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
2022-03-18 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-03-18_final
2022-03-18 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-03-18_final
2022-03-18 12:14:22	ga_s2am_ard_3-2-1_50KKU_2022-03-18_final
2022-03-18 12:14:25	ga_s2am_ard_3-2-1_49KHP_2022-03-18_final
2022-03-18 12:14:31	ga_s2am_ard_3-2-1_49KGP_2022-03-18_final
2022-03-18 12:14:34	ga_s2am_ard_3-2-1_49JHN_2022-03-18_final
2022-03-18 12:15:03	ga_s2am_ard_3-2-1_49JFM_2022-03-18_final
2022-03-18 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-03-18_final
2022-03-18 12:15:23	ga_s2am_ard_3-2-1_49JGK_2022-03-18_final
2022-03-19 10:01:32	ga_s2am_ard_3-2-1_55KFB_2022-03-19_final
2022-03-19 10:01:36	ga_s2am_ard_3-2-1_55KEB_2022-03-19_final
2022-03-19 10:01:39	ga_s2am_ard_3-2-1_55KDB_2022-03-19_final
2022-03-19 10:01:42	ga_s2am_ard_3-2-1_55KCB_2022-03-19_final
2022-03-19 10:01:54	ga_s2am_ard_3-2-1_55KDA_2022-03-19_final
2022-03-19 10:01:57	ga_s2am_ard_3-2-1_55KCA_2022-03-19_final
2022-03-19 10:02:04	ga_s2am_ard_3-2-1_55KEV_2022-03-19_final
2022-03-19 10:02:08	ga_s2am_ard_3-2-1_55KDV_2022-03-19_final
2022-03-19 10:02:40	ga_s2am_ard_3-2-1_55KCT_2022-03-19_final
2022-03-19 10:02:45	ga_s2am_ard_3-2-1_54KZC_2022-03-19_final
2022-03-19 10:02:58	ga_s2am_ard_3-2-1_54KZB_2022-03-19_final
2022-03-19 10:03:13	ga_s2am_ard_3-2-1_54KZA_2022-03-19_final
2022-03-19 10:03:27	ga_s2am_ard_3-2-1_55KBQ_2022-03-19_final
2022-03-19 10:03:27	ga_s2am_ard_3-2-1_54KZV_2022-03-19_final
2022-03-19 10:03:35	ga_s2am_ard_3-2-1_54KYV_2022-03-19_final
2022-03-19 10:03:42	ga_s2am_ard_3-2-1_54KZU_2022-03-19_final
2022-03-19 10:03:46	ga_s2am_ard_3-2-1_54KYU_2022-03-19_final
2022-03-19 10:03:56	ga_s2am_ard_3-2-1_54JZT_2022-03-19_final
2022-03-19 10:04:08	ga_s2am_ard_3-2-1_55JCM_2022-03-19_final
2022-03-19 10:04:11	ga_s2am_ard_3-2-1_54JZS_2022-03-19_final
2022-03-19 10:04:22	ga_s2am_ard_3-2-1_55JCL_2022-03-19_final
2022-03-19 10:04:26	ga_s2am_ard_3-2-1_55JBL_2022-03-19_final
2022-03-19 10:04:29	ga_s2am_ard_3-2-1_54JYR_2022-03-19_final
2022-03-19 10:04:36	ga_s2am_ard_3-2-1_54JXR_2022-03-19_final
2022-03-19 10:04:40	ga_s2am_ard_3-2-1_55JBK_2022-03-19_final
2022-03-19 10:04:43	ga_s2am_ard_3-2-1_54JYQ_2022-03-19_final
2022-03-19 10:05:06	ga_s2am_ard_3-2-1_55JCH_2022-03-19_final
2022-03-19 10:05:09	ga_s2am_ard_3-2-1_55JBH_2022-03-19_final
2022-03-19 10:05:12	ga_s2am_ard_3-2-1_54JYN_2022-03-19_final
2022-03-19 10:05:16	ga_s2am_ard_3-2-1_54JXN_2022-03-19_final
2022-03-19 10:05:24	ga_s2am_ard_3-2-1_55JBG_2022-03-19_final
2022-03-19 10:05:27	ga_s2am_ard_3-2-1_54JYM_2022-03-19_final
2022-03-19 10:05:48	ga_s2am_ard_3-2-1_54JWL_2022-03-19_final
2022-03-19 10:05:53	ga_s2am_ard_3-2-1_55HBE_2022-03-19_final
2022-03-19 10:05:55	ga_s2am_ard_3-2-1_54HYK_2022-03-19_final
2022-03-19 10:06:22	ga_s2am_ard_3-2-1_55HBC_2022-03-19_final
2022-03-19 10:06:24	ga_s2am_ard_3-2-1_54HYH_2022-03-19_final
2022-03-19 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-03-19_final
2022-03-19 10:07:04	ga_s2am_ard_3-2-1_54HVF_2022-03-19_final
2022-03-19 10:07:11	ga_s2am_ard_3-2-1_54HXE_2022-03-19_final
2022-03-19 10:07:15	ga_s2am_ard_3-2-1_54HWE_2022-03-19_final
2022-03-19 11:41:01	ga_s2am_ard_3-2-1_51LWG_2022-03-19_final.stac-item
2022-03-19 11:41:04	ga_s2am_ard_3-2-1_51LVG_2022-03-19_final
2022-03-19 11:42:13	ga_s2am_ard_3-2-1_51KWB_2022-03-19_final
2022-03-19 11:42:17	ga_s2am_ard_3-2-1_51KVB_2022-03-19_final
2022-03-19 11:42:19	ga_s2am_ard_3-2-1_51KUB_2022-03-19_final.stac-item
2022-03-19 11:42:25	ga_s2am_ard_3-2-1_51KVB_2022-03-19_final
2022-03-19 11:42:25	ga_s2am_ard_3-2-1_51KVA_2022-03-19_final
2022-03-19 11:42:26	ga_s2am_ard_3-2-1_51KUB_2022-03-19_final.stac-item
2022-03-19 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-03-19_final
2022-03-19 11:42:46	ga_s2am_ard_3-2-1_51KVV_2022-03-19_final
2022-03-19 11:42:49	ga_s2am_ard_3-2-1_51KUV_2022-03-19_final
2022-03-19 11:43:08	ga_s2am_ard_3-2-1_50KRD_2022-03-19_final
2022-03-19 11:43:18	ga_s2am_ard_3-2-1_51KUT_2022-03-19_final
2022-03-19 11:43:22	ga_s2am_ard_3-2-1_50KRC_2022-03-19_final
2022-03-19 11:43:37	ga_s2am_ard_3-2-1_50KRB_2022-03-19_final
2022-03-19 11:43:51	ga_s2am_ard_3-2-1_50KRA_2022-03-19_final
2022-03-19 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2022-03-19_final
2022-03-19 11:44:05	ga_s2am_ard_3-2-1_50KRV_2022-03-19_final
2022-03-19 11:44:09	ga_s2am_ard_3-2-1_50KQV_2022-03-19_final
2022-03-19 11:44:16	ga_s2am_ard_3-2-1_51KUP_2022-03-19_final
2022-03-19 11:44:20	ga_s2am_ard_3-2-1_50KRU_2022-03-19_final
2022-03-19 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-03-19_final
2022-03-19 11:44:23	ga_s2am_ard_3-2-1_50KQU_2022-03-19_final
2022-03-19 11:44:27	ga_s2am_ard_3-2-1_50KPU_2022-03-19_final
2022-03-19 11:44:31	ga_s2am_ard_3-2-1_51JUN_2022-03-19_final
2022-03-19 11:44:34	ga_s2am_ard_3-2-1_50JRT_2022-03-19_final
2022-03-19 11:44:44	ga_s2am_ard_3-2-1_51JUM_2022-03-19_final
2022-03-19 11:44:48	ga_s2am_ard_3-2-1_50JRS_2022-03-19_final
2022-03-19 11:44:54	ga_s2am_ard_3-2-1_51JUL_2022-03-19_final
2022-03-19 11:44:56	ga_s2am_ard_3-2-1_50JPS_2022-03-19_final
2022-03-19 11:45:03	ga_s2am_ard_3-2-1_51JTL_2022-03-19_final
2022-03-19 11:45:07	ga_s2am_ard_3-2-1_50JQR_2022-03-19_final
2022-03-19 11:45:10	ga_s2am_ard_3-2-1_50JPR_2022-03-19_final
2022-03-19 11:45:15	ga_s2am_ard_3-2-1_50JNR_2022-03-19_final
2022-03-19 11:45:18	ga_s2am_ard_3-2-1_51JTK_2022-03-19_final
2022-03-19 11:45:21	ga_s2am_ard_3-2-1_50JQQ_2022-03-19_final
2022-03-19 11:45:28	ga_s2am_ard_3-2-1_50JNQ_2022-03-19_final
2022-03-19 11:45:43	ga_s2am_ard_3-2-1_50JNP_2022-03-19_final
2022-03-19 11:45:47	ga_s2am_ard_3-2-1_51JTH_2022-03-19_final
2022-03-19 11:45:50	ga_s2am_ard_3-2-1_50JQN_2022-03-19_final
2022-03-19 11:45:54	ga_s2am_ard_3-2-1_50JPN_2022-03-19_final
2022-03-19 11:45:57	ga_s2am_ard_3-2-1_50JNN_2022-03-19_final
2022-03-19 11:46:00	ga_s2am_ard_3-2-1_51JTG_2022-03-19_final
2022-03-19 11:46:04	ga_s2am_ard_3-2-1_50JQM_2022-03-19_final
2022-03-19 11:46:12	ga_s2am_ard_3-2-1_50JNM_2022-03-19_final
2022-03-19 11:46:16	ga_s2am_ard_3-2-1_50JMM_2022-03-19_final
2022-03-19 11:46:19	ga_s2am_ard_3-2-1_50JQL_2022-03-19_final
2022-03-19 11:46:26	ga_s2am_ard_3-2-1_50JNL_2022-03-19_final
2022-03-19 11:46:29	ga_s2am_ard_3-2-1_50JML_2022-03-19_final
2022-03-19 11:46:33	ga_s2am_ard_3-2-1_50HQK_2022-03-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

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