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
2022-03-16 11:34:40	ga_s2am_ard_3-2-1_51JTN_2022-03-16_final
2022-03-16 11:34:41	ga_s2am_ard_3-2-1_50JRT_2022-03-16_final
2022-03-16 11:35:08	ga_s2am_ard_3-2-1_51JTL_2022-03-16_final
2022-03-16 11:35:19	ga_s2am_ard_3-2-1_51JUK_2022-03-16_final
2022-03-16 11:35:23	ga_s2am_ard_3-2-1_51JTK_2022-03-16_final
2022-03-16 11:35:23	ga_s2am_ard_3-2-1_51JWJ_2022-03-16_final
2022-03-16 11:35:34	ga_s2am_ard_3-2-1_51JUJ_2022-03-16_final
2022-03-16 11:35:37	ga_s2am_ard_3-2-1_51JTJ_2022-03-16_final
2022-03-16 11:35:41	ga_s2am_ard_3-2-1_50JQP_2022-03-16_final
2022-03-16 11:35:45	ga_s2am_ard_3-2-1_51JVH_2022-03-16_final
2022-03-16 11:35:49	ga_s2am_ard_3-2-1_51JUH_2022-03-16_final
2022-03-16 11:35:52	ga_s2am_ard_3-2-1_51JTH_2022-03-16_final
2022-03-16 11:35:54	ga_s2am_ard_3-2-1_50JQN_2022-03-16_final
2022-03-16 11:36:03	ga_s2am_ard_3-2-1_51JUG_2022-03-16_final
2022-03-16 11:36:06	ga_s2am_ard_3-2-1_51JTG_2022-03-16_final
2022-03-16 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-03-16_final
2022-03-16 11:36:14	ga_s2am_ard_3-2-1_51JVF_2022-03-16_final
2022-03-16 11:36:18	ga_s2am_ard_3-2-1_51JUF_2022-03-16_final
2022-03-16 11:36:21	ga_s2am_ard_3-2-1_51JTF_2022-03-16_final
2022-03-16 11:36:23	ga_s2am_ard_3-2-1_50JQL_2022-03-16_final
2022-03-16 11:36:27	ga_s2am_ard_3-2-1_51HVE_2022-03-16_final
2022-03-16 11:36:30	ga_s2am_ard_3-2-1_50JPL_2022-03-16_final
2022-03-16 11:36:32	ga_s2am_ard_3-2-1_51HUE_2022-03-16_final
2022-03-16 11:36:36	ga_s2am_ard_3-2-1_51HTE_2022-03-16_final
2022-03-16 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-03-16_final
2022-03-16 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-03-16_final
2022-03-16 11:37:05	ga_s2am_ard_3-2-1_51HTC_2022-03-16_final
2022-03-16 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-03-16_final
2022-03-16 11:37:16	ga_s2am_ard_3-2-1_51HUB_2022-03-16_final.stac-item
2022-03-16 11:37:25	ga_s2am_ard_3-2-1_50HPG_2022-03-16_final.stac-item
2022-03-17 09:23:43	ga_s2am_ard_3-2-1_56JNT_2022-03-16_final
2022-03-17 09:23:58	ga_s2am_ard_3-2-1_56JNS_2022-03-16_final
2022-03-17 09:24:13	ga_s2am_ard_3-2-1_56JNR_2022-03-16_final.stac-item
2022-03-17 09:24:42	ga_s2am_ard_3-2-1_56JNP_2022-03-16_final.stac-item
2022-03-17 09:24:45	ga_s2am_ard_3-2-1_56JMP_2022-03-16_final
2022-03-17 09:24:56	ga_s2am_ard_3-2-1_56JNN_2022-03-16_final
2022-03-17 09:25:00	ga_s2am_ard_3-2-1_56JMN_2022-03-16_final
2022-03-17 09:25:25	ga_s2am_ard_3-2-1_56JNL_2022-03-16_final
2022-03-17 09:25:29	ga_s2am_ard_3-2-1_56JML_2022-03-16_final
2022-03-17 09:25:33	ga_s2am_ard_3-2-1_56JLL_2022-03-16_final
2022-03-17 09:25:43	ga_s2am_ard_3-2-1_56HMK_2022-03-16_final
2022-03-17 09:25:46	ga_s2am_ard_3-2-1_56HLK_2022-03-16_final
2022-03-17 09:26:30	ga_s2am_ard_3-2-1_56HLG_2022-03-16_final.stac-item
2022-03-17 09:26:48	ga_s2am_ard_3-2-1_56HKF_2022-03-16_final
2022-03-17 09:27:05	ga_s2am_ard_3-2-1_55HGV_2022-03-16_final
2022-03-17 09:27:53	ga_s2am_ard_3-2-1_55HFS_2022-03-16_final.stac-item
2022-03-17 09:28:05	ga_s2am_ard_3-2-1_55GFR_2022-03-16_final
2022-03-17 09:28:20	ga_s2am_ard_3-2-1_55GFQ_2022-03-16_final
2022-03-17 11:00:18	ga_s2am_ard_3-2-1_53LKJ_2022-03-17_final.stac-item
2022-03-17 11:00:26	ga_s2am_ard_3-2-1_53LMH_2022-03-17_final.stac-item
2022-03-17 11:00:29	ga_s2am_ard_3-2-1_53LLH_2022-03-17_final.stac-item
2022-03-17 11:00:44	ga_s2am_ard_3-2-1_53LLG_2022-03-17_final
2022-03-17 11:00:52	ga_s2am_ard_3-2-1_53LMF_2022-03-17_final
2022-03-17 11:01:27	ga_s2am_ard_3-2-1_53LLD_2022-03-17_final
2022-03-17 11:01:43	ga_s2am_ard_3-2-1_52LFJ_2022-03-17_final
2022-03-17 11:01:50	ga_s2am_ard_3-2-1_52LGH_2022-03-17_final
2022-03-17 11:02:00	ga_s2am_ard_3-2-1_53KKB_2022-03-17_final
2022-03-17 11:02:01	ga_s2am_ard_3-2-1_52KHG_2022-03-17_final
2022-03-17 11:02:04	ga_s2am_ard_3-2-1_52KGG_2022-03-17_final
2022-03-17 11:02:07	ga_s2am_ard_3-2-1_53KLA_2022-03-17_final
2022-03-17 11:02:14	ga_s2am_ard_3-2-1_53KKA_2022-03-17_final
2022-03-17 11:02:19	ga_s2am_ard_3-2-1_52KGF_2022-03-17_final
2022-03-17 11:02:37	ga_s2am_ard_3-2-1_52KFE_2022-03-17_final
2022-03-17 11:02:43	ga_s2am_ard_3-2-1_53KKU_2022-03-17_final
2022-03-17 11:02:56	ga_s2am_ard_3-2-1_52KED_2022-03-17_final
2022-03-17 11:02:58	ga_s2am_ard_3-2-1_53KKT_2022-03-17_final
2022-03-17 11:03:02	ga_s2am_ard_3-2-1_52KGC_2022-03-17_final
2022-03-17 11:03:09	ga_s2am_ard_3-2-1_52KEC_2022-03-17_final
2022-03-17 11:03:11	ga_s2am_ard_3-2-1_53KKS_2022-03-17_final
2022-03-17 11:03:17	ga_s2am_ard_3-2-1_52KGB_2022-03-17_final
2022-03-17 11:03:23	ga_s2am_ard_3-2-1_53KKR_2022-03-17_final
2022-03-17 11:03:35	ga_s2am_ard_3-2-1_52KFA_2022-03-17_final
2022-03-17 11:03:45	ga_s2am_ard_3-2-1_52KGV_2022-03-17_final
2022-03-17 11:03:53	ga_s2am_ard_3-2-1_52KEV_2022-03-17_final
2022-03-17 11:04:04	ga_s2am_ard_3-2-1_52KFU_2022-03-17_final
2022-03-17 11:04:07	ga_s2am_ard_3-2-1_52KEU_2022-03-17_final
2022-03-17 11:04:10	ga_s2am_ard_3-2-1_52KDU_2022-03-17_final
2022-03-17 11:04:15	ga_s2am_ard_3-2-1_52JGT_2022-03-17_final
2022-03-17 11:04:39	ga_s2am_ard_3-2-1_52JGR_2022-03-17_final
2022-03-17 11:04:47	ga_s2am_ard_3-2-1_52JFR_2022-03-17_final
2022-03-17 11:04:55	ga_s2am_ard_3-2-1_52JFQ_2022-03-17_final
2022-03-17 11:04:57	ga_s2am_ard_3-2-1_52JEQ_2022-03-17_final
2022-03-17 11:05:02	ga_s2am_ard_3-2-1_52JFQ_2022-03-17_final
2022-03-17 11:05:12	ga_s2am_ard_3-2-1_52JCQ_2022-03-17_final
2022-03-17 11:05:16	ga_s2am_ard_3-2-1_52JFP_2022-03-17_final
2022-03-17 11:05:20	ga_s2am_ard_3-2-1_52JEP_2022-03-17_final
2022-03-17 11:05:23	ga_s2am_ard_3-2-1_52JDP_2022-03-17_final
2022-03-17 11:05:26	ga_s2am_ard_3-2-1_52JCP_2022-03-17_final
2022-03-17 11:05:34	ga_s2am_ard_3-2-1_52JEN_2022-03-17_final
2022-03-17 11:05:38	ga_s2am_ard_3-2-1_52JDN_2022-03-17_final
2022-03-17 11:05:41	ga_s2am_ard_3-2-1_52JCN_2022-03-17_final
2022-03-17 11:05:42	ga_s2am_ard_3-2-1_52JFM_2022-03-17_final
2022-03-17 11:05:56	ga_s2am_ard_3-2-1_52JCM_2022-03-17_final
2022-03-17 11:06:02	ga_s2am_ard_3-2-1_52JBM_2022-03-17_final
2022-03-17 11:06:03	ga_s2am_ard_3-2-1_52JEL_2022-03-17_final
2022-03-17 11:06:07	ga_s2am_ard_3-2-1_52JDL_2022-03-17_final
2022-03-17 11:06:10	ga_s2am_ard_3-2-1_52JCL_2022-03-17_final
2022-03-17 11:06:14	ga_s2am_ard_3-2-1_52JBL_2022-03-17_final
2022-03-17 11:06:21	ga_s2am_ard_3-2-1_52HDK_2022-03-17_final.stac-item
2022-03-17 11:06:25	ga_s2am_ard_3-2-1_52HCK_2022-03-17_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

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