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
2018-12-14 12:14:51	ga_s2am_ard_3-2-1_49JFM_2018-12-14_final
2018-12-14 12:15:02	ga_s2am_ard_3-2-1_49JGL_2018-12-14_final
2018-12-14 12:15:11	ga_s2am_ard_3-2-1_49JGK_2018-12-14_final
2018-12-15 10:01:03	ga_s2am_ard_3-2-1_55LCD_2018-12-15_final
2018-12-15 10:01:09	ga_s2am_ard_3-2-1_55LEC_2018-12-15_final
2018-12-15 10:01:20	ga_s2am_ard_3-2-1_55KFB_2018-12-15_final
2018-12-15 10:01:24	ga_s2am_ard_3-2-1_55KEB_2018-12-15_final
2018-12-15 10:01:27	ga_s2am_ard_3-2-1_55KDB_2018-12-15_final
2018-12-15 10:01:30	ga_s2am_ard_3-2-1_55KCB_2018-12-15_final
2018-12-15 10:01:59	ga_s2am_ard_3-2-1_55KCV_2018-12-15_final
2018-12-15 10:02:49	ga_s2am_ard_3-2-1_55KER_2018-12-15_final
2018-12-15 10:02:54	ga_s2am_ard_3-2-1_55KDR_2018-12-15_final
2018-12-15 10:03:01	ga_s2am_ard_3-2-1_54KZA_2018-12-15_final
2018-12-15 10:03:15	ga_s2am_ard_3-2-1_54KZV_2018-12-15_final
2018-12-15 10:03:56	ga_s2am_ard_3-2-1_55JCM_2018-12-15_final
2018-12-15 10:04:05	ga_s2am_ard_3-2-1_55JDL_2018-12-15_final
2018-12-15 10:04:10	ga_s2am_ard_3-2-1_55JCL_2018-12-15_final
2018-12-15 10:04:13	ga_s2am_ard_3-2-1_55JBL_2018-12-15_final
2018-12-15 10:04:15	ga_s2am_ard_3-2-1_55JDK_2018-12-15_final
2018-12-15 10:04:17	ga_s2am_ard_3-2-1_54JYR_2018-12-15_final
2018-12-15 10:04:24	ga_s2am_ard_3-2-1_54JXR_2018-12-15_final
2018-12-15 10:04:31	ga_s2am_ard_3-2-1_54JYQ_2018-12-15_final
2018-12-15 10:04:39	ga_s2am_ard_3-2-1_55JCJ_2018-12-15_final
2018-12-15 10:04:42	ga_s2am_ard_3-2-1_55JBJ_2018-12-15_final
2018-12-15 10:04:45	ga_s2am_ard_3-2-1_54JYP_2018-12-15_final
2018-12-15 10:04:49	ga_s2am_ard_3-2-1_54JXP_2018-12-15_final
2018-12-15 10:04:54	ga_s2am_ard_3-2-1_55JCH_2018-12-15_final
2018-12-15 10:04:57	ga_s2am_ard_3-2-1_55JBH_2018-12-15_final
2018-12-15 10:05:00	ga_s2am_ard_3-2-1_54JYN_2018-12-15_final
2018-12-15 10:05:04	ga_s2am_ard_3-2-1_54JXN_2018-12-15_final
2018-12-15 10:05:12	ga_s2am_ard_3-2-1_55JBG_2018-12-15_final
2018-12-15 10:05:14	ga_s2am_ard_3-2-1_54JYM_2018-12-15_final
2018-12-15 10:05:25	ga_s2am_ard_3-2-1_54JWM_2018-12-15_final
2018-12-15 10:05:26	ga_s2am_ard_3-2-1_55JBF_2018-12-15_final
2018-12-15 10:05:29	ga_s2am_ard_3-2-1_54JYL_2018-12-15_final
2018-12-15 10:06:01	ga_s2am_ard_3-2-1_54HXJ_2018-12-15_final
2018-12-15 10:06:10	ga_s2am_ard_3-2-1_55HBC_2018-12-15_final
2018-12-15 10:06:12	ga_s2am_ard_3-2-1_54HYH_2018-12-15_final
2018-12-15 10:06:24	ga_s2am_ard_3-2-1_55HBB_2018-12-15_final
2018-12-15 10:06:30	ga_s2am_ard_3-2-1_54HXG_2018-12-15_final
2018-12-15 10:06:47	ga_s2am_ard_3-2-1_55HBV_2018-12-15_final
2018-12-15 10:06:49	ga_s2am_ard_3-2-1_54HWF_2018-12-15_final
2018-12-15 10:06:52	ga_s2am_ard_3-2-1_54HVF_2018-12-15_final
2018-12-15 10:06:55	ga_s2am_ard_3-2-1_54HYE_2018-12-15_final
2018-12-15 10:06:59	ga_s2am_ard_3-2-1_54HXE_2018-12-15_final
2018-12-15 10:07:03	ga_s2am_ard_3-2-1_54HWE_2018-12-15_final
2018-12-15 10:07:07	ga_s2am_ard_3-2-1_54HVE_2018-12-15_final
2018-12-15 10:07:18	ga_s2am_ard_3-2-1_54HWD_2018-12-15_final
2018-12-15 10:07:21	ga_s2am_ard_3-2-1_54HVD_2018-12-15_final
2018-12-15 11:40:49	ga_s2am_ard_3-2-1_51LWG_2018-12-15_final.stac-item
2018-12-15 11:40:52	ga_s2am_ard_3-2-1_51LVG_2018-12-15_final
2018-12-15 11:41:06	ga_s2am_ard_3-2-1_51LVF_2018-12-15_final
2018-12-15 11:41:39	ga_s2am_ard_3-2-1_51LUD_2018-12-15_final.stac-item
2018-12-15 11:41:47	ga_s2am_ard_3-2-1_51LWC_2018-12-15_final
2018-12-15 11:41:50	ga_s2am_ard_3-2-1_51LVC_2018-12-15_final
2018-12-15 11:41:53	ga_s2am_ard_3-2-1_51LUC_2018-12-15_final.stac-item
2018-12-15 11:42:01	ga_s2am_ard_3-2-1_51KWB_2018-12-15_final
2018-12-15 11:42:05	ga_s2am_ard_3-2-1_51KVB_2018-12-15_final
2018-12-15 11:42:22	ga_s2am_ard_3-2-1_51KUA_2018-12-15_final
2018-12-15 11:42:33	ga_s2am_ard_3-2-1_51KVV_2018-12-15_final
2018-12-15 11:42:37	ga_s2am_ard_3-2-1_51KUV_2018-12-15_final
2018-12-15 11:43:24	ga_s2am_ard_3-2-1_50KRB_2018-12-15_final
2018-12-15 11:43:27	ga_s2am_ard_3-2-1_51KVR_2018-12-15_final
2018-12-15 11:43:39	ga_s2am_ard_3-2-1_50KRA_2018-12-15_final
2018-12-15 11:43:53	ga_s2am_ard_3-2-1_50KRV_2018-12-15_final
2018-12-15 11:43:57	ga_s2am_ard_3-2-1_50KQV_2018-12-15_final
2018-12-15 11:44:01	ga_s2am_ard_3-2-1_50KPV_2018-12-15_final
2018-12-15 11:44:14	ga_s2am_ard_3-2-1_50KPU_2018-12-15_final
2018-12-15 11:44:29	ga_s2am_ard_3-2-1_51JUM_2018-12-15_final
2018-12-15 11:44:31	ga_s2am_ard_3-2-1_50JRS_2018-12-15_final
2018-12-15 11:44:35	ga_s2am_ard_3-2-1_50JPS_2018-12-15_final
2018-12-15 11:44:35	ga_s2am_ard_3-2-1_51JUM_2018-12-15_final
2018-12-15 11:44:38	ga_s2am_ard_3-2-1_50JRS_2018-12-15_final
2018-12-15 11:44:43	ga_s2am_ard_3-2-1_51JUL_2018-12-15_final
2018-12-15 11:44:44	ga_s2am_ard_3-2-1_50JPS_2018-12-15_final
2018-12-15 11:44:51	ga_s2am_ard_3-2-1_51JTL_2018-12-15_final
2018-12-15 11:44:55	ga_s2am_ard_3-2-1_50JQR_2018-12-15_final
2018-12-15 11:44:58	ga_s2am_ard_3-2-1_50JPR_2018-12-15_final
2018-12-15 11:45:03	ga_s2am_ard_3-2-1_50JNR_2018-12-15_final
2018-12-15 11:45:09	ga_s2am_ard_3-2-1_50JQQ_2018-12-15_final
2018-12-15 11:45:16	ga_s2am_ard_3-2-1_50JNQ_2018-12-15_final
2018-12-15 11:45:20	ga_s2am_ard_3-2-1_51JTJ_2018-12-15_final
2018-12-15 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-12-15_final
2018-12-15 11:45:27	ga_s2am_ard_3-2-1_50JPP_2018-12-15_final
2018-12-15 11:45:31	ga_s2am_ard_3-2-1_50JNP_2018-12-15_final
2018-12-15 11:45:35	ga_s2am_ard_3-2-1_51JTH_2018-12-15_final
2018-12-15 11:45:38	ga_s2am_ard_3-2-1_50JQN_2018-12-15_final
2018-12-15 11:45:42	ga_s2am_ard_3-2-1_50JPN_2018-12-15_final
2018-12-15 11:45:45	ga_s2am_ard_3-2-1_50JNN_2018-12-15_final
2018-12-15 11:45:48	ga_s2am_ard_3-2-1_51JTG_2018-12-15_final
2018-12-15 11:45:52	ga_s2am_ard_3-2-1_50JQM_2018-12-15_final
2018-12-15 11:45:59	ga_s2am_ard_3-2-1_51JTF_2018-12-15_final
2018-12-15 11:46:00	ga_s2am_ard_3-2-1_50JNM_2018-12-15_final
2018-12-15 11:46:04	ga_s2am_ard_3-2-1_50JMM_2018-12-15_final
2018-12-15 11:46:07	ga_s2am_ard_3-2-1_50JQL_2018-12-15_final
2018-12-15 11:46:14	ga_s2am_ard_3-2-1_50JNL_2018-12-15_final
2018-12-15 11:46:17	ga_s2am_ard_3-2-1_50JML_2018-12-15_final
2018-12-15 11:46:39	ga_s2am_ard_3-2-1_50HPJ_2018-12-15_final
2018-12-15 11:46:45	ga_s2am_ard_3-2-1_50HQH_2018-12-15_final
2018-12-15 11:47:08	ga_s2am_ard_3-2-1_50HPG_2018-12-15_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

Other products

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