_50JLR_2023-01-26_final.stac-item
2023-02-01 12:13:52	ga_s2am_ard_3-2-1_50KKA_2023-02-01_final.stac-item
2023-02-12 11:47:22	ga_s2am_ard_3-2-1_50HMG_2023-02-12_final
2023-03-30 12:04:11	ga_s2am_ard_3-2-1_50KKV_2023-03-30_final
2023-08-24 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2023-08-24_final
2023-09-03 11:55:21	ga_s2am_ard_3-2-1_50JPQ_2023-09-03_final
2023-12-22 11:53:28	ga_s2am_ard_3-2-1_50KQB_2023-12-22_final
2024-02-03 12:05:22	ga_s2am_ard_3-2-1_50JKQ_2024-02-03_final
2024-02-14 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2024-02-14_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