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
2022-04-14 12:04:49	ga_s2am_ard_3-2-1_49JGN_2022-04-14_final
2022-04-14 12:04:51	ga_s2am_ard_3-2-1_50JMS_2022-04-14_final
2022-04-14 12:05:00	ga_s2am_ard_3-2-1_50JKS_2022-04-14_final
2022-04-14 12:05:01	ga_s2am_ard_3-2-1_50JMR_2022-04-14_final
2022-04-14 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final
2022-04-14 12:05:06	ga_s2am_ard_3-2-1_50JLR_2022-04-14_final
2022-04-14 12:05:07	ga_s2am_ard_3-2-1_49JHM_2022-04-14_final
2022-04-14 12:05:07	ga_s2am_ard_3-2-1_50JKR_2022-04-14_final
2022-04-14 12:05:08	ga_s2am_ard_3-2-1_49JGL_2022-04-14_final
2022-04-14 12:05:09	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final
2022-04-14 12:05:11	ga_s2am_ard_3-2-1_49JFM_2022-04-14_final
2022-04-14 12:05:15	ga_s2am_ard_3-2-1_50JKR_2022-04-14_final.stac-item
2022-04-14 12:05:18	ga_s2am_ard_3-2-1_49JGL_2022-04-14_final
2022-04-14 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2022-04-14_final
2022-04-14 12:05:40	ga_s2am_ard_3-2-1_50JLP_2022-04-14_final
2022-04-14 12:05:54	ga_s2am_ard_3-2-1_50JLN_2022-04-14_final
2022-04-14 12:06:01	ga_s2am_ard_3-2-1_49JGH_2022-04-14_final.stac-item
2022-04-14 12:06:13	ga_s2am_ard_3-2-1_50JKM_2022-04-14_final
2022-04-15 09:51:15	ga_s2am_ard_3-2-1_55LHC_2022-04-15_final.stac-item
2022-04-15 09:51:19	ga_s2am_ard_3-2-1_55LGC_2022-04-15_final
2022-04-15 09:51:51	ga_s2am_ard_3-2-1_55KFA_2022-04-15_final
2022-04-15 09:52:09	ga_s2am_ard_3-2-1_55KEV_2022-04-15_final
2022-04-15 09:52:16	ga_s2am_ard_3-2-1_55KGU_2022-04-15_final
2022-04-15 09:52:20	ga_s2am_ard_3-2-1_55KFU_2022-04-15_final
2022-04-15 09:52:23	ga_s2am_ard_3-2-1_55KEU_2022-04-15_final
2022-04-15 09:52:34	ga_s2am_ard_3-2-1_55KFT_2022-04-15_final
2022-04-15 09:52:38	ga_s2am_ard_3-2-1_55KET_2022-04-15_final
2022-04-15 09:52:45	ga_s2am_ard_3-2-1_55KGS_2022-04-15_final
2022-04-15 09:53:14	ga_s2am_ard_3-2-1_55KGQ_2022-04-15_final
2022-04-15 09:53:28	ga_s2am_ard_3-2-1_55KGP_2022-04-15_final
2022-04-15 09:53:32	ga_s2am_ard_3-2-1_55KFP_2022-04-15_final
2022-04-15 09:53:36	ga_s2am_ard_3-2-1_55KEP_2022-04-15_final
2022-04-15 09:53:39	ga_s2am_ard_3-2-1_55KDP_2022-04-15_final
2022-04-15 09:53:41	ga_s2am_ard_3-2-1_55JGN_2022-04-15_final
2022-04-15 09:53:51	ga_s2am_ard_3-2-1_55JGM_2022-04-15_final
2022-04-15 09:54:05	ga_s2am_ard_3-2-1_55JEM_2022-04-15_final
2022-04-15 09:54:08	ga_s2am_ard_3-2-1_55JDM_2022-04-15_final
2022-04-15 09:54:16	ga_s2am_ard_3-2-1_55JFL_2022-04-15_final
2022-04-15 09:54:19	ga_s2am_ard_3-2-1_55JEL_2022-04-15_final
2022-04-15 09:54:48	ga_s2am_ard_3-2-1_55JEJ_2022-04-15_final
2022-04-15 09:54:52	ga_s2am_ard_3-2-1_55JDJ_2022-04-15_final
2022-04-15 09:55:10	ga_s2am_ard_3-2-1_55JCH_2022-04-15_final
2022-04-15 09:55:14	ga_s2am_ard_3-2-1_55JBH_2022-04-15_final
2022-04-15 09:55:17	ga_s2am_ard_3-2-1_55JEG_2022-04-15_final
2022-04-15 09:55:21	ga_s2am_ard_3-2-1_55JDG_2022-04-15_final
2022-04-15 09:55:32	ga_s2am_ard_3-2-1_55JEF_2022-04-15_final
2022-04-15 09:55:36	ga_s2am_ard_3-2-1_55JDF_2022-04-15_final
2022-04-15 09:55:46	ga_s2am_ard_3-2-1_55HEE_2022-04-15_final
2022-04-15 09:55:53	ga_s2am_ard_3-2-1_55HCE_2022-04-15_final
2022-04-15 09:56:00	ga_s2am_ard_3-2-1_54HYK_2022-04-15_final
2022-04-15 09:56:28	ga_s2am_ard_3-2-1_54HYH_2022-04-15_final
2022-04-15 09:56:48	ga_s2am_ard_3-2-1_55HDA_2022-04-15_final
2022-04-15 09:57:01	ga_s2am_ard_3-2-1_55HDV_2022-04-15_final
2022-04-15 09:57:06	ga_s2am_ard_3-2-1_55HCV_2022-04-15_final
2022-04-15 09:57:10	ga_s2am_ard_3-2-1_55HBV_2022-04-15_final
2022-04-15 09:57:11	ga_s2am_ard_3-2-1_54HYE_2022-04-15_final
2022-04-15 09:57:15	ga_s2am_ard_3-2-1_54HXE_2022-04-15_final
2022-04-15 09:57:29	ga_s2am_ard_3-2-1_54HXD_2022-04-15_final
2022-04-15 09:57:35	ga_s2am_ard_3-2-1_55HCT_2022-04-15_final
2022-04-15 09:57:39	ga_s2am_ard_3-2-1_55HBT_2022-04-15_final
2022-04-15 09:57:40	ga_s2am_ard_3-2-1_54HYC_2022-04-15_final
2022-04-15 09:57:44	ga_s2am_ard_3-2-1_54HXC_2022-04-15_final
2022-04-15 09:57:48	ga_s2am_ard_3-2-1_54HWC_2022-04-15_final
2022-04-15 09:57:54	ga_s2am_ard_3-2-1_54HYB_2022-04-15_final
2022-04-15 09:58:17	ga_s2am_ard_3-2-1_55GCQ_2022-04-15_final
2022-04-15 09:58:22	ga_s2am_ard_3-2-1_54GYV_2022-04-15_final.stac-item
2022-04-15 11:31:34	ga_s2am_ard_3-2-1_51LWE_2022-04-15_final
2022-04-15 11:31:52	ga_s2am_ard_3-2-1_51LZC_2022-04-15_final
2022-04-15 11:31:56	ga_s2am_ard_3-2-1_51LYC_2022-04-15_final
2022-04-15 11:32:29	ga_s2am_ard_3-2-1_51KXA_2022-04-15_final
2022-04-15 11:32:32	ga_s2am_ard_3-2-1_51KWA_2022-04-15_final
2022-04-15 11:32:47	ga_s2am_ard_3-2-1_51KWV_2022-04-15_final
2022-04-15 11:32:50	ga_s2am_ard_3-2-1_51KVV_2022-04-15_final
2022-04-15 11:32:54	ga_s2am_ard_3-2-1_51KYU_2022-04-15_final
2022-04-15 11:32:58	ga_s2am_ard_3-2-1_51KXU_2022-04-15_final
2022-04-15 11:33:01	ga_s2am_ard_3-2-1_51KWU_2022-04-15_final
2022-04-15 11:33:05	ga_s2am_ard_3-2-1_51KVU_2022-04-15_final
2022-04-15 11:33:12	ga_s2am_ard_3-2-1_51KXT_2022-04-15_final
2022-04-15 11:33:16	ga_s2am_ard_3-2-1_51KWT_2022-04-15_final
2022-04-15 11:33:19	ga_s2am_ard_3-2-1_51KVT_2022-04-15_final
2022-04-15 11:33:25	ga_s2am_ard_3-2-1_51KUT_2022-04-15_final
2022-04-15 11:34:08	ga_s2am_ard_3-2-1_51KXP_2022-04-15_final
2022-04-15 11:34:14	ga_s2am_ard_3-2-1_51KWP_2022-04-15_final
2022-04-15 11:34:17	ga_s2am_ard_3-2-1_51KVP_2022-04-15_final
2022-04-15 11:34:21	ga_s2am_ard_3-2-1_51KUP_2022-04-15_final
2022-04-15 11:34:43	ga_s2am_ard_3-2-1_51JWM_2022-04-15_final
2022-04-15 11:34:46	ga_s2am_ard_3-2-1_51JVM_2022-04-15_final
2022-04-15 11:34:52	ga_s2am_ard_3-2-1_51JTM_2022-04-15_final
2022-04-15 11:34:57	ga_s2am_ard_3-2-1_51JWL_2022-04-15_final
2022-04-15 11:35:01	ga_s2am_ard_3-2-1_51JVL_2022-04-15_final
2022-04-15 11:35:04	ga_s2am_ard_3-2-1_51JUL_2022-04-15_final
2022-04-15 11:35:22	ga_s2am_ard_3-2-1_51JWJ_2022-04-15_final
2022-04-15 11:35:30	ga_s2am_ard_3-2-1_51JVJ_2022-04-15_final
2022-04-15 11:35:44	ga_s2am_ard_3-2-1_51JVH_2022-04-15_final
2022-04-15 11:35:48	ga_s2am_ard_3-2-1_51JUH_2022-04-15_final
2022-04-15 11:35:59	ga_s2am_ard_3-2-1_51JVG_2022-04-15_final
2022-04-15 11:36:08	ga_s2am_ard_3-2-1_50JQM_2022-04-15_final
2022-04-15 11:36:31	ga_s2am_ard_3-2-1_51HUE_2022-04-15_final
2022-04-15 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2022-04-15_final
2022-04-15 11:37:04	ga_s2am_ard_3-2-1_51HTC_2022-04-15_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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