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
2019-08-04 10:45:15	ga_s2am_ard_3-2-1_53JLJ_2019-08-04_final
2019-08-04 10:45:18	ga_s2am_ard_3-2-1_53JKJ_2019-08-04_final
2019-08-04 10:45:30	ga_s2am_ard_3-2-1_53JLH_2019-08-04_final
2019-08-04 10:45:33	ga_s2am_ard_3-2-1_53JKH_2019-08-04_final
2019-08-04 10:45:36	ga_s2am_ard_3-2-1_53JNG_2019-08-04_final
2019-08-04 10:45:41	ga_s2am_ard_3-2-1_53JMG_2019-08-04_final
2019-08-04 10:45:45	ga_s2am_ard_3-2-1_53JLG_2019-08-04_final
2019-08-04 10:45:46	ga_s2am_ard_3-2-1_53JNF_2019-08-04_final
2019-08-04 10:45:48	ga_s2am_ard_3-2-1_53JKG_2019-08-04_final
2019-08-04 10:45:56	ga_s2am_ard_3-2-1_53JMF_2019-08-04_final
2019-08-04 10:46:02	ga_s2am_ard_3-2-1_53JKF_2019-08-04_final
2019-08-04 10:46:04	ga_s2am_ard_3-2-1_52JGL_2019-08-04_final
2019-08-04 10:46:10	ga_s2am_ard_3-2-1_53HME_2019-08-04_final
2019-08-04 10:46:17	ga_s2am_ard_3-2-1_53HKE_2019-08-04_final.stac-item
2019-08-04 10:46:19	ga_s2am_ard_3-2-1_52HGK_2019-08-04_final.stac-item
2019-08-04 10:46:25	ga_s2am_ard_3-2-1_53HMD_2019-08-04_final
2019-08-04 10:46:28	ga_s2am_ard_3-2-1_53HLD_2019-08-04_final
2019-08-04 10:46:35	ga_s2am_ard_3-2-1_53HMC_2019-08-04_final.stac-item
2019-08-05 10:10:03	ga_s2am_ard_3-2-1_54LZP_2019-08-05_final
2019-08-05 10:10:55	ga_s2am_ard_3-2-1_55LCE_2019-08-05_final
2019-08-05 10:10:58	ga_s2am_ard_3-2-1_55LBE_2019-08-05_final
2019-08-05 10:10:59	ga_s2am_ard_3-2-1_54LZK_2019-08-05_final
2019-08-05 10:11:04	ga_s2am_ard_3-2-1_54LYK_2019-08-05_final
2019-08-05 10:11:12	ga_s2am_ard_3-2-1_55LBD_2019-08-05_final
2019-08-05 10:11:13	ga_s2am_ard_3-2-1_54LZJ_2019-08-05_final
2019-08-05 10:11:17	ga_s2am_ard_3-2-1_54LYJ_2019-08-05_final
2019-08-05 10:11:23	ga_s2am_ard_3-2-1_55LCC_2019-08-05_final
2019-08-05 10:11:28	ga_s2am_ard_3-2-1_54LZH_2019-08-05_final
2019-08-05 10:11:31	ga_s2am_ard_3-2-1_54LYH_2019-08-05_final
2019-08-05 10:11:38	ga_s2am_ard_3-2-1_55KCB_2019-08-05_final
2019-08-05 10:11:42	ga_s2am_ard_3-2-1_55KBB_2019-08-05_final
2019-08-05 10:11:42	ga_s2am_ard_3-2-1_54KZG_2019-08-05_final
2019-08-05 10:11:46	ga_s2am_ard_3-2-1_54KYG_2019-08-05_final
2019-08-05 10:11:53	ga_s2am_ard_3-2-1_55KCA_2019-08-05_final
2019-08-05 10:12:06	ga_s2am_ard_3-2-1_54KXF_2019-08-05_final
2019-08-05 10:12:07	ga_s2am_ard_3-2-1_55KCV_2019-08-05_final
2019-08-05 10:12:18	ga_s2am_ard_3-2-1_54KXE_2019-08-05_final
2019-08-05 10:12:21	ga_s2am_ard_3-2-1_55KCU_2019-08-05_final
2019-08-05 10:12:25	ga_s2am_ard_3-2-1_55KBU_2019-08-05_final
2019-08-05 10:12:26	ga_s2am_ard_3-2-1_54KZD_2019-08-05_final
2019-08-05 10:12:29	ga_s2am_ard_3-2-1_54KYD_2019-08-05_final
2019-08-05 10:12:32	ga_s2am_ard_3-2-1_55KCT_2019-08-05_final
2019-08-05 10:12:33	ga_s2am_ard_3-2-1_54KXD_2019-08-05_final
2019-08-05 10:12:39	ga_s2am_ard_3-2-1_55KBT_2019-08-05_final
2019-08-05 10:12:40	ga_s2am_ard_3-2-1_54KZC_2019-08-05_final
2019-08-05 10:12:44	ga_s2am_ard_3-2-1_54KYC_2019-08-05_final
2019-08-05 10:12:47	ga_s2am_ard_3-2-1_54KXC_2019-08-05_final
2019-08-05 10:12:54	ga_s2am_ard_3-2-1_55KBS_2019-08-05_final
2019-08-05 10:12:54	ga_s2am_ard_3-2-1_54KZB_2019-08-05_final
2019-08-05 10:12:58	ga_s2am_ard_3-2-1_54KYB_2019-08-05_final
2019-08-05 10:13:09	ga_s2am_ard_3-2-1_54KZA_2019-08-05_final
2019-08-05 10:13:24	ga_s2am_ard_3-2-1_54KZV_2019-08-05_final
2019-08-05 10:13:37	ga_s2am_ard_3-2-1_55KBP_2019-08-05_final
2019-08-05 10:13:38	ga_s2am_ard_3-2-1_54KZU_2019-08-05_final
2019-08-05 10:13:42	ga_s2am_ard_3-2-1_54KYU_2019-08-05_final
2019-08-05 10:13:48	ga_s2am_ard_3-2-1_55JBN_2019-08-05_final
2019-08-05 10:13:49	ga_s2am_ard_3-2-1_54KWU_2019-08-05_final
2019-08-05 10:13:49	ga_s2am_ard_3-2-1_54JZT_2019-08-05_final
2019-08-05 10:13:56	ga_s2am_ard_3-2-1_54JYT_2019-08-05_final
2019-08-05 10:14:00	ga_s2am_ard_3-2-1_54JXT_2019-08-05_final
2019-08-05 10:14:03	ga_s2am_ard_3-2-1_54JWT_2019-08-05_final
2019-08-05 10:14:10	ga_s2am_ard_3-2-1_54JVT_2019-08-05_final
2019-08-05 10:14:14	ga_s2am_ard_3-2-1_54JXS_2019-08-05_final
2019-08-05 10:14:29	ga_s2am_ard_3-2-1_54JXR_2019-08-05_final
2019-08-05 10:14:32	ga_s2am_ard_3-2-1_54JWR_2019-08-05_final
2019-08-05 10:14:35	ga_s2am_ard_3-2-1_54JVR_2019-08-05_final
2019-08-05 10:14:39	ga_s2am_ard_3-2-1_54JYQ_2019-08-05_final
2019-08-05 10:14:43	ga_s2am_ard_3-2-1_54JXQ_2019-08-05_final
2019-08-05 10:14:52	ga_s2am_ard_3-2-1_54JYP_2019-08-05_final
2019-08-05 10:14:58	ga_s2am_ard_3-2-1_54JXP_2019-08-05_final
2019-08-05 10:15:02	ga_s2am_ard_3-2-1_54JYN_2019-08-05_final
2019-08-05 10:15:12	ga_s2am_ard_3-2-1_54JUP_2019-08-05_final
2019-08-05 10:15:12	ga_s2am_ard_3-2-1_54JXN_2019-08-05_final
2019-08-05 10:15:16	ga_s2am_ard_3-2-1_54JWN_2019-08-05_final
2019-08-05 10:15:19	ga_s2am_ard_3-2-1_54JVN_2019-08-05_final
2019-08-05 10:15:23	ga_s2am_ard_3-2-1_54JUN_2019-08-05_final
2019-08-05 10:15:27	ga_s2am_ard_3-2-1_54JXM_2019-08-05_final
2019-08-05 10:15:41	ga_s2am_ard_3-2-1_54JXL_2019-08-05_final
2019-08-05 10:15:45	ga_s2am_ard_3-2-1_54JWL_2019-08-05_final
2019-08-05 10:15:48	ga_s2am_ard_3-2-1_54JVL_2019-08-05_final
2019-08-05 10:16:04	ga_s2am_ard_3-2-1_54HXJ_2019-08-05_final
2019-08-05 10:16:14	ga_s2am_ard_3-2-1_54HWJ_2019-08-05_final
2019-08-05 10:16:18	ga_s2am_ard_3-2-1_54HVJ_2019-08-05_final
2019-08-05 10:16:21	ga_s2am_ard_3-2-1_54HUJ_2019-08-05_final
2019-08-05 10:16:25	ga_s2am_ard_3-2-1_54HTJ_2019-08-05_final
2019-08-05 10:16:28	ga_s2am_ard_3-2-1_54HWH_2019-08-05_final
2019-08-05 10:16:32	ga_s2am_ard_3-2-1_54HVH_2019-08-05_final
2019-08-05 10:16:35	ga_s2am_ard_3-2-1_54HUH_2019-08-05_final
2019-08-05 10:16:43	ga_s2am_ard_3-2-1_54HWG_2019-08-05_final
2019-08-05 10:16:47	ga_s2am_ard_3-2-1_54HVG_2019-08-05_final
2019-08-05 10:16:50	ga_s2am_ard_3-2-1_54HUG_2019-08-05_final
2019-08-05 10:16:53	ga_s2am_ard_3-2-1_54HTG_2019-08-05_final
2019-08-05 10:16:56	ga_s2am_ard_3-2-1_53HQB_2019-08-05_final
2019-08-05 10:16:56	ga_s2am_ard_3-2-1_54HWF_2019-08-05_final
2019-08-05 10:17:01	ga_s2am_ard_3-2-1_54HVF_2019-08-05_final
2019-08-05 10:17:04	ga_s2am_ard_3-2-1_54HUF_2019-08-05_final
2019-08-05 10:17:08	ga_s2am_ard_3-2-1_54HTF_2019-08-05_final
2019-08-05 10:17:09	ga_s2am_ard_3-2-1_53HQA_2019-08-05_final
2019-08-05 10:17:30	ga_s2am_ard_3-2-1_54HVD_2019-08-05_final
2019-08-05 10:17:34	ga_s2am_ard_3-2-1_54HUD_2019-08-05_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

All years