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
2019-10-22 11:12:53	ga_s2am_ard_3-2-1_52KDD_2019-10-22_final
2019-10-22 11:12:56	ga_s2am_ard_3-2-1_52KCD_2019-10-22_final
2019-10-22 11:12:57	ga_s2am_ard_3-2-1_52KFC_2019-10-22_final
2019-10-22 11:13:18	ga_s2am_ard_3-2-1_52KEB_2019-10-22_final
2019-10-22 11:13:22	ga_s2am_ard_3-2-1_52KDB_2019-10-22_final
2019-10-22 11:13:25	ga_s2am_ard_3-2-1_52KCB_2019-10-22_final
2019-10-22 11:13:28	ga_s2am_ard_3-2-1_52KBB_2019-10-22_final
2019-10-22 11:13:32	ga_s2am_ard_3-2-1_51KZS_2019-10-22_final
2019-10-22 11:13:32	ga_s2am_ard_3-2-1_52KCB_2019-10-22_final
2019-10-22 11:13:34	ga_s2am_ard_3-2-1_52KBB_2019-10-22_final
2019-10-22 11:13:34	ga_s2am_ard_3-2-1_52KBA_2019-10-22_final
2019-10-22 11:13:34	ga_s2am_ard_3-2-1_51KZS_2019-10-22_final
2019-10-22 11:13:35	ga_s2am_ard_3-2-1_51KZR_2019-10-22_final
2019-10-22 11:13:43	ga_s2am_ard_3-2-1_52KBA_2019-10-22_final
2019-10-22 11:13:43	ga_s2am_ard_3-2-1_51KZR_2019-10-22_final
2019-10-22 11:13:47	ga_s2am_ard_3-2-1_52KEV_2019-10-22_final
2019-10-22 11:13:51	ga_s2am_ard_3-2-1_52KDV_2019-10-22_final
2019-10-22 11:13:57	ga_s2am_ard_3-2-1_51KZQ_2019-10-22_final
2019-10-22 11:14:11	ga_s2am_ard_3-2-1_52JET_2019-10-22_final
2019-10-22 11:14:12	ga_s2am_ard_3-2-1_51KZP_2019-10-22_final
2019-10-22 11:14:20	ga_s2am_ard_3-2-1_52JDT_2019-10-22_final
2019-10-22 11:14:27	ga_s2am_ard_3-2-1_51JZN_2019-10-22_final
2019-10-22 11:14:27	ga_s2am_ard_3-2-1_52JBT_2019-10-22_final
2019-10-22 11:14:32	ga_s2am_ard_3-2-1_51JYN_2019-10-22_final
2019-10-22 11:14:34	ga_s2am_ard_3-2-1_52JDS_2019-10-22_final
2019-10-22 11:14:41	ga_s2am_ard_3-2-1_51JZM_2019-10-22_final
2019-10-22 11:14:49	ga_s2am_ard_3-2-1_52JDR_2019-10-22_final
2019-10-22 11:14:53	ga_s2am_ard_3-2-1_52JCR_2019-10-22_final
2019-10-22 11:14:56	ga_s2am_ard_3-2-1_52JBR_2019-10-22_final
2019-10-22 11:15:07	ga_s2am_ard_3-2-1_52JCQ_2019-10-22_final
2019-10-22 11:15:15	ga_s2am_ard_3-2-1_52JDP_2019-10-22_final
2019-10-22 11:15:21	ga_s2am_ard_3-2-1_52JCP_2019-10-22_final
2019-10-22 11:15:28	ga_s2am_ard_3-2-1_51JYJ_2019-10-22_final
2019-10-22 11:15:33	ga_s2am_ard_3-2-1_51JXJ_2019-10-22_final
2019-10-22 11:15:40	ga_s2am_ard_3-2-1_52JBN_2019-10-22_final
2019-10-22 11:15:51	ga_s2am_ard_3-2-1_52JCM_2019-10-22_final
2019-10-22 11:15:57	ga_s2am_ard_3-2-1_51JYG_2019-10-22_final
2019-10-22 11:16:00	ga_s2am_ard_3-2-1_51JXG_2019-10-22_final
2019-10-22 11:16:05	ga_s2am_ard_3-2-1_52JCL_2019-10-22_final
2019-10-22 11:16:15	ga_s2am_ard_3-2-1_51JXF_2019-10-22_final
2019-10-22 11:16:19	ga_s2am_ard_3-2-1_52HCK_2019-10-22_final.stac-item
2019-10-22 11:16:23	ga_s2am_ard_3-2-1_51JWF_2019-10-22_final
2019-10-22 11:16:29	ga_s2am_ard_3-2-1_51HXE_2019-10-22_final
2019-10-22 11:16:34	ga_s2am_ard_3-2-1_51HWE_2019-10-22_final
2019-10-23 10:40:43	ga_s2am_ard_3-2-1_53LPG_2019-10-23_final
2019-10-23 10:40:54	ga_s2am_ard_3-2-1_53LQF_2019-10-23_final.stac-item
2019-10-23 10:40:57	ga_s2am_ard_3-2-1_53LPF_2019-10-23_final
2019-10-23 10:41:09	ga_s2am_ard_3-2-1_53LQE_2019-10-23_final.stac-item
2019-10-23 10:41:23	ga_s2am_ard_3-2-1_53LQD_2019-10-23_final
2019-10-23 10:41:41	ga_s2am_ard_3-2-1_53LPC_2019-10-23_final
2019-10-23 10:41:45	ga_s2am_ard_3-2-1_53LNC_2019-10-23_final
2019-10-23 10:41:48	ga_s2am_ard_3-2-1_53KRB_2019-10-23_final
2019-10-23 10:41:55	ga_s2am_ard_3-2-1_53KPB_2019-10-23_final
2019-10-23 10:41:57	ga_s2am_ard_3-2-1_54KTF_2019-10-23_final
2019-10-23 10:41:58	ga_s2am_ard_3-2-1_53KNB_2019-10-23_final
2019-10-23 10:42:03	ga_s2am_ard_3-2-1_53KRA_2019-10-23_final
2019-10-23 10:42:07	ga_s2am_ard_3-2-1_53KQA_2019-10-23_final
2019-10-23 10:42:10	ga_s2am_ard_3-2-1_53KPA_2019-10-23_final
2019-10-23 10:42:13	ga_s2am_ard_3-2-1_53KNA_2019-10-23_final
2019-10-23 10:42:25	ga_s2am_ard_3-2-1_53KPV_2019-10-23_final
2019-10-23 10:42:25	ga_s2am_ard_3-2-1_53KRU_2019-10-23_final
2019-10-23 10:42:28	ga_s2am_ard_3-2-1_53KNV_2019-10-23_final
2019-10-23 10:42:42	ga_s2am_ard_3-2-1_53KNU_2019-10-23_final
2019-10-23 10:42:46	ga_s2am_ard_3-2-1_53KMU_2019-10-23_final
2019-10-23 10:43:04	ga_s2am_ard_3-2-1_53KQS_2019-10-23_final
2019-10-23 10:43:08	ga_s2am_ard_3-2-1_53KPS_2019-10-23_final
2019-10-23 10:43:12	ga_s2am_ard_3-2-1_53KNS_2019-10-23_final
2019-10-23 10:43:15	ga_s2am_ard_3-2-1_53KMS_2019-10-23_final
2019-10-23 10:43:22	ga_s2am_ard_3-2-1_53KPR_2019-10-23_final
2019-10-23 10:43:37	ga_s2am_ard_3-2-1_53KMQ_2019-10-23_final
2019-10-23 10:43:44	ga_s2am_ard_3-2-1_53KMQ_2019-10-23_final
2019-10-23 10:43:55	ga_s2am_ard_3-2-1_53KNP_2019-10-23_final
2019-10-23 10:43:58	ga_s2am_ard_3-2-1_53KMP_2019-10-23_final
2019-10-23 10:44:06	ga_s2am_ard_3-2-1_53JPN_2019-10-23_final
2019-10-23 10:44:10	ga_s2am_ard_3-2-1_53JNN_2019-10-23_final
2019-10-23 10:44:13	ga_s2am_ard_3-2-1_53JMN_2019-10-23_final
2019-10-23 10:44:20	ga_s2am_ard_3-2-1_53JPM_2019-10-23_final
2019-10-23 10:44:24	ga_s2am_ard_3-2-1_53JNM_2019-10-23_final
2019-10-23 10:44:27	ga_s2am_ard_3-2-1_53JMM_2019-10-23_final
2019-10-23 10:44:31	ga_s2am_ard_3-2-1_53JPL_2019-10-23_final
2019-10-23 10:44:38	ga_s2am_ard_3-2-1_53JNL_2019-10-23_final
2019-10-23 10:44:45	ga_s2am_ard_3-2-1_53JLL_2019-10-23_final
2019-10-23 10:44:53	ga_s2am_ard_3-2-1_53JNK_2019-10-23_final
2019-10-23 10:44:57	ga_s2am_ard_3-2-1_53JMK_2019-10-23_final
2019-10-23 10:45:00	ga_s2am_ard_3-2-1_53JLK_2019-10-23_final
2019-10-23 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2019-10-23_final
2019-10-23 10:45:11	ga_s2am_ard_3-2-1_53JMJ_2019-10-23_final
2019-10-23 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2019-10-23_final
2019-10-23 10:45:22	ga_s2am_ard_3-2-1_53JNH_2019-10-23_final
2019-10-23 10:45:26	ga_s2am_ard_3-2-1_53JMH_2019-10-23_final
2019-10-23 10:45:32	ga_s2am_ard_3-2-1_53JKH_2019-10-23_final
2019-10-23 10:45:35	ga_s2am_ard_3-2-1_53JNG_2019-10-23_final
2019-10-23 10:45:40	ga_s2am_ard_3-2-1_53JMG_2019-10-23_final
2019-10-23 10:45:44	ga_s2am_ard_3-2-1_53JLG_2019-10-23_final
2019-10-23 10:45:45	ga_s2am_ard_3-2-1_53JNF_2019-10-23_final
2019-10-23 10:45:50	ga_s2am_ard_3-2-1_52JGM_2019-10-23_final
2019-10-23 10:45:54	ga_s2am_ard_3-2-1_53JMF_2019-10-23_final
2019-10-23 10:45:58	ga_s2am_ard_3-2-1_53JLF_2019-10-23_final
2019-10-23 10:46:09	ga_s2am_ard_3-2-1_53HME_2019-10-23_final
2019-10-23 10:46:13	ga_s2am_ard_3-2-1_53HLE_2019-10-23_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

All years