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

68 results

Time (local)	Label
2016-11-19 09:42:43	ga_s2am_ard_3-2-1_55HCS_2016-11-19_final.stac-item
2016-11-19 09:47:39	ga_s2am_ard_3-2-1_55GBR_2016-11-19_final.stac-item
2016-11-20 10:47:23	ga_s2am_ard_3-2-1_53KKV_2016-11-20_final.stac-item
2016-11-20 10:47:23	ga_s2am_ard_3-2-1_53LLE_2016-11-20_final.stac-item
2016-12-08 10:09:14	ga_s2am_ard_3-2-1_54KZC_2016-12-08_final.stac-item
2016-12-09 09:43:25	ga_s2am_ard_3-2-1_55HDU_2016-12-09_final.stac-item
2016-12-09 09:43:25	ga_s2am_ard_3-2-1_55HES_2016-12-09_final.stac-item
2016-12-09 09:43:25	ga_s2am_ard_3-2-1_55JFJ_2016-12-09_final.stac-item
2016-12-09 09:43:25	ga_s2am_ard_3-2-1_55JGM_2016-12-09_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51LZC_2016-12-09_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_52KHB_2016-12-10_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_53KKV_2016-12-10_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_53LLC_2016-12-10_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_52JHS_2016-12-10_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_52KHD_2016-12-10_final.stac-item
2016-12-11 10:20:28	ga_s2am_ard_3-2-1_54JTP_2016-12-11_final.stac-item
2016-12-11 10:25:20	ga_s2am_ard_3-2-1_53HQA_2016-12-11_final.stac-item
2016-12-11 10:25:20	ga_s2am_ard_3-2-1_54JVM_2016-12-11_final.stac-item
2016-12-11 10:25:20	ga_s2am_ard_3-2-1_53HPV_2016-12-11_final.stac-item
2016-12-12 09:51:01	ga_s2am_ard_3-2-1_55JEL_2016-12-12_final.stac-item
2016-12-12 09:55:50	ga_s2am_ard_3-2-1_55HCV_2016-12-12_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_50JRT_2016-12-12_final.stac-item
2016-12-13 11:02:39	ga_s2am_ard_3-2-1_52JCM_2016-12-13_final.stac-item
2016-12-13 11:02:39	ga_s2am_ard_3-2-1_52JCR_2016-12-13_final.stac-item
2016-12-14 10:33:36	ga_s2am_ard_3-2-1_53JQG_2016-12-14_final.stac-item
2016-12-14 10:33:36	ga_s2am_ard_3-2-1_53JQK_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51LVE_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51LWG_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JQS_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51JTL_2016-12-15_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51LUD_2016-12-15_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_51JYF_2016-12-16_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_51HXB_2016-12-16_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_52JBL_2016-12-16_final.stac-item
2016-12-17 10:38:38	ga_s2am_ard_3-2-1_53KPV_2016-12-17_final.stac-item
2016-12-17 10:38:38	ga_s2am_ard_3-2-1_53KQS_2016-12-17_final.stac-item
2016-12-17 10:43:37	ga_s2am_ard_3-2-1_53JKH_2016-12-17_final.stac-item
2016-12-17 10:43:37	ga_s2am_ard_3-2-1_53JMF_2016-12-17_final.stac-item
2016-12-18 10:14:12	ga_s2am_ard_3-2-1_53HQB_2016-12-18_final.stac-item
2016-12-18 10:14:12	ga_s2am_ard_3-2-1_54HTF_2016-12-18_final.stac-item
2016-12-18 10:14:12	ga_s2am_ard_3-2-1_54JXQ_2016-12-18_final.stac-item
2016-12-19 09:43:23	ga_s2am_ard_3-2-1_55HDC_2016-12-19_final.stac-item
2016-12-19 09:43:23	ga_s2am_ard_3-2-1_55HEV_2016-12-19_final.stac-item
2016-12-19 09:43:23	ga_s2am_ard_3-2-1_55HEA_2016-12-19_final.stac-item
2016-12-20 10:52:10	ga_s2am_ard_3-2-1_53KKA_2016-12-20_final.stac-item
2016-12-20 10:52:10	ga_s2am_ard_3-2-1_52KHD_2016-12-20_final.stac-item
2016-12-21 10:26:31	ga_s2am_ard_3-2-1_53HPC_2016-12-21_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVB_2016-12-22_final.stac-item
2016-12-23 10:57:35	ga_s2am_ard_3-2-1_52KHE_2016-12-23_final.stac-item
2016-12-23 10:57:35	ga_s2am_ard_3-2-1_52KHF_2016-12-23_final.stac-item
2016-12-25 10:04:36	ga_s2am_ard_3-2-1_54HXC_2016-12-25_final.stac-item
2016-12-25 10:04:36	ga_s2am_ard_3-2-1_55HCE_2016-12-25_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_51LWG_2016-12-25_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50JQQ_2016-12-25_final.stac-item
2016-12-26 09:32:12	ga_s2am_ard_3-2-1_55HFT_2016-12-26_final.stac-item
2016-12-26 09:37:29	ga_s2am_ard_3-2-1_55GCM_2016-12-26_final.stac-item
2016-12-26 09:37:29	ga_s2am_ard_3-2-1_55HET_2016-12-26_final.stac-item
2016-12-27 10:38:37	ga_s2am_ard_3-2-1_53KPT_2016-12-27_final.stac-item
2016-12-27 10:43:36	ga_s2am_ard_3-2-1_53HLE_2016-12-27_final.stac-item
2016-12-28 10:14:12	ga_s2am_ard_3-2-1_53HQV_2016-12-28_final.stac-item
2016-12-28 10:14:12	ga_s2am_ard_3-2-1_54JUP_2016-12-28_final.stac-item
2016-12-29 09:43:23	ga_s2am_ard_3-2-1_55JGK_2016-12-29_final.stac-item
2016-12-29 09:48:19	ga_s2am_ard_3-2-1_55GCP_2016-12-29_final.stac-item
2016-12-29 11:21:06	ga_s2am_ard_3-2-1_51JYJ_2016-12-29_final.stac-item
2016-12-30 10:48:09	ga_s2am_ard_3-2-1_53LME_2016-12-30_final.stac-item
2016-12-31 10:20:29	ga_s2am_ard_3-2-1_53JPG_2016-12-31_final.stac-item
2016-12-31 10:25:21	ga_s2am_ard_3-2-1_53HQA_2016-12-31_final.stac-item
2016-12-31 10:25:21	ga_s2am_ard_3-2-1_54HTF_2016-12-31_final.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

Other products

All years