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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

72 results

Time (local)	Label
2023-10-23 10:10:21	ga_s2am_ard_3-2-1_55LCG_2023-10-23_nrt.stac-item
2023-10-23 11:50:30	ga_s2am_ard_3-2-1_51LUJ_2023-10-23_nrt.stac-item
2023-10-23 11:50:33	ga_s2am_ard_3-2-1_51LTJ_2023-10-23_nrt.stac-item
2023-10-23 11:50:38	ga_s2am_ard_3-2-1_50LQP_2023-10-23_nrt.stac-item
2023-10-23 11:50:44	ga_s2am_ard_3-2-1_51LUH_2023-10-23_nrt.stac-item
2023-10-23 11:51:04	ga_s2am_ard_3-2-1_50LRM_2023-10-23_nrt.stac-item
2023-10-23 11:51:07	ga_s2am_ard_3-2-1_50LQM_2023-10-23_nrt.stac-item
2023-10-23 11:51:31	ga_s2am_ard_3-2-1_51LTE_2023-10-23_nrt.stac-item
2023-10-23 11:51:33	ga_s2am_ard_3-2-1_50LRK_2023-10-23_nrt.stac-item
2023-10-23 11:51:47	ga_s2am_ard_3-2-1_50LRJ_2023-10-23_nrt.stac-item
2023-10-23 11:51:54	ga_s2am_ard_3-2-1_50LPJ_2023-10-23_nrt.stac-item
2023-10-23 11:52:01	ga_s2am_ard_3-2-1_50LRH_2023-10-23_nrt.stac-item
2023-10-23 11:52:16	ga_s2am_ard_3-2-1_50KRG_2023-10-23_nrt.stac-item
2023-10-23 11:52:23	ga_s2am_ard_3-2-1_50KPG_2023-10-23_nrt.stac-item
2023-10-23 11:52:28	ga_s2am_ard_3-2-1_50KNG_2023-10-23_nrt.stac-item
2023-10-23 11:52:55	ga_s2am_ard_3-2-1_50KNE_2023-10-23_nrt.stac-item
2023-10-23 11:53:10	ga_s2am_ard_3-2-1_50KND_2023-10-23_nrt.stac-item
2023-10-23 11:56:24	ga_s2am_ard_3-2-1_50JKL_2023-10-23_nrt.stac-item
2023-10-23 11:56:27	ga_s2am_ard_3-2-1_49JGF_2023-10-23_nrt.stac-item
2023-10-23 11:56:43	ga_s2am_ard_3-2-1_50HKK_2023-10-23_nrt.stac-item
2023-10-23 11:56:45	ga_s2am_ard_3-2-1_49HGE_2023-10-23_nrt.stac-item
2023-10-23 11:56:58	ga_s2am_ard_3-2-1_50HKJ_2023-10-23_nrt.stac-item
2023-10-23 11:57:00	ga_s2am_ard_3-2-1_49HGD_2023-10-23_nrt.stac-item
2023-10-23 11:57:12	ga_s2am_ard_3-2-1_50HKH_2023-10-23_nrt.stac-item
2023-10-23 11:57:14	ga_s2am_ard_3-2-1_49HGC_2023-10-23_nrt.stac-item
2023-10-23 11:57:27	ga_s2am_ard_3-2-1_49HFB_2023-10-23_nrt.stac-item
2023-10-24 09:39:35	ga_s2am_ard_3-2-1_56LPP_2023-10-24_nrt.stac-item
2023-10-24 09:39:39	ga_s2am_ard_3-2-1_56LNP_2023-10-24_nrt.stac-item
2023-10-24 09:39:42	ga_s2am_ard_3-2-1_56LMP_2023-10-24_nrt.stac-item
2023-10-24 09:39:49	ga_s2am_ard_3-2-1_56LLP_2023-10-24_nrt.stac-item
2023-10-24 09:39:49	ga_s2am_ard_3-2-1_56LPN_2023-10-24_nrt.stac-item
2023-10-24 09:39:53	ga_s2am_ard_3-2-1_56LNN_2023-10-24_nrt.stac-item
2023-10-24 09:39:56	ga_s2am_ard_3-2-1_56LMN_2023-10-24_nrt.stac-item
2023-10-24 09:40:00	ga_s2am_ard_3-2-1_56LLN_2023-10-24_nrt.stac-item
2023-10-24 09:40:03	ga_s2am_ard_3-2-1_56LPM_2023-10-24_nrt.stac-item
2023-10-24 09:40:05	ga_s2am_ard_3-2-1_56LNM_2023-10-24_nrt.stac-item
2023-10-24 09:40:07	ga_s2am_ard_3-2-1_56LMM_2023-10-24_nrt.stac-item
2023-10-24 09:40:08	ga_s2am_ard_3-2-1_56LLM_2023-10-24_nrt.stac-item
2023-10-24 09:40:10	ga_s2am_ard_3-2-1_56LPL_2023-10-24_nrt.stac-item
2023-10-24 09:41:15	ga_s2am_ard_3-2-1_56LNH_2023-10-24_nrt.stac-item
2023-10-24 09:41:16	ga_s2am_ard_3-2-1_56LMH_2023-10-24_nrt.stac-item
2023-10-24 09:41:17	ga_s2am_ard_3-2-1_56LLH_2023-10-24_nrt.stac-item
2023-10-24 09:41:19	ga_s2am_ard_3-2-1_56LKH_2023-10-24_nrt.stac-item
2023-10-24 09:41:21	ga_s2am_ard_3-2-1_56KNG_2023-10-24_nrt.stac-item
2023-10-24 09:41:34	ga_s2am_ard_3-2-1_56KNF_2023-10-24_nrt.stac-item
2023-10-24 09:41:45	ga_s2am_ard_3-2-1_55KHA_2023-10-24_nrt.stac-item
2023-10-24 09:41:46	ga_s2am_ard_3-2-1_56KNE_2023-10-24_nrt.stac-item
2023-10-24 09:41:59	ga_s2am_ard_3-2-1_56KKE_2023-10-24_nrt.stac-item
2023-10-24 09:42:00	ga_s2am_ard_3-2-1_55KHV_2023-10-24_nrt.stac-item
2023-10-24 09:42:14	ga_s2am_ard_3-2-1_56KKD_2023-10-24_nrt.stac-item
2023-10-24 09:42:14	ga_s2am_ard_3-2-1_55KHU_2023-10-24_nrt.stac-item
2023-10-24 09:42:22	ga_s2am_ard_3-2-1_56KMC_2023-10-24_nrt.stac-item
2023-10-24 09:42:25	ga_s2am_ard_3-2-1_56KLC_2023-10-24_nrt.stac-item
2023-10-24 09:42:28	ga_s2am_ard_3-2-1_56KKC_2023-10-24_nrt.stac-item
2023-10-24 09:42:29	ga_s2am_ard_3-2-1_55KHT_2023-10-24_nrt.stac-item
2023-10-24 09:43:01	ga_s2am_ard_3-2-1_56KMV_2023-10-24_nrt.stac-item
2023-10-24 09:48:38	ga_s2am_ard_3-2-1_54GYU_2023-10-24_nrt.stac-item
2023-10-24 09:48:38	ga_s2am_ard_3-2-1_55GBP_2023-10-24_nrt.stac-item
2023-10-24 09:48:43	ga_s2am_ard_3-2-1_54GXU_2023-10-24_nrt.stac-item
2023-10-24 09:48:49	ga_s2am_ard_3-2-1_54GYT_2023-10-24_nrt.stac-item
2023-10-24 09:48:51	ga_s2am_ard_3-2-1_54GXT_2023-10-24_nrt.stac-item
2023-10-24 09:48:56	ga_s2am_ard_3-2-1_54GYT_2023-10-24_nrt.stac-item
2023-10-24 09:48:58	ga_s2am_ard_3-2-1_54GXT_2023-10-24_nrt.stac-item
2023-10-24 09:49:00	ga_s2am_ard_3-2-1_54GYS_2023-10-24_nrt.stac-item
2023-10-24 09:49:02	ga_s2am_ard_3-2-1_54GXS_2023-10-24_nrt.stac-item
2023-10-24 11:20:16	ga_s2am_ard_3-2-1_52LEP_2023-10-24_nrt.stac-item
2023-10-24 11:20:20	ga_s2am_ard_3-2-1_52LDP_2023-10-24_nrt.stac-item
2023-10-24 11:20:26	ga_s2am_ard_3-2-1_52LBP_2023-10-24_nrt.stac-item
2023-10-24 11:20:34	ga_s2am_ard_3-2-1_52LDN_2023-10-24_nrt.stac-item
2023-10-24 11:20:55	ga_s2am_ard_3-2-1_52LBM_2023-10-24_nrt.stac-item
2023-10-24 11:21:03	ga_s2am_ard_3-2-1_52LDL_2023-10-24_nrt.stac-item
2023-10-24 11:21:17	ga_s2am_ard_3-2-1_52LDK_2023-10-24_nrt.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