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
2022-04-17 12:15:14	ga_s2am_ard_3-2-1_49JGL_2022-04-17_final
2022-04-18 10:01:15	ga_s2am_ard_3-2-1_55LCD_2022-04-18_final
2022-04-18 10:01:32	ga_s2am_ard_3-2-1_55KFB_2022-04-18_final
2022-04-18 10:01:42	ga_s2am_ard_3-2-1_55KCB_2022-04-18_final
2022-04-18 10:01:46	ga_s2am_ard_3-2-1_55KFA_2022-04-18_final
2022-04-18 10:01:54	ga_s2am_ard_3-2-1_55KDA_2022-04-18_final
2022-04-18 10:01:57	ga_s2am_ard_3-2-1_55KCA_2022-04-18_final
2022-04-18 10:02:05	ga_s2am_ard_3-2-1_55KEV_2022-04-18_final
2022-04-18 10:02:08	ga_s2am_ard_3-2-1_55KDV_2022-04-18_final
2022-04-18 10:02:09	ga_s2am_ard_3-2-1_55KFU_2022-04-18_final
2022-04-18 10:02:19	ga_s2am_ard_3-2-1_55KBV_2022-04-18_final
2022-04-18 10:02:19	ga_s2am_ard_3-2-1_55KEU_2022-04-18_final
2022-04-18 10:02:23	ga_s2am_ard_3-2-1_55KDU_2022-04-18_final
2022-04-18 10:02:41	ga_s2am_ard_3-2-1_55KCT_2022-04-18_final
2022-04-18 10:02:48	ga_s2am_ard_3-2-1_55KES_2022-04-18_final
2022-04-18 10:02:52	ga_s2am_ard_3-2-1_55KDS_2022-04-18_final
2022-04-18 10:02:55	ga_s2am_ard_3-2-1_55KCS_2022-04-18_final
2022-04-18 10:03:02	ga_s2am_ard_3-2-1_55KER_2022-04-18_final
2022-04-18 10:03:06	ga_s2am_ard_3-2-1_55KDR_2022-04-18_final
2022-04-18 10:03:10	ga_s2am_ard_3-2-1_55KCR_2022-04-18_final
2022-04-18 10:03:24	ga_s2am_ard_3-2-1_55KCQ_2022-04-18_final
2022-04-18 10:03:27	ga_s2am_ard_3-2-1_55KBQ_2022-04-18_final
2022-04-18 10:03:36	ga_s2am_ard_3-2-1_54KYV_2022-04-18_final
2022-04-18 10:03:42	ga_s2am_ard_3-2-1_55KBP_2022-04-18_final
2022-04-18 10:03:46	ga_s2am_ard_3-2-1_54KYU_2022-04-18_final
2022-04-18 10:03:56	ga_s2am_ard_3-2-1_54JZT_2022-04-18_final
2022-04-18 10:03:57	ga_s2am_ard_3-2-1_55JBN_2022-04-18_final
2022-04-18 10:04:00	ga_s2am_ard_3-2-1_54JYT_2022-04-18_final
2022-04-18 10:04:04	ga_s2am_ard_3-2-1_55JDM_2022-04-18_final
2022-04-18 10:04:15	ga_s2am_ard_3-2-1_54JYS_2022-04-18_final
2022-04-18 10:04:17	ga_s2am_ard_3-2-1_55JDL_2022-04-18_final
2022-04-18 10:04:22	ga_s2am_ard_3-2-1_55JCL_2022-04-18_final
2022-04-18 10:04:26	ga_s2am_ard_3-2-1_55JBL_2022-04-18_final
2022-04-18 10:04:27	ga_s2am_ard_3-2-1_55JDK_2022-04-18_final
2022-04-18 10:04:36	ga_s2am_ard_3-2-1_54JXR_2022-04-18_final
2022-04-18 10:04:55	ga_s2am_ard_3-2-1_55JBJ_2022-04-18_final
2022-04-18 10:04:58	ga_s2am_ard_3-2-1_54JYP_2022-04-18_final
2022-04-18 10:05:10	ga_s2am_ard_3-2-1_55JBH_2022-04-18_final
2022-04-18 10:05:12	ga_s2am_ard_3-2-1_54JYN_2022-04-18_final
2022-04-18 10:05:24	ga_s2am_ard_3-2-1_55JBG_2022-04-18_final
2022-04-18 10:05:27	ga_s2am_ard_3-2-1_54JYM_2022-04-18_final
2022-04-18 10:05:37	ga_s2am_ard_3-2-1_54JWM_2022-04-18_final
2022-04-18 10:05:49	ga_s2am_ard_3-2-1_54JWL_2022-04-18_final
2022-04-18 10:06:08	ga_s2am_ard_3-2-1_55HBD_2022-04-18_final
2022-04-18 10:06:10	ga_s2am_ard_3-2-1_54HYJ_2022-04-18_final
2022-04-18 10:06:23	ga_s2am_ard_3-2-1_55HBC_2022-04-18_final
2022-04-18 10:06:24	ga_s2am_ard_3-2-1_54HYH_2022-04-18_final
2022-04-18 10:06:59	ga_s2am_ard_3-2-1_55HBV_2022-04-18_final
2022-04-18 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-04-18_final
2022-04-18 10:07:04	ga_s2am_ard_3-2-1_54HVF_2022-04-18_final
2022-04-18 10:07:07	ga_s2am_ard_3-2-1_54HYE_2022-04-18_final
2022-04-18 10:07:12	ga_s2am_ard_3-2-1_54HXE_2022-04-18_final
2022-04-18 10:07:15	ga_s2am_ard_3-2-1_54HWE_2022-04-18_final
2022-04-18 10:07:19	ga_s2am_ard_3-2-1_54HVE_2022-04-18_final
2022-04-18 11:41:30	ga_s2am_ard_3-2-1_51LWE_2022-04-18_final
2022-04-18 11:41:34	ga_s2am_ard_3-2-1_51LVE_2022-04-18_final
2022-04-18 11:41:37	ga_s2am_ard_3-2-1_51LUE_2022-04-18_final
2022-04-18 11:41:51	ga_s2am_ard_3-2-1_51LUD_2022-04-18_final.stac-item
2022-04-18 11:42:20	ga_s2am_ard_3-2-1_51KUB_2022-04-18_final.stac-item
2022-04-18 11:42:23	ga_s2am_ard_3-2-1_51KWA_2022-04-18_final
2022-04-18 11:42:25	ga_s2am_ard_3-2-1_51KVA_2022-04-18_final
2022-04-18 11:42:26	ga_s2am_ard_3-2-1_51KUA_2022-04-18_final
2022-04-18 11:42:27	ga_s2am_ard_3-2-1_51KWA_2022-04-18_final
2022-04-18 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-04-18_final
2022-04-18 11:42:35	ga_s2am_ard_3-2-1_51KUA_2022-04-18_final
2022-04-18 11:42:46	ga_s2am_ard_3-2-1_51KVV_2022-04-18_final
2022-04-18 11:43:01	ga_s2am_ard_3-2-1_51KVU_2022-04-18_final
2022-04-18 11:43:04	ga_s2am_ard_3-2-1_51KUU_2022-04-18_final
2022-04-18 11:43:19	ga_s2am_ard_3-2-1_51KUT_2022-04-18_final
2022-04-18 11:43:29	ga_s2am_ard_3-2-1_51KVS_2022-04-18_final
2022-04-18 11:43:33	ga_s2am_ard_3-2-1_51KUS_2022-04-18_final
2022-04-18 11:43:47	ga_s2am_ard_3-2-1_51KUR_2022-04-18_final
2022-04-18 11:43:55	ga_s2am_ard_3-2-1_50KQA_2022-04-18_final
2022-04-18 11:44:02	ga_s2am_ard_3-2-1_51KUQ_2022-04-18_final
2022-04-18 11:44:09	ga_s2am_ard_3-2-1_50KQV_2022-04-18_final
2022-04-18 11:44:17	ga_s2am_ard_3-2-1_51KUP_2022-04-18_final
2022-04-18 11:44:20	ga_s2am_ard_3-2-1_51KTP_2022-04-18_final
2022-04-18 11:44:27	ga_s2am_ard_3-2-1_50KPU_2022-04-18_final
2022-04-18 11:44:34	ga_s2am_ard_3-2-1_50JRT_2022-04-18_final
2022-04-18 11:44:35	ga_s2am_ard_3-2-1_51JTN_2022-04-18_final
2022-04-18 11:44:38	ga_s2am_ard_3-2-1_50JQT_2022-04-18_final
2022-04-18 11:44:53	ga_s2am_ard_3-2-1_50JQS_2022-04-18_final
2022-04-18 11:44:55	ga_s2am_ard_3-2-1_51JUL_2022-04-18_final
2022-04-18 11:45:03	ga_s2am_ard_3-2-1_51JTL_2022-04-18_final
2022-04-18 11:45:07	ga_s2am_ard_3-2-1_50JQR_2022-04-18_final
2022-04-18 11:45:11	ga_s2am_ard_3-2-1_50JPR_2022-04-18_final
2022-04-18 11:45:15	ga_s2am_ard_3-2-1_50JNR_2022-04-18_final
2022-04-18 11:45:33	ga_s2am_ard_3-2-1_51JTJ_2022-04-18_final
2022-04-18 11:45:36	ga_s2am_ard_3-2-1_50JQP_2022-04-18_final
2022-04-18 11:45:43	ga_s2am_ard_3-2-1_50JNP_2022-04-18_final
2022-04-18 11:45:47	ga_s2am_ard_3-2-1_51JTH_2022-04-18_final
2022-04-18 11:45:50	ga_s2am_ard_3-2-1_50JQN_2022-04-18_final
2022-04-18 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-04-18_final
2022-04-18 11:46:01	ga_s2am_ard_3-2-1_51JTG_2022-04-18_final
2022-04-18 11:46:04	ga_s2am_ard_3-2-1_50JQM_2022-04-18_final
2022-04-18 11:46:12	ga_s2am_ard_3-2-1_50JNM_2022-04-18_final
2022-04-18 11:46:16	ga_s2am_ard_3-2-1_50JMM_2022-04-18_final
2022-04-18 11:46:27	ga_s2am_ard_3-2-1_50JNL_2022-04-18_final
2022-04-18 11:46:30	ga_s2am_ard_3-2-1_50JML_2022-04-18_final
2022-04-18 11:46:47	ga_s2am_ard_3-2-1_50HQJ_2022-04-18_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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