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
2022-07-11 11:24:32	ga_s2am_ard_3-2-1_52JBT_2022-07-11_final
2022-07-11 11:24:32	ga_s2am_ard_3-2-1_51JZN_2022-07-11_final
2022-07-11 11:24:35	ga_s2am_ard_3-2-1_51JYN_2022-07-11_final
2022-07-11 11:24:45	ga_s2am_ard_3-2-1_51JZM_2022-07-11_final
2022-07-11 11:24:45	ga_s2am_ard_3-2-1_52JBS_2022-07-11_final
2022-07-11 11:24:50	ga_s2am_ard_3-2-1_51JYM_2022-07-11_final
2022-07-11 11:24:53	ga_s2am_ard_3-2-1_51JXM_2022-07-11_final
2022-07-11 11:24:56	ga_s2am_ard_3-2-1_52JBR_2022-07-11_final
2022-07-11 11:25:08	ga_s2am_ard_3-2-1_51JXL_2022-07-11_final
2022-07-11 11:25:22	ga_s2am_ard_3-2-1_51JXK_2022-07-11_final
2022-07-11 11:25:26	ga_s2am_ard_3-2-1_51JWK_2022-07-11_final
2022-07-11 11:25:29	ga_s2am_ard_3-2-1_51JVK_2022-07-11_final
2022-07-11 11:25:41	ga_s2am_ard_3-2-1_51JWJ_2022-07-11_final
2022-07-11 11:25:44	ga_s2am_ard_3-2-1_51JVJ_2022-07-11_final
2022-07-11 11:25:55	ga_s2am_ard_3-2-1_51JWH_2022-07-11_final
2022-07-11 11:25:57	ga_s2am_ard_3-2-1_51JYG_2022-07-11_final
2022-07-11 11:25:58	ga_s2am_ard_3-2-1_51JVH_2022-07-11_final
2022-07-11 11:26:06	ga_s2am_ard_3-2-1_51JXG_2022-07-11_final
2022-07-11 11:26:10	ga_s2am_ard_3-2-1_51JWG_2022-07-11_final
2022-07-11 11:26:13	ga_s2am_ard_3-2-1_51JVG_2022-07-11_final
2022-07-11 11:26:18	ga_s2am_ard_3-2-1_51JUG_2022-07-11_final
2022-07-11 11:26:24	ga_s2am_ard_3-2-1_51JWF_2022-07-11_final
2022-07-11 11:26:27	ga_s2am_ard_3-2-1_51JVF_2022-07-11_final
2022-07-11 11:26:35	ga_s2am_ard_3-2-1_51HXE_2022-07-11_final
2022-07-11 11:26:45	ga_s2am_ard_3-2-1_51HUE_2022-07-11_final
2022-07-11 11:26:48	ga_s2am_ard_3-2-1_51HXD_2022-07-11_final
2022-07-11 11:26:54	ga_s2am_ard_3-2-1_51HUD_2022-07-11_final
2022-07-11 11:26:55	ga_s2am_ard_3-2-1_51HXD_2022-07-11_final
2022-07-11 11:27:00	ga_s2am_ard_3-2-1_51HXC_2022-07-11_final.stac-item
2022-07-11 11:27:01	ga_s2am_ard_3-2-1_51HUD_2022-07-11_final
2022-07-11 11:27:07	ga_s2am_ard_3-2-1_51HWC_2022-07-11_final.stac-item
2022-07-11 11:27:11	ga_s2am_ard_3-2-1_51HVC_2022-07-11_final
2022-07-11 11:27:14	ga_s2am_ard_3-2-1_51HUC_2022-07-11_final
2022-07-11 11:27:20	ga_s2am_ard_3-2-1_51HTC_2022-07-11_final
2022-07-11 11:27:21	ga_s2am_ard_3-2-1_51HWB_2022-07-11_final.stac-item
2022-07-11 11:27:23	ga_s2am_ard_3-2-1_51HVB_2022-07-11_final.stac-item
2022-07-11 11:27:25	ga_s2am_ard_3-2-1_51HUB_2022-07-11_final.stac-item
2022-07-11 11:27:27	ga_s2am_ard_3-2-1_51HTB_2022-07-11_final.stac-item
2022-07-12 10:50:47	ga_s2am_ard_3-2-1_53LPG_2022-07-12_final
2022-07-12 10:50:51	ga_s2am_ard_3-2-1_53LNG_2022-07-12_final
2022-07-12 10:50:54	ga_s2am_ard_3-2-1_53LMG_2022-07-12_final
2022-07-12 10:51:00	ga_s2am_ard_3-2-1_53LLG_2022-07-12_final
2022-07-12 10:51:06	ga_s2am_ard_3-2-1_53LNF_2022-07-12_final
2022-07-12 10:51:09	ga_s2am_ard_3-2-1_53LMF_2022-07-12_final
2022-07-12 10:51:35	ga_s2am_ard_3-2-1_53LND_2022-07-12_final
2022-07-12 10:51:38	ga_s2am_ard_3-2-1_53LMD_2022-07-12_final
2022-07-12 10:51:43	ga_s2am_ard_3-2-1_53LPC_2022-07-12_final
2022-07-12 10:51:48	ga_s2am_ard_3-2-1_53LLD_2022-07-12_final
2022-07-12 10:51:49	ga_s2am_ard_3-2-1_53LLC_2022-07-12_final
2022-07-12 10:51:49	ga_s2am_ard_3-2-1_53LPC_2022-07-12_final
2022-07-12 10:51:54	ga_s2am_ard_3-2-1_53KPB_2022-07-12_final
2022-07-12 10:51:56	ga_s2am_ard_3-2-1_53LLC_2022-07-12_final
2022-07-12 10:52:03	ga_s2am_ard_3-2-1_53KNB_2022-07-12_final
2022-07-12 10:52:07	ga_s2am_ard_3-2-1_53KMB_2022-07-12_final
2022-07-12 10:52:10	ga_s2am_ard_3-2-1_53KLB_2022-07-12_final
2022-07-12 10:52:18	ga_s2am_ard_3-2-1_53KNA_2022-07-12_final
2022-07-12 10:52:22	ga_s2am_ard_3-2-1_53KMA_2022-07-12_final
2022-07-12 10:52:28	ga_s2am_ard_3-2-1_53KKA_2022-07-12_final
2022-07-12 10:52:32	ga_s2am_ard_3-2-1_52KHF_2022-07-12_final
2022-07-12 10:52:33	ga_s2am_ard_3-2-1_53KNV_2022-07-12_final
2022-07-12 10:52:36	ga_s2am_ard_3-2-1_53KMV_2022-07-12_final
2022-07-12 10:52:39	ga_s2am_ard_3-2-1_53KLV_2022-07-12_final
2022-07-12 10:52:42	ga_s2am_ard_3-2-1_53KKV_2022-07-12_final
2022-07-12 10:52:44	ga_s2am_ard_3-2-1_52KHE_2022-07-12_final
2022-07-12 10:53:19	ga_s2am_ard_3-2-1_53KMS_2022-07-12_final
2022-07-12 10:53:27	ga_s2am_ard_3-2-1_52KHB_2022-07-12_final
2022-07-12 10:53:41	ga_s2am_ard_3-2-1_53KKR_2022-07-12_final
2022-07-12 10:53:41	ga_s2am_ard_3-2-1_52KHA_2022-07-12_final
2022-07-12 10:53:49	ga_s2am_ard_3-2-1_53KMQ_2022-07-12_final
2022-07-12 10:53:52	ga_s2am_ard_3-2-1_53KLQ_2022-07-12_final
2022-07-12 10:53:55	ga_s2am_ard_3-2-1_53KKQ_2022-07-12_final
2022-07-12 10:53:55	ga_s2am_ard_3-2-1_52KHV_2022-07-12_final
2022-07-12 10:54:07	ga_s2am_ard_3-2-1_53KLP_2022-07-12_final
2022-07-12 10:54:10	ga_s2am_ard_3-2-1_52KHU_2022-07-12_final
2022-07-12 10:54:14	ga_s2am_ard_3-2-1_52KGU_2022-07-12_final
2022-07-12 10:54:21	ga_s2am_ard_3-2-1_53JLN_2022-07-12_final
2022-07-12 10:54:23	ga_s2am_ard_3-2-1_52JHT_2022-07-12_final
2022-07-12 10:54:23	ga_s2am_ard_3-2-1_53JKN_2022-07-12_final
2022-07-12 10:54:24	ga_s2am_ard_3-2-1_52JGT_2022-07-12_final
2022-07-12 10:54:28	ga_s2am_ard_3-2-1_53JLN_2022-07-12_final
2022-07-12 10:54:29	ga_s2am_ard_3-2-1_52JHT_2022-07-12_final
2022-07-12 10:54:29	ga_s2am_ard_3-2-1_53JKN_2022-07-12_final
2022-07-12 10:54:39	ga_s2am_ard_3-2-1_52JHS_2022-07-12_final
2022-07-12 10:54:39	ga_s2am_ard_3-2-1_53JKM_2022-07-12_final
2022-07-12 10:54:42	ga_s2am_ard_3-2-1_52JGS_2022-07-12_final
2022-07-12 10:54:50	ga_s2am_ard_3-2-1_53JLL_2022-07-12_final
2022-07-12 10:54:57	ga_s2am_ard_3-2-1_52JGR_2022-07-12_final
2022-07-12 10:55:00	ga_s2am_ard_3-2-1_52JFR_2022-07-12_final
2022-07-12 10:55:05	ga_s2am_ard_3-2-1_53JLK_2022-07-12_final
2022-07-12 10:55:08	ga_s2am_ard_3-2-1_53JKK_2022-07-12_final
2022-07-12 10:55:15	ga_s2am_ard_3-2-1_52JFQ_2022-07-12_final
2022-07-12 10:55:28	ga_s2am_ard_3-2-1_53JLH_2022-07-12_final
2022-07-12 10:55:35	ga_s2am_ard_3-2-1_52JEP_2022-07-12_final
2022-07-12 10:55:37	ga_s2am_ard_3-2-1_53JKH_2022-07-12_final
2022-07-12 10:55:40	ga_s2am_ard_3-2-1_52JGN_2022-07-12_final
2022-07-12 10:55:47	ga_s2am_ard_3-2-1_52JEN_2022-07-12_final
2022-07-12 10:56:02	ga_s2am_ard_3-2-1_52JEM_2022-07-12_final
2022-07-12 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-07-12_final
2022-07-12 10:56:17	ga_s2am_ard_3-2-1_52JEL_2022-07-12_final
2022-07-12 10:56:21	ga_s2am_ard_3-2-1_53HKE_2022-07-12_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