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
2015-09-19 11:36:06	ga_s2am_ard_3-2-1_51HVE_2015-09-19_final.stac-item
2015-12-04 11:57:46	ga_s2am_ard_3-2-1_50LRL_2015-12-04_final
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLQ_2016-04-02_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50KKB_2016-05-15_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HNG_2016-05-16_final
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLT_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50KPC_2016-05-22_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51HUD_2016-05-23_final.stac-item
2016-05-25 12:03:53	ga_s2am_ard_3-2-1_49KHR_2016-05-25_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51HTE_2016-10-03_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50JNR_2017-02-13_final.stac-item
2017-05-27 11:56:10	ga_s2am_ard_3-2-1_50JNL_2017-05-27_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JFM_2017-06-02_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HPK_2017-07-03_final.stac-item
2017-08-19 11:36:41	ga_s2am_ard_3-2-1_51HUD_2017-08-19_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50JMM_2017-09-21_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JLL_2017-12-03_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KNC_2018-01-12_final.stac-item
2018-02-08 11:45:59	ga_s2am_ard_3-2-1_50HNJ_2018-02-08_final.stac-item
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-02-24_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_50JPL_2018-02-25_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50KMC_2018-03-26_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50KKB_2018-04-15_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLN_2018-05-02_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51JTG_2018-06-05_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHR_2018-08-06_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50KRC_2018-08-20_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JGM_2018-09-05_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HPH_2018-09-06_final.stac-item
2018-11-15 11:47:09	ga_s2am_ard_3-2-1_50HLH_2018-11-15_final.stac-item
2018-11-19 11:26:37	ga_s2am_ard_3-2-1_51HVD_2018-11-19_final.stac-item
2019-02-07 11:26:55	ga_s2am_ard_3-2-1_51HVC_2019-02-07_final.stac-item
2019-03-08 11:53:05	ga_s2am_ard_3-2-1_50KRC_2019-03-08_final.stac-item
2019-07-09 12:04:04	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-10 11:37:12	ga_s2am_ard_3-2-1_50HPH_2019-07-10_final.stac-item
2019-08-21 12:13:56	ga_s2am_ard_3-2-1_50KKA_2019-08-21_final.stac-item
2019-11-03 11:53:13	ga_s2am_ard_3-2-1_50KRC_2019-11-03_final.stac-item
2020-01-15 12:03:17	ga_s2am_ard_3-2-1_50KMC_2020-01-15_final.stac-item
2020-04-01 11:57:02	ga_s2am_ard_3-2-1_50HMH_2020-04-01_final.stac-item
2020-04-18 11:46:34	ga_s2am_ard_3-2-1_50HPK_2020-04-18_final.stac-item
2020-04-22 11:26:48	ga_s2am_ard_3-2-1_51HUD_2020-04-22_final.stac-item
2020-04-24 12:04:33	ga_s2am_ard_3-2-1_49KGP_2020-04-24_final.stac-item
2020-05-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-05-25_final.stac-item
2020-06-04 11:37:07	ga_s2am_ard_3-2-1_51HTC_2020-06-04_final.stac-item
2020-08-12 12:04:37	ga_s2am_ard_3-2-1_49KGP_2020-08-12_final.stac-item
2020-08-12 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-08-12_final.stac-item
2020-10-08 11:56:28	ga_s2am_ard_3-2-1_50JML_2020-10-08_final.stac-item
2020-10-08 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-10-08_final.stac-item
2020-11-01 11:36:51	ga_s2am_ard_3-2-1_51HTD_2020-11-01_final.stac-item
2020-11-20 12:04:01	ga_s2am_ard_3-2-1_50KKA_2020-11-20_final.stac-item
2020-12-04 11:44:29	ga_s2am_ard_3-2-1_50JRT_2020-12-04_final.stac-item
2020-12-17 11:57:04	ga_s2am_ard_3-2-1_50HMH_2020-12-17_final.stac-item
2020-12-24 11:47:09	ga_s2am_ard_3-2-1_50HMH_2020-12-24_final.stac-item
2021-01-03 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-01-03_final.stac-item
2021-02-18 12:03:22	ga_s2am_ard_3-2-1_50KMC_2021-02-18_final.stac-item
2021-04-22 12:13:50	ga_s2am_ard_3-2-1_50KKA_2021-04-22_final.stac-item
2021-04-22 12:14:52	ga_s2am_ard_3-2-1_49JGM_2021-04-22_final.stac-item
2021-05-06 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2021-05-06_final.stac-item
2021-05-26 11:53:22	ga_s2am_ard_3-2-1_50KPC_2021-05-26_final.stac-item
2021-06-05 11:53:25	ga_s2am_ard_3-2-1_50KNC_2021-06-05_final.stac-item
2021-06-21 12:14:57	ga_s2am_ard_3-2-1_49JGM_2021-06-21_final.stac-item
2021-07-15 11:56:14	ga_s2am_ard_3-2-1_50JLM_2021-07-15_final.stac-item
2021-07-25 11:53:24	ga_s2am_ard_3-2-1_50KPC_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
2021-08-11 11:47:12	ga_s2am_ard_3-2-1_50HMH_2021-08-11_final.stac-item
2021-08-17 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-08-17_final
2021-08-24 11:53:26	ga_s2am_ard_3-2-1_50KNC_2021-08-24_final.stac-item
2021-09-07 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-09-07_final
2021-09-13 11:52:20	ga_s2am_ard_3-2-1_50KQG_2021-09-13_final
2021-10-13 11:56:05	ga_s2am_ard_3-2-1_50JKN_2021-10-13_final.stac-item
2021-10-21 11:16:49	ga_s2am_ard_3-2-1_51HWD_2021-10-21_final.stac-item
2021-11-15 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-11-15_final.stac-item
2021-12-19 11:43:19	ga_s2am_ard_3-2-1_50KRC_2021-12-19_final.stac-item
2022-01-01 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-01_final.stac-item
2022-01-04 12:06:11	ga_s2am_ard_3-2-1_50JKM_2022-01-04_final.stac-item
2022-02-20 11:56:38	ga_s2am_ard_3-2-1_50HMK_2022-02-20_final.stac-item
2022-02-21 11:26:42	ga_s2am_ard_3-2-1_51HWD_2022-02-21_final.stac-item
2022-03-25 12:03:26	ga_s2am_ard_3-2-1_50KMC_2022-03-25_final.stac-item
2022-04-02 11:26:38	ga_s2am_ard_3-2-1_51HXD_2022-04-02_final.stac-item
2022-06-04 11:37:11	ga_s2am_ard_3-2-1_50HQH_2022-06-04_final.stac-item
2022-11-10 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-11-10_final.stac-item
2023-01-06 11:55:45	ga_s2am_ard_3-2-1_50JKP_2023-01-06_final.stac-item
2023-01-26 11:57:17	ga_s2am_ard_3-2-1_50HMG_2023-01-26_final
2023-02-01 12:14:54	ga_s2am_ard_3-2-1_49JGM_2023-02-01_final.stac-item
2023-02-12 11:47:15	ga_s2am_ard_3-2-1_50HPG_2023-02-12_final
2023-02-28 12:03:56	ga_s2am_ard_3-2-1_50KKA_2023-02-28_final
2023-03-03 12:13:51	ga_s2am_ard_3-2-1_50KKA_2023-03-03_final
2023-04-03 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-04-03_final
2023-04-30 11:37:17	ga_s2am_ard_3-2-1_50HQG_2023-04-30_final
2023-05-09 12:03:44	ga_s2am_ard_3-2-1_49KHS_2023-05-09_final
2023-05-09 12:05:51	ga_s2am_ard_3-2-1_50JLN_2023-05-09_final
2023-08-08 11:36:33	ga_s2am_ard_3-2-1_51HUE_2023-08-08_final
2023-08-11 11:47:11	ga_s2am_ard_3-2-1_50HNH_2023-08-11_final
2023-10-01 11:17:01	ga_s2am_ard_3-2-1_51HWC_2023-10-01_final
2023-10-03 11:54:53	ga_s2am_ard_3-2-1_50JNS_2023-10-03_final
2023-12-09 11:43:17	ga_s2am_ard_3-2-1_50KQC_2023-12-09_final
2023-12-16 11:36:39	ga_s2am_ard_3-2-1_51HUD_2023-12-16_final
2024-02-16 12:14:25	ga_s2am_ard_3-2-1_49KGP_2024-02-16_final
2024-05-04 11:37:04	ga_s2am_ard_3-2-1_51HTC_2024-05-04_final
2024-05-08 11:17:01	ga_s2am_ard_3-2-1_51HWC_2024-05-08_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