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
2022-02-14 11:31:24	ga_s2am_ard_3-2-1_51LYE_2022-02-14_final
2022-02-14 11:31:31	ga_s2am_ard_3-2-1_51LWE_2022-02-14_final
2022-02-14 11:31:39	ga_s2am_ard_3-2-1_51LYD_2022-02-14_final
2022-02-14 11:31:42	ga_s2am_ard_3-2-1_51LXD_2022-02-14_final
2022-02-14 11:31:53	ga_s2am_ard_3-2-1_51LYC_2022-02-14_final
2022-02-14 11:31:57	ga_s2am_ard_3-2-1_51LXC_2022-02-14_final
2022-02-14 11:31:59	ga_s2am_ard_3-2-1_51KZB_2022-02-14_final
2022-02-14 11:32:00	ga_s2am_ard_3-2-1_51LWC_2022-02-14_final
2022-02-14 11:32:07	ga_s2am_ard_3-2-1_51KYB_2022-02-14_final
2022-02-14 11:32:11	ga_s2am_ard_3-2-1_51KXB_2022-02-14_final
2022-02-14 11:32:15	ga_s2am_ard_3-2-1_51KWB_2022-02-14_final
2022-02-14 11:32:19	ga_s2am_ard_3-2-1_51KVB_2022-02-14_final
2022-02-14 11:32:22	ga_s2am_ard_3-2-1_51KYA_2022-02-14_final
2022-02-14 11:32:26	ga_s2am_ard_3-2-1_51KXA_2022-02-14_final
2022-02-14 11:32:29	ga_s2am_ard_3-2-1_51KWA_2022-02-14_final
2022-02-14 11:32:32	ga_s2am_ard_3-2-1_51KVA_2022-02-14_final
2022-02-14 11:32:37	ga_s2am_ard_3-2-1_51KYV_2022-02-14_final
2022-02-14 11:32:40	ga_s2am_ard_3-2-1_51KXV_2022-02-14_final
2022-02-14 11:32:44	ga_s2am_ard_3-2-1_51KWV_2022-02-14_final
2022-02-14 11:32:47	ga_s2am_ard_3-2-1_51KVV_2022-02-14_final
2022-02-14 11:32:50	ga_s2am_ard_3-2-1_51KYU_2022-02-14_final
2022-02-14 11:32:55	ga_s2am_ard_3-2-1_51KXU_2022-02-14_final
2022-02-14 11:32:58	ga_s2am_ard_3-2-1_51KWU_2022-02-14_final
2022-02-14 11:33:01	ga_s2am_ard_3-2-1_51KVU_2022-02-14_final
2022-02-14 11:33:02	ga_s2am_ard_3-2-1_51KYT_2022-02-14_final
2022-02-14 11:33:09	ga_s2am_ard_3-2-1_51KXT_2022-02-14_final
2022-02-14 11:33:13	ga_s2am_ard_3-2-1_51KWT_2022-02-14_final
2022-02-14 11:33:16	ga_s2am_ard_3-2-1_51KVT_2022-02-14_final
2022-02-14 11:33:22	ga_s2am_ard_3-2-1_51KUT_2022-02-14_final
2022-02-14 11:33:23	ga_s2am_ard_3-2-1_51KXS_2022-02-14_final
2022-02-14 11:33:27	ga_s2am_ard_3-2-1_51KWS_2022-02-14_final
2022-02-14 11:33:30	ga_s2am_ard_3-2-1_51KVS_2022-02-14_final
2022-02-14 11:33:34	ga_s2am_ard_3-2-1_51KUS_2022-02-14_final
2022-02-14 11:33:38	ga_s2am_ard_3-2-1_51KXR_2022-02-14_final
2022-02-14 11:33:42	ga_s2am_ard_3-2-1_51KWR_2022-02-14_final
2022-02-14 11:33:45	ga_s2am_ard_3-2-1_51KVR_2022-02-14_final
2022-02-14 11:33:48	ga_s2am_ard_3-2-1_51KUR_2022-02-14_final
2022-02-14 11:33:52	ga_s2am_ard_3-2-1_51KXQ_2022-02-14_final
2022-02-14 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2022-02-14_final
2022-02-14 11:34:00	ga_s2am_ard_3-2-1_51KVQ_2022-02-14_final
2022-02-14 11:34:03	ga_s2am_ard_3-2-1_51KUQ_2022-02-14_final
2022-02-14 11:34:05	ga_s2am_ard_3-2-1_51KXP_2022-02-14_final
2022-02-14 11:34:11	ga_s2am_ard_3-2-1_51KWP_2022-02-14_final
2022-02-14 11:34:14	ga_s2am_ard_3-2-1_51KVP_2022-02-14_final
2022-02-14 11:34:15	ga_s2am_ard_3-2-1_51JXN_2022-02-14_final
2022-02-14 11:34:17	ga_s2am_ard_3-2-1_51KUP_2022-02-14_final
2022-02-14 11:34:25	ga_s2am_ard_3-2-1_51JWN_2022-02-14_final
2022-02-14 11:34:29	ga_s2am_ard_3-2-1_51JVN_2022-02-14_final
2022-02-14 11:34:32	ga_s2am_ard_3-2-1_51JUN_2022-02-14_final
2022-02-14 11:34:36	ga_s2am_ard_3-2-1_51JTN_2022-02-14_final
2022-02-14 11:34:37	ga_s2am_ard_3-2-1_50JRT_2022-02-14_final
2022-02-14 11:34:40	ga_s2am_ard_3-2-1_51JWM_2022-02-14_final
2022-02-14 11:34:43	ga_s2am_ard_3-2-1_51JVM_2022-02-14_final
2022-02-14 11:34:46	ga_s2am_ard_3-2-1_51JUM_2022-02-14_final
2022-02-14 11:34:49	ga_s2am_ard_3-2-1_50JRS_2022-02-14_final
2022-02-14 11:34:49	ga_s2am_ard_3-2-1_51JTM_2022-02-14_final
2022-02-14 11:34:54	ga_s2am_ard_3-2-1_51JWL_2022-02-14_final
2022-02-14 11:34:58	ga_s2am_ard_3-2-1_51JVL_2022-02-14_final
2022-02-14 11:35:01	ga_s2am_ard_3-2-1_51JUL_2022-02-14_final
2022-02-14 11:35:04	ga_s2am_ard_3-2-1_51JTL_2022-02-14_final
2022-02-14 11:35:08	ga_s2am_ard_3-2-1_51JWK_2022-02-14_final
2022-02-14 11:35:12	ga_s2am_ard_3-2-1_51JVK_2022-02-14_final
2022-02-14 11:35:16	ga_s2am_ard_3-2-1_51JUK_2022-02-14_final
2022-02-14 11:35:19	ga_s2am_ard_3-2-1_51JTK_2022-02-14_final
2022-02-14 11:35:19	ga_s2am_ard_3-2-1_51JWJ_2022-02-14_final
2022-02-14 11:35:26	ga_s2am_ard_3-2-1_51JVJ_2022-02-14_final
2022-02-14 11:35:30	ga_s2am_ard_3-2-1_51JUJ_2022-02-14_final
2022-02-14 11:35:33	ga_s2am_ard_3-2-1_51JTJ_2022-02-14_final
2022-02-14 11:35:37	ga_s2am_ard_3-2-1_50JQP_2022-02-14_final
2022-02-14 11:35:41	ga_s2am_ard_3-2-1_51JVH_2022-02-14_final
2022-02-14 11:35:45	ga_s2am_ard_3-2-1_51JUH_2022-02-14_final
2022-02-14 11:35:48	ga_s2am_ard_3-2-1_51JTH_2022-02-14_final
2022-02-14 11:35:50	ga_s2am_ard_3-2-1_50JQN_2022-02-14_final
2022-02-14 11:35:56	ga_s2am_ard_3-2-1_51JVG_2022-02-14_final
2022-02-14 11:35:59	ga_s2am_ard_3-2-1_51JUG_2022-02-14_final
2022-02-14 11:36:02	ga_s2am_ard_3-2-1_51JTG_2022-02-14_final
2022-02-14 11:36:05	ga_s2am_ard_3-2-1_50JQM_2022-02-14_final
2022-02-14 11:36:10	ga_s2am_ard_3-2-1_51JVF_2022-02-14_final
2022-02-14 11:36:14	ga_s2am_ard_3-2-1_51JUF_2022-02-14_final
2022-02-14 11:36:17	ga_s2am_ard_3-2-1_51JTF_2022-02-14_final
2022-02-14 11:36:20	ga_s2am_ard_3-2-1_50JQL_2022-02-14_final
2022-02-14 11:36:23	ga_s2am_ard_3-2-1_51HVE_2022-02-14_final
2022-02-14 11:36:26	ga_s2am_ard_3-2-1_50JPL_2022-02-14_final
2022-02-14 11:36:28	ga_s2am_ard_3-2-1_51HUE_2022-02-14_final
2022-02-14 11:36:32	ga_s2am_ard_3-2-1_51HTE_2022-02-14_final
2022-02-14 11:36:34	ga_s2am_ard_3-2-1_51HVD_2022-02-14_final
2022-02-14 11:36:34	ga_s2am_ard_3-2-1_50HQK_2022-02-14_final
2022-02-14 11:36:38	ga_s2am_ard_3-2-1_50HPK_2022-02-14_final
2022-02-14 11:36:43	ga_s2am_ard_3-2-1_51HUD_2022-02-14_final
2022-02-14 11:36:46	ga_s2am_ard_3-2-1_51HTD_2022-02-14_final
2022-02-14 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2022-02-14_final
2022-02-14 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2022-02-14_final
2022-02-14 11:36:57	ga_s2am_ard_3-2-1_51HUC_2022-02-14_final
2022-02-14 11:37:01	ga_s2am_ard_3-2-1_51HTC_2022-02-14_final
2022-02-14 11:37:03	ga_s2am_ard_3-2-1_50HQH_2022-02-14_final
2022-02-14 11:37:07	ga_s2am_ard_3-2-1_50HPH_2022-02-14_final
2022-02-14 11:37:12	ga_s2am_ard_3-2-1_51HUB_2022-02-14_final.stac-item
2022-02-14 11:37:15	ga_s2am_ard_3-2-1_51HTB_2022-02-14_final.stac-item
2022-02-14 11:37:17	ga_s2am_ard_3-2-1_50HQG_2022-02-14_final.stac-item
2022-02-14 11:37:21	ga_s2am_ard_3-2-1_50HPG_2022-02-14_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

Other products

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