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
2022-05-28 10:03:02	ga_s2am_ard_3-2-1_55KBS_2022-05-28_final
2022-05-28 10:03:31	ga_s2am_ard_3-2-1_55KBQ_2022-05-28_final
2022-05-28 10:03:39	ga_s2am_ard_3-2-1_54KYV_2022-05-28_final
2022-05-28 10:03:43	ga_s2am_ard_3-2-1_55KCP_2022-05-28_final
2022-05-28 10:03:46	ga_s2am_ard_3-2-1_55KBP_2022-05-28_final
2022-05-28 10:03:50	ga_s2am_ard_3-2-1_54KYU_2022-05-28_final
2022-05-28 10:03:54	ga_s2am_ard_3-2-1_55JDN_2022-05-28_final
2022-05-28 10:04:03	ga_s2am_ard_3-2-1_54JYT_2022-05-28_final
2022-05-28 10:04:21	ga_s2am_ard_3-2-1_55JDL_2022-05-28_final
2022-05-28 10:04:26	ga_s2am_ard_3-2-1_55JCL_2022-05-28_final
2022-05-28 10:04:29	ga_s2am_ard_3-2-1_55JBL_2022-05-28_final
2022-05-28 10:04:31	ga_s2am_ard_3-2-1_55JDK_2022-05-28_final
2022-05-28 10:04:33	ga_s2am_ard_3-2-1_54JYR_2022-05-28_final
2022-05-28 10:04:40	ga_s2am_ard_3-2-1_54JXR_2022-05-28_final
2022-05-28 10:05:13	ga_s2am_ard_3-2-1_55JBH_2022-05-28_final
2022-05-28 10:05:16	ga_s2am_ard_3-2-1_54JYN_2022-05-28_final
2022-05-28 10:05:30	ga_s2am_ard_3-2-1_54JYM_2022-05-28_final
2022-05-28 10:06:21	ga_s2am_ard_3-2-1_54HWJ_2022-05-28_final
2022-05-28 10:06:26	ga_s2am_ard_3-2-1_55HBC_2022-05-28_final
2022-05-28 10:06:28	ga_s2am_ard_3-2-1_54HYH_2022-05-28_final
2022-05-28 10:06:36	ga_s2am_ard_3-2-1_54HWH_2022-05-28_final
2022-05-28 10:06:43	ga_s2am_ard_3-2-1_54HWH_2022-05-28_final
2022-05-28 10:07:03	ga_s2am_ard_3-2-1_55HBV_2022-05-28_final
2022-05-28 10:07:05	ga_s2am_ard_3-2-1_54HWF_2022-05-28_final
2022-05-28 10:07:08	ga_s2am_ard_3-2-1_54HVF_2022-05-28_final
2022-05-28 10:07:11	ga_s2am_ard_3-2-1_54HYE_2022-05-28_final
2022-05-28 10:07:15	ga_s2am_ard_3-2-1_54HXE_2022-05-28_final
2022-05-28 10:07:19	ga_s2am_ard_3-2-1_54HWE_2022-05-28_final
2022-05-28 10:07:22	ga_s2am_ard_3-2-1_54HYD_2022-05-28_final
2022-05-28 10:07:23	ga_s2am_ard_3-2-1_54HVE_2022-05-28_final
2022-05-28 10:07:29	ga_s2am_ard_3-2-1_54HXD_2022-05-28_final
2022-05-28 10:07:42	ga_s2am_ard_3-2-1_54HUD_2022-05-28_final.stac-item
2022-05-28 11:41:23	ga_s2am_ard_3-2-1_51LVF_2022-05-28_final
2022-05-28 11:41:26	ga_s2am_ard_3-2-1_51LUF_2022-05-28_final
2022-05-28 11:41:55	ga_s2am_ard_3-2-1_51LUD_2022-05-28_final.stac-item
2022-05-28 11:43:04	ga_s2am_ard_3-2-1_51KVU_2022-05-28_final
2022-05-28 11:43:25	ga_s2am_ard_3-2-1_51KTT_2022-05-28_final
2022-05-28 11:43:29	ga_s2am_ard_3-2-1_50KQC_2022-05-28_final
2022-05-28 11:43:40	ga_s2am_ard_3-2-1_51KTS_2022-05-28_final
2022-05-28 11:43:44	ga_s2am_ard_3-2-1_50KQB_2022-05-28_final
2022-05-28 11:44:09	ga_s2am_ard_3-2-1_51KTQ_2022-05-28_final
2022-05-28 11:44:13	ga_s2am_ard_3-2-1_50KQV_2022-05-28_final
2022-05-28 11:44:20	ga_s2am_ard_3-2-1_51KUP_2022-05-28_final
2022-05-28 11:44:24	ga_s2am_ard_3-2-1_51KTP_2022-05-28_final
2022-05-28 11:44:27	ga_s2am_ard_3-2-1_50KQU_2022-05-28_final
2022-05-28 11:44:31	ga_s2am_ard_3-2-1_50KPU_2022-05-28_final
2022-05-28 11:44:38	ga_s2am_ard_3-2-1_51JTN_2022-05-28_final
2022-05-28 11:44:42	ga_s2am_ard_3-2-1_50JQT_2022-05-28_final
2022-05-28 11:44:58	ga_s2am_ard_3-2-1_51JUL_2022-05-28_final
2022-05-28 11:45:07	ga_s2am_ard_3-2-1_51JTL_2022-05-28_final
2022-05-28 11:45:11	ga_s2am_ard_3-2-1_50JQR_2022-05-28_final
2022-05-28 11:45:14	ga_s2am_ard_3-2-1_50JPR_2022-05-28_final
2022-05-28 11:45:19	ga_s2am_ard_3-2-1_50JNR_2022-05-28_final
2022-05-28 11:45:32	ga_s2am_ard_3-2-1_50JNQ_2022-05-28_final
2022-05-28 11:45:41	ga_s2am_ard_3-2-1_50JNP_2022-05-28_final
2022-05-28 11:45:43	ga_s2am_ard_3-2-1_51JTH_2022-05-28_final
2022-05-28 11:45:49	ga_s2am_ard_3-2-1_50JNP_2022-05-28_final
2022-05-28 11:45:51	ga_s2am_ard_3-2-1_51JTH_2022-05-28_final
2022-05-28 11:45:54	ga_s2am_ard_3-2-1_50JQN_2022-05-28_final
2022-05-28 11:46:01	ga_s2am_ard_3-2-1_50JNN_2022-05-28_final
2022-05-28 11:46:04	ga_s2am_ard_3-2-1_51JTG_2022-05-28_final
2022-05-28 11:46:08	ga_s2am_ard_3-2-1_50JQM_2022-05-28_final
2022-05-28 11:46:16	ga_s2am_ard_3-2-1_50JNM_2022-05-28_final
2022-05-28 11:46:20	ga_s2am_ard_3-2-1_50JMM_2022-05-28_final
2022-05-28 11:46:59	ga_s2am_ard_3-2-1_50HNJ_2022-05-28_final
2022-05-28 11:47:01	ga_s2am_ard_3-2-1_50HQH_2022-05-28_final
2022-05-28 11:47:03	ga_s2am_ard_3-2-1_50HMJ_2022-05-28_final
2022-05-29 09:33:35	ga_s2am_ard_3-2-1_56KLU_2022-05-29_final
2022-05-29 09:33:43	ga_s2am_ard_3-2-1_56JNT_2022-05-29_final
2022-05-29 09:33:47	ga_s2am_ard_3-2-1_56JMT_2022-05-29_final
2022-05-29 09:34:12	ga_s2am_ard_3-2-1_56JNR_2022-05-29_final.stac-item
2022-05-29 09:34:16	ga_s2am_ard_3-2-1_56JMR_2022-05-29_final
2022-05-29 09:34:19	ga_s2am_ard_3-2-1_56JLR_2022-05-29_final
2022-05-29 09:34:22	ga_s2am_ard_3-2-1_56JKR_2022-05-29_final
2022-05-29 09:34:27	ga_s2am_ard_3-2-1_56JNQ_2022-05-29_final.stac-item
2022-05-29 09:34:30	ga_s2am_ard_3-2-1_56JMQ_2022-05-29_final
2022-05-29 09:35:06	ga_s2am_ard_3-2-1_56JKN_2022-05-29_final
2022-05-29 09:35:09	ga_s2am_ard_3-2-1_55JGH_2022-05-29_final
2022-05-29 09:35:20	ga_s2am_ard_3-2-1_56JKM_2022-05-29_final
2022-05-29 09:35:23	ga_s2am_ard_3-2-1_55JGG_2022-05-29_final
2022-05-29 09:35:56	ga_s2am_ard_3-2-1_56HMJ_2022-05-29_final
2022-05-29 09:36:19	ga_s2am_ard_3-2-1_56HKH_2022-05-29_final
2022-05-29 09:36:21	ga_s2am_ard_3-2-1_55HGC_2022-05-29_final
2022-05-29 09:36:58	ga_s2am_ard_3-2-1_55HEA_2022-05-29_final
2022-05-29 09:37:04	ga_s2am_ard_3-2-1_55HGV_2022-05-29_final
2022-05-29 09:37:08	ga_s2am_ard_3-2-1_55HFV_2022-05-29_final
2022-05-29 09:37:11	ga_s2am_ard_3-2-1_55HEV_2022-05-29_final
2022-05-29 09:37:18	ga_s2am_ard_3-2-1_55HGU_2022-05-29_final.stac-item
2022-05-29 09:37:22	ga_s2am_ard_3-2-1_55HFU_2022-05-29_final.stac-item
2022-05-29 09:37:55	ga_s2am_ard_3-2-1_55HES_2022-05-29_final
2022-05-29 09:37:59	ga_s2am_ard_3-2-1_55HDS_2022-05-29_final
2022-05-29 09:38:34	ga_s2am_ard_3-2-1_55GFP_2022-05-29_final
2022-05-29 09:38:42	ga_s2am_ard_3-2-1_55GDP_2022-05-29_final
2022-05-29 09:38:48	ga_s2am_ard_3-2-1_55GCP_2022-05-29_final
2022-05-29 09:38:48	ga_s2am_ard_3-2-1_55GFN_2022-05-29_final
2022-05-29 09:38:53	ga_s2am_ard_3-2-1_55GEN_2022-05-29_final
2022-05-29 09:38:56	ga_s2am_ard_3-2-1_55GDN_2022-05-29_final
2022-05-29 09:39:00	ga_s2am_ard_3-2-1_55GCN_2022-05-29_final
2022-05-29 09:39:07	ga_s2am_ard_3-2-1_55GEM_2022-05-29_final.stac-item
2022-05-29 09:39:10	ga_s2am_ard_3-2-1_55GDM_2022-05-29_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