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
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_50KKA_2016-08-13_final.stac-item
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_50KKV_2016-08-13_final.stac-item
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_49KHQ_2016-08-13_final.stac-item
2016-08-13 12:03:51	ga_s2am_ard_3-2-1_49KHR_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKQ_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKR_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKS_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKT_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_49JHM_2016-08-13_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_49JHN_2016-08-13_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JKM_2016-08-20_final.stac-item
2016-08-23 12:05:55	ga_s2am_ard_3-2-1_50JKM_2016-08-23_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_50KKA_2016-09-02_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_50KKV_2016-09-02_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2016-09-02_final.stac-item
2016-09-02 12:03:47	ga_s2am_ard_3-2-1_49KHR_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKQ_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKR_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKS_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JKT_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JHM_2016-09-02_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_49JHN_2016-09-02_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JKM_2016-09-09_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50HLH_2018-08-10_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKM_2018-08-10_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKN_2018-08-10_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JKP_2018-08-10_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKM_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKN_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKP_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKQ_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKR_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKS_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKT_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50KKA_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50KKB_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50KKU_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50KKV_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHM_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JHN_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHP_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KHR_2018-08-23_final.stac-item
2018-12-28 11:56:07	ga_s2am_ard_3-2-1_50JKM_2018-12-28_final.stac-item
2018-12-28 11:56:48	ga_s2am_ard_3-2-1_50HLJ_2018-12-28_final.stac-item
2018-12-28 11:57:02	ga_s2am_ard_3-2-1_50HLH_2018-12-28_final.stac-item
2018-12-31 12:05:05	ga_s2am_ard_3-2-1_50JKR_2018-12-31_final.stac-item
2018-12-31 12:05:20	ga_s2am_ard_3-2-1_50JKQ_2018-12-31_final.stac-item
2018-12-31 12:05:34	ga_s2am_ard_3-2-1_50JKP_2018-12-31_final.stac-item
2018-12-31 12:05:49	ga_s2am_ard_3-2-1_50JKN_2018-12-31_final.stac-item
2018-12-31 12:06:03	ga_s2am_ard_3-2-1_50JKM_2018-12-31_final.stac-item
2019-04-07 11:55:47	ga_s2am_ard_3-2-1_50JKP_2019-04-07_final.stac-item
2019-04-07 11:56:01	ga_s2am_ard_3-2-1_50JKN_2019-04-07_final.stac-item
2019-04-07 11:56:15	ga_s2am_ard_3-2-1_50JKM_2019-04-07_final.stac-item
2019-04-07 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2019-04-07_final.stac-item
2019-04-07 11:57:10	ga_s2am_ard_3-2-1_50HLH_2019-04-07_final.stac-item
2019-04-10 12:03:46	ga_s2am_ard_3-2-1_50KKB_2019-04-10_final.stac-item
2019-04-10 12:04:00	ga_s2am_ard_3-2-1_50KKA_2019-04-10_final.stac-item
2019-04-10 12:04:01	ga_s2am_ard_3-2-1_49KHR_2019-04-10_final.stac-item
2019-04-10 12:04:06	ga_s2am_ard_3-2-1_50KKA_2019-04-10_final.stac-item
2019-04-10 12:04:06	ga_s2am_ard_3-2-1_49KHR_2019-04-10_final.stac-item
2019-04-10 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2019-04-10_final.stac-item
2019-04-10 12:04:08	ga_s2am_ard_3-2-1_50KKV_2019-04-10_final.stac-item
2019-04-10 12:04:15	ga_s2am_ard_3-2-1_50KKV_2019-04-10_final.stac-item
2019-04-10 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2019-04-10_final.stac-item
2019-04-10 12:04:29	ga_s2am_ard_3-2-1_49KHP_2019-04-10_final.stac-item
2019-04-10 12:04:29	ga_s2am_ard_3-2-1_50KKU_2019-04-10_final.stac-item
2019-07-26 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-07-26_final.stac-item
2019-07-26 11:56:19	ga_s2am_ard_3-2-1_50JKM_2019-07-26_final.stac-item
2019-07-26 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2019-07-26_final.stac-item
2019-07-26 11:57:14	ga_s2am_ard_3-2-1_50HLH_2019-07-26_final.stac-item
2019-08-05 11:57:13	ga_s2am_ard_3-2-1_50HLH_2019-08-05_final.stac-item
2023-02-11 12:13:28	ga_s2am_ard_3-2-1_50KKC_2023-02-11_nrt.stac-item
2023-02-11 12:13:28	ga_s2am_ard_3-2-1_49KHT_2023-02-11_nrt.stac-item
2023-02-18 12:03:11	ga_s2am_ard_3-2-1_50KKD_2023-02-18_nrt.stac-item
2023-02-18 12:03:14	ga_s2am_ard_3-2-1_49KHU_2023-02-18_nrt.stac-item
2023-02-18 12:03:26	ga_s2am_ard_3-2-1_50KKC_2023-02-18_final
2023-02-18 12:03:27	ga_s2am_ard_3-2-1_49KHT_2023-02-18_nrt.stac-item
2023-02-18 12:03:41	ga_s2am_ard_3-2-1_50KKB_2023-02-18_nrt.stac-item
2023-02-18 12:03:41	ga_s2am_ard_3-2-1_50KKB_2023-02-18_final
2023-02-18 12:03:41	ga_s2am_ard_3-2-1_49KHS_2023-02-18_final
2023-02-18 12:03:55	ga_s2am_ard_3-2-1_50KKA_2023-02-18_nrt.stac-item
2023-02-18 12:03:55	ga_s2am_ard_3-2-1_50KKA_2023-02-18_final
2023-02-18 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-02-18_nrt.stac-item
2023-02-18 12:03:56	ga_s2am_ard_3-2-1_49KHR_2023-02-18_final
2023-02-18 12:04:10	ga_s2am_ard_3-2-1_50KKV_2023-02-18_nrt.stac-item
2023-02-18 12:04:10	ga_s2am_ard_3-2-1_50KKV_2023-02-18_final
2023-02-18 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2023-02-18_nrt.stac-item
2023-02-18 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2023-02-18_final
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_49KHP_2023-02-18_nrt.stac-item
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_49KHP_2023-02-18_final
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_50KKU_2023-02-18_nrt.stac-item
2023-02-18 12:04:25	ga_s2am_ard_3-2-1_50KKU_2023-02-18_final
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_nrt.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_final
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_50JKT_2023-02-18_nrt.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_50JKT_2023-02-18_final
2023-02-18 12:04:53	ga_s2am_ard_3-2-1_49JHM_2023-02-18_nrt.stac-item
2023-02-18 12:04:53	ga_s2am_ard_3-2-1_49JHM_2023-02-18_final
2023-02-18 12:04:54	ga_s2am_ard_3-2-1_50JKS_2023-02-18_nrt.stac-item

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

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