Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2023-10-13 11:57:07	ga_s2am_ard_3-2-1_50HLH_2023-10-13_final.stac-item
2023-10-13 11:57:18	ga_s2am_ard_3-2-1_50HMG_2023-10-13_final.stac-item
2023-10-13 11:57:20	ga_s2am_ard_3-2-1_50HLG_2023-10-13_final.stac-item
2023-10-13 11:57:22	ga_s2am_ard_3-2-1_50HKG_2023-10-13_nrt.stac-item
2023-10-14 09:39:33	ga_s2am_ard_3-2-1_56LPP_2023-10-14_nrt.stac-item
2023-10-14 09:39:37	ga_s2am_ard_3-2-1_56LNP_2023-10-14_nrt.stac-item
2023-10-14 09:39:40	ga_s2am_ard_3-2-1_56LMP_2023-10-14_nrt.stac-item
2023-10-14 09:39:47	ga_s2am_ard_3-2-1_56LLP_2023-10-14_nrt.stac-item
2023-10-14 09:41:12	ga_s2am_ard_3-2-1_56LNH_2023-10-14_nrt.stac-item
2023-10-14 09:41:14	ga_s2am_ard_3-2-1_56LMH_2023-10-14_nrt.stac-item
2023-10-14 09:41:15	ga_s2am_ard_3-2-1_56LLH_2023-10-14_nrt.stac-item
2023-10-14 09:41:40	ga_s2am_ard_3-2-1_56KLF_2023-10-14_final.stac-item
2023-10-14 09:42:12	ga_s2am_ard_3-2-1_56KKD_2023-10-14_nrt.stac-item
2023-10-14 09:42:23	ga_s2am_ard_3-2-1_56KLC_2023-10-14_nrt.stac-item
2023-10-14 09:42:27	ga_s2am_ard_3-2-1_55KHT_2023-10-14_nrt.stac-item
2023-10-14 09:42:38	ga_s2am_ard_3-2-1_56KLB_2023-10-14_final.stac-item
2023-10-14 09:42:41	ga_s2am_ard_3-2-1_56KKB_2023-10-14_final.stac-item
2023-10-14 09:42:45	ga_s2am_ard_3-2-1_55KGS_2023-10-14_final.stac-item
2023-10-14 09:43:54	ga_s2am_ard_3-2-1_55JHM_2023-10-14_final.stac-item
2023-10-14 09:43:57	ga_s2am_ard_3-2-1_55JGM_2023-10-14_final.stac-item
2023-10-14 09:44:23	ga_s2am_ard_3-2-1_56JKQ_2023-10-14_final.stac-item
2023-10-14 09:44:26	ga_s2am_ard_3-2-1_55JGK_2023-10-14_final.stac-item
2023-10-14 09:44:37	ga_s2am_ard_3-2-1_56JKP_2023-10-14_final.stac-item
2023-10-14 09:44:41	ga_s2am_ard_3-2-1_55JGJ_2023-10-14_final.stac-item
2023-10-14 09:44:44	ga_s2am_ard_3-2-1_55JFJ_2023-10-14_final.stac-item
2023-10-14 09:44:55	ga_s2am_ard_3-2-1_55JGH_2023-10-14_final.stac-item
2023-10-14 09:45:02	ga_s2am_ard_3-2-1_55JEH_2023-10-14_final.stac-item
2023-10-14 09:45:20	ga_s2am_ard_3-2-1_56JKL_2023-10-14_final.stac-item
2023-10-14 09:45:24	ga_s2am_ard_3-2-1_55JGF_2023-10-14_final.stac-item
2023-10-14 09:45:57	ga_s2am_ard_3-2-1_55HFD_2023-10-14_final.stac-item
2023-10-14 09:46:11	ga_s2am_ard_3-2-1_55HFC_2023-10-14_final.stac-item
2023-10-14 09:46:15	ga_s2am_ard_3-2-1_55HEC_2023-10-14_final.stac-item
2023-10-14 09:46:15	ga_s2am_ard_3-2-1_55HGB_2023-10-14_final.stac-item
2023-10-14 09:46:18	ga_s2am_ard_3-2-1_55HDC_2023-10-14_final.stac-item
2023-10-14 09:46:25	ga_s2am_ard_3-2-1_55HFB_2023-10-14_final.stac-item
2023-10-14 09:46:26	ga_s2am_ard_3-2-1_55HCC_2023-10-14_final.stac-item
2023-10-14 09:46:29	ga_s2am_ard_3-2-1_55HEB_2023-10-14_final.stac-item
2023-10-14 09:46:37	ga_s2am_ard_3-2-1_55HCB_2023-10-14_final.stac-item
2023-10-14 09:46:58	ga_s2am_ard_3-2-1_55HEV_2023-10-14_final.stac-item
2023-10-14 09:47:02	ga_s2am_ard_3-2-1_55HDV_2023-10-14_final.stac-item
2023-10-14 09:47:05	ga_s2am_ard_3-2-1_55HCV_2023-10-14_final.stac-item
2023-10-14 09:47:18	ga_s2am_ard_3-2-1_55HFT_2023-10-14_final.stac-item
2023-10-14 09:47:34	ga_s2am_ard_3-2-1_55HCT_2023-10-14_final.stac-item
2023-10-14 09:47:38	ga_s2am_ard_3-2-1_55HBT_2023-10-14_final.stac-item
2023-10-14 09:47:42	ga_s2am_ard_3-2-1_55HES_2023-10-14_final.stac-item
2023-10-14 09:47:43	ga_s2am_ard_3-2-1_54HYC_2023-10-14_final.stac-item
2023-10-14 09:47:52	ga_s2am_ard_3-2-1_55HBS_2023-10-14_final.stac-item
2023-10-14 09:47:53	ga_s2am_ard_3-2-1_54HYB_2023-10-14_final.stac-item
2023-10-14 09:48:10	ga_s2am_ard_3-2-1_55GEQ_2023-10-14_final.stac-item
2023-10-14 09:48:14	ga_s2am_ard_3-2-1_55GDQ_2023-10-14_final.stac-item
2023-10-14 09:48:18	ga_s2am_ard_3-2-1_55GCQ_2023-10-14_final.stac-item
2023-10-14 09:48:21	ga_s2am_ard_3-2-1_55GBQ_2023-10-14_final.stac-item
2023-10-14 09:48:22	ga_s2am_ard_3-2-1_54GYV_2023-10-14_final.stac-item
2023-10-14 09:48:43	ga_s2am_ard_3-2-1_55GDN_2023-10-14_final.stac-item
2023-10-14 09:48:46	ga_s2am_ard_3-2-1_55GCN_2023-10-14_final.stac-item
2023-10-14 09:48:47	ga_s2am_ard_3-2-1_54GYT_2023-10-14_nrt.stac-item
2023-10-14 09:48:49	ga_s2am_ard_3-2-1_54GXT_2023-10-14_nrt.stac-item
2023-10-14 09:48:51	ga_s2am_ard_3-2-1_55GDN_2023-10-14_final.stac-item
2023-10-14 09:48:51	ga_s2am_ard_3-2-1_55GDM_2023-10-14_final.stac-item
2023-10-14 09:48:52	ga_s2am_ard_3-2-1_55GCM_2023-10-14_final.stac-item
2023-10-14 09:48:53	ga_s2am_ard_3-2-1_55GCN_2023-10-14_final.stac-item
2023-10-14 09:48:54	ga_s2am_ard_3-2-1_54GYT_2023-10-14_nrt.stac-item
2023-10-14 09:48:55	ga_s2am_ard_3-2-1_55GDM_2023-10-14_final.stac-item
2023-10-14 09:48:56	ga_s2am_ard_3-2-1_54GXT_2023-10-14_nrt.stac-item
2023-10-14 09:48:57	ga_s2am_ard_3-2-1_55GCM_2023-10-14_final.stac-item
2023-10-14 09:48:58	ga_s2am_ard_3-2-1_54GYS_2023-10-14_nrt.stac-item
2023-10-14 09:49:00	ga_s2am_ard_3-2-1_54GXS_2023-10-14_nrt.stac-item
2023-10-14 11:20:14	ga_s2am_ard_3-2-1_52LEP_2023-10-14_nrt.stac-item
2023-10-14 11:20:18	ga_s2am_ard_3-2-1_52LDP_2023-10-14_nrt.stac-item
2023-10-14 11:20:21	ga_s2am_ard_3-2-1_52LCP_2023-10-14_nrt.stac-item
2023-10-14 11:20:24	ga_s2am_ard_3-2-1_52LBP_2023-10-14_nrt.stac-item
2023-10-14 11:20:38	ga_s2am_ard_3-2-1_52LBN_2023-10-14_nrt.stac-item
2023-10-14 11:21:16	ga_s2am_ard_3-2-1_52LDK_2023-10-14_nrt.stac-item
2023-10-14 11:21:45	ga_s2am_ard_3-2-1_52LDH_2023-10-14_final.stac-item
2023-10-14 11:22:17	ga_s2am_ard_3-2-1_52KCF_2023-10-14_final.stac-item
2023-10-14 11:22:50	ga_s2am_ard_3-2-1_52KBD_2023-10-14_final.stac-item
2023-10-14 11:22:59	ga_s2am_ard_3-2-1_51KXU_2023-10-14_final.stac-item
2023-10-14 11:23:01	ga_s2am_ard_3-2-1_52KCC_2023-10-14_final.stac-item
2023-10-14 11:23:05	ga_s2am_ard_3-2-1_51KZT_2023-10-14_final.stac-item
2023-10-14 11:23:12	ga_s2am_ard_3-2-1_51KXT_2023-10-14_final.stac-item
2023-10-14 11:23:19	ga_s2am_ard_3-2-1_52KBB_2023-10-14_final.stac-item
2023-10-14 11:23:23	ga_s2am_ard_3-2-1_51KYS_2023-10-14_final.stac-item
2023-10-14 11:24:13	ga_s2am_ard_3-2-1_51KWP_2023-10-14_final.stac-item
2023-10-14 11:24:30	ga_s2am_ard_3-2-1_51JZM_2023-10-14_final.stac-item
2023-10-14 11:24:35	ga_s2am_ard_3-2-1_51JYM_2023-10-14_final.stac-item
2023-10-14 11:24:57	ga_s2am_ard_3-2-1_51JWL_2023-10-14_final.stac-item
2023-10-14 11:25:08	ga_s2am_ard_3-2-1_51JXK_2023-10-14_final.stac-item
2023-10-14 11:25:19	ga_s2am_ard_3-2-1_51JYJ_2023-10-14_final.stac-item
2023-10-14 11:25:22	ga_s2am_ard_3-2-1_51JXJ_2023-10-14_final.stac-item
2023-10-14 11:25:58	ga_s2am_ard_3-2-1_51JVG_2023-10-14_final.stac-item
2023-10-14 11:26:09	ga_s2am_ard_3-2-1_51JWF_2023-10-14_final.stac-item
2023-10-14 11:26:34	ga_s2am_ard_3-2-1_51HXD_2023-10-14_final.stac-item
2023-10-14 11:26:45	ga_s2am_ard_3-2-1_51HUD_2023-10-14_final.stac-item
2023-10-14 11:26:46	ga_s2am_ard_3-2-1_51HXC_2023-10-14_final.stac-item
2023-10-14 11:26:53	ga_s2am_ard_3-2-1_51HWC_2023-10-14_final.stac-item
2023-10-14 11:26:56	ga_s2am_ard_3-2-1_51HVC_2023-10-14_final.stac-item
2023-10-14 11:27:00	ga_s2am_ard_3-2-1_51HUC_2023-10-14_final.stac-item
2023-10-14 11:27:07	ga_s2am_ard_3-2-1_51HWB_2023-10-14_final.stac-item
2023-10-14 11:27:09	ga_s2am_ard_3-2-1_51HVB_2023-10-14_final.stac-item
2023-10-14 11:27:11	ga_s2am_ard_3-2-1_51HUB_2023-10-14_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

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