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
2022-05-11 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-05-11_final
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final
2022-05-11 11:57:24	ga_s2am_ard_3-2-1_50HMG_2022-05-11_final.stac-item
2022-05-12 09:41:36	ga_s2am_ard_3-2-1_55KHB_2022-05-12_final.stac-item
2022-05-12 09:41:45	ga_s2am_ard_3-2-1_56KLF_2022-05-12_final
2022-05-12 09:41:56	ga_s2am_ard_3-2-1_56KME_2022-05-12_final.stac-item
2022-05-12 09:41:59	ga_s2am_ard_3-2-1_56KLE_2022-05-12_final
2022-05-12 09:42:53	ga_s2am_ard_3-2-1_56KMA_2022-05-12_final
2022-05-12 09:43:15	ga_s2am_ard_3-2-1_56KKV_2022-05-12_final
2022-05-12 09:43:19	ga_s2am_ard_3-2-1_55KGQ_2022-05-12_final
2022-05-12 09:43:26	ga_s2am_ard_3-2-1_56KLU_2022-05-12_final
2022-05-12 09:43:30	ga_s2am_ard_3-2-1_56KKU_2022-05-12_final
2022-05-12 09:43:34	ga_s2am_ard_3-2-1_55KGP_2022-05-12_final
2022-05-12 09:43:38	ga_s2am_ard_3-2-1_55KFP_2022-05-12_final
2022-05-12 09:43:45	ga_s2am_ard_3-2-1_56JKT_2022-05-12_final
2022-05-12 09:43:48	ga_s2am_ard_3-2-1_55JGN_2022-05-12_final
2022-05-12 09:43:56	ga_s2am_ard_3-2-1_56JLS_2022-05-12_final
2022-05-12 09:44:06	ga_s2am_ard_3-2-1_55JFM_2022-05-12_final
2022-05-12 09:44:09	ga_s2am_ard_3-2-1_56JLR_2022-05-12_final
2022-05-12 09:44:14	ga_s2am_ard_3-2-1_56JKR_2022-05-12_final
2022-05-12 09:44:17	ga_s2am_ard_3-2-1_55JGL_2022-05-12_final
2022-05-12 09:44:21	ga_s2am_ard_3-2-1_55JFL_2022-05-12_final
2022-05-12 09:44:29	ga_s2am_ard_3-2-1_55JEL_2022-05-12_final
2022-05-12 09:44:57	ga_s2am_ard_3-2-1_56JKN_2022-05-12_final
2022-05-12 09:45:12	ga_s2am_ard_3-2-1_56JKM_2022-05-12_final
2022-05-12 09:45:15	ga_s2am_ard_3-2-1_55JGG_2022-05-12_final
2022-05-12 09:45:22	ga_s2am_ard_3-2-1_55JEG_2022-05-12_final
2022-05-12 09:45:30	ga_s2am_ard_3-2-1_55JDG_2022-05-12_final
2022-05-12 09:46:06	ga_s2am_ard_3-2-1_55HED_2022-05-12_final
2022-05-12 09:46:11	ga_s2am_ard_3-2-1_55HGC_2022-05-12_final
2022-05-12 09:46:16	ga_s2am_ard_3-2-1_55HFC_2022-05-12_final
2022-05-12 09:46:20	ga_s2am_ard_3-2-1_55HEC_2022-05-12_final
2022-05-12 09:46:21	ga_s2am_ard_3-2-1_55HGB_2022-05-12_final
2022-05-12 09:46:31	ga_s2am_ard_3-2-1_55HCC_2022-05-12_final
2022-05-12 09:46:35	ga_s2am_ard_3-2-1_55HEB_2022-05-12_final
2022-05-12 09:46:38	ga_s2am_ard_3-2-1_55HDB_2022-05-12_final
2022-05-12 09:46:42	ga_s2am_ard_3-2-1_55HCB_2022-05-12_final
2022-05-12 09:46:49	ga_s2am_ard_3-2-1_55HEA_2022-05-12_final
2022-05-12 09:46:53	ga_s2am_ard_3-2-1_55HDA_2022-05-12_final
2022-05-12 09:47:00	ga_s2am_ard_3-2-1_55HFV_2022-05-12_final
2022-05-12 09:47:04	ga_s2am_ard_3-2-1_55HEV_2022-05-12_final
2022-05-12 09:47:07	ga_s2am_ard_3-2-1_55HDV_2022-05-12_final
2022-05-12 09:47:10	ga_s2am_ard_3-2-1_55HCV_2022-05-12_final
2022-05-12 09:47:47	ga_s2am_ard_3-2-1_55HES_2022-05-12_final
2022-05-12 09:47:54	ga_s2am_ard_3-2-1_55HCS_2022-05-12_final
2022-05-12 09:47:57	ga_s2am_ard_3-2-1_55HBS_2022-05-12_final
2022-05-12 09:48:25	ga_s2am_ard_3-2-1_55GEP_2022-05-12_final
2022-05-12 09:48:34	ga_s2am_ard_3-2-1_55GDP_2022-05-12_final
2022-05-12 09:48:38	ga_s2am_ard_3-2-1_55GCP_2022-05-12_final
2022-05-12 09:48:49	ga_s2am_ard_3-2-1_55GDN_2022-05-12_final
2022-05-12 09:48:52	ga_s2am_ard_3-2-1_55GCN_2022-05-12_final
2022-05-12 11:21:01	ga_s2am_ard_3-2-1_52LEL_2022-05-12_final.stac-item
2022-05-12 11:21:28	ga_s2am_ard_3-2-1_52LBK_2022-05-12_final
2022-05-12 11:21:29	ga_s2am_ard_3-2-1_51LZE_2022-05-12_final
2022-05-12 11:21:35	ga_s2am_ard_3-2-1_52LDJ_2022-05-12_final
2022-05-12 11:21:39	ga_s2am_ard_3-2-1_52LCJ_2022-05-12_final
2022-05-12 11:21:53	ga_s2am_ard_3-2-1_52LCH_2022-05-12_final
2022-05-12 11:21:57	ga_s2am_ard_3-2-1_52LBH_2022-05-12_final
2022-05-12 11:21:58	ga_s2am_ard_3-2-1_51LZC_2022-05-12_final
2022-05-12 11:22:02	ga_s2am_ard_3-2-1_51LYC_2022-05-12_final
2022-05-12 11:22:11	ga_s2am_ard_3-2-1_52KBG_2022-05-12_final
2022-05-12 11:22:12	ga_s2am_ard_3-2-1_51KZB_2022-05-12_final
2022-05-12 11:22:15	ga_s2am_ard_3-2-1_51KYB_2022-05-12_final
2022-05-12 11:22:22	ga_s2am_ard_3-2-1_52KCF_2022-05-12_final
2022-05-12 11:22:37	ga_s2am_ard_3-2-1_52KCE_2022-05-12_final
2022-05-12 11:22:55	ga_s2am_ard_3-2-1_52KBD_2022-05-12_final
2022-05-12 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-05-12_final
2022-05-12 11:23:17	ga_s2am_ard_3-2-1_51KXT_2022-05-12_final
2022-05-12 11:23:53	ga_s2am_ard_3-2-1_52KBV_2022-05-12_final
2022-05-12 11:23:57	ga_s2am_ard_3-2-1_51KYQ_2022-05-12_final
2022-05-12 11:24:08	ga_s2am_ard_3-2-1_52KBU_2022-05-12_final
2022-05-12 11:24:11	ga_s2am_ard_3-2-1_51KYP_2022-05-12_final
2022-05-12 11:24:15	ga_s2am_ard_3-2-1_51KXP_2022-05-12_final
2022-05-12 11:24:18	ga_s2am_ard_3-2-1_51KWP_2022-05-12_final
2022-05-12 11:24:22	ga_s2am_ard_3-2-1_52JBT_2022-05-12_final
2022-05-12 11:24:26	ga_s2am_ard_3-2-1_51JYN_2022-05-12_final
2022-05-12 11:24:44	ga_s2am_ard_3-2-1_51JXM_2022-05-12_final
2022-05-12 11:24:47	ga_s2am_ard_3-2-1_52JBR_2022-05-12_final
2022-05-12 11:24:55	ga_s2am_ard_3-2-1_51JYL_2022-05-12_final
2022-05-12 11:24:59	ga_s2am_ard_3-2-1_51JXL_2022-05-12_final
2022-05-12 11:25:02	ga_s2am_ard_3-2-1_51JWL_2022-05-12_final
2022-05-12 11:25:07	ga_s2am_ard_3-2-1_51JVL_2022-05-12_final
2022-05-12 11:25:16	ga_s2am_ard_3-2-1_51JWK_2022-05-12_final
2022-05-12 11:25:20	ga_s2am_ard_3-2-1_51JVK_2022-05-12_final
2022-05-12 11:25:31	ga_s2am_ard_3-2-1_51JWJ_2022-05-12_final
2022-05-12 11:25:34	ga_s2am_ard_3-2-1_51JVJ_2022-05-12_final
2022-05-12 11:25:46	ga_s2am_ard_3-2-1_51JWH_2022-05-12_final
2022-05-12 11:25:48	ga_s2am_ard_3-2-1_51JYG_2022-05-12_final
2022-05-12 11:25:49	ga_s2am_ard_3-2-1_51JVH_2022-05-12_final
2022-05-12 11:26:00	ga_s2am_ard_3-2-1_51JWG_2022-05-12_final
2022-05-12 11:26:04	ga_s2am_ard_3-2-1_51JVG_2022-05-12_final
2022-05-12 11:26:09	ga_s2am_ard_3-2-1_51JUG_2022-05-12_final
2022-05-12 11:26:18	ga_s2am_ard_3-2-1_51JVF_2022-05-12_final
2022-05-12 11:26:51	ga_s2am_ard_3-2-1_51HUD_2022-05-12_final
2022-05-12 11:26:51	ga_s2am_ard_3-2-1_51HXC_2022-05-12_final.stac-item
2022-05-12 11:26:58	ga_s2am_ard_3-2-1_51HWC_2022-05-12_final.stac-item
2022-05-12 11:27:02	ga_s2am_ard_3-2-1_51HVC_2022-05-12_final
2022-05-12 11:27:05	ga_s2am_ard_3-2-1_51HUC_2022-05-12_final
2022-05-12 11:27:11	ga_s2am_ard_3-2-1_51HTC_2022-05-12_final
2022-05-12 11:27:14	ga_s2am_ard_3-2-1_51HVB_2022-05-12_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