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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

First 100 results (query limit)

Time (local)	Label
2019-05-13 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-05-13_final
2019-05-14 10:01:18	ga_s2am_ard_3-2-1_55LFC_2019-05-14_final
2019-05-14 10:01:21	ga_s2am_ard_3-2-1_55LEC_2019-05-14_final
2019-05-14 10:01:28	ga_s2am_ard_3-2-1_55LCC_2019-05-14_final
2019-05-14 10:01:36	ga_s2am_ard_3-2-1_55KEB_2019-05-14_final
2019-05-14 10:01:39	ga_s2am_ard_3-2-1_55KDB_2019-05-14_final
2019-05-14 10:01:46	ga_s2am_ard_3-2-1_55KFA_2019-05-14_final
2019-05-14 10:01:54	ga_s2am_ard_3-2-1_55KDA_2019-05-14_final
2019-05-14 10:01:57	ga_s2am_ard_3-2-1_55KCA_2019-05-14_final
2019-05-14 10:02:05	ga_s2am_ard_3-2-1_55KEV_2019-05-14_final
2019-05-14 10:02:08	ga_s2am_ard_3-2-1_55KDV_2019-05-14_final
2019-05-14 10:02:09	ga_s2am_ard_3-2-1_55KFU_2019-05-14_final
2019-05-14 10:02:26	ga_s2am_ard_3-2-1_55KCU_2019-05-14_final
2019-05-14 10:02:37	ga_s2am_ard_3-2-1_55KDT_2019-05-14_final
2019-05-14 10:02:40	ga_s2am_ard_3-2-1_55KCT_2019-05-14_final
2019-05-14 10:02:48	ga_s2am_ard_3-2-1_55KES_2019-05-14_final
2019-05-14 10:02:52	ga_s2am_ard_3-2-1_55KDS_2019-05-14_final
2019-05-14 10:02:55	ga_s2am_ard_3-2-1_55KCS_2019-05-14_final
2019-05-14 10:02:58	ga_s2am_ard_3-2-1_54KZB_2019-05-14_final
2019-05-14 10:03:02	ga_s2am_ard_3-2-1_55KER_2019-05-14_final
2019-05-14 10:03:06	ga_s2am_ard_3-2-1_55KDR_2019-05-14_final
2019-05-14 10:03:10	ga_s2am_ard_3-2-1_55KCR_2019-05-14_final
2019-05-14 10:03:13	ga_s2am_ard_3-2-1_55KEQ_2019-05-14_final
2019-05-14 10:03:13	ga_s2am_ard_3-2-1_55KBR_2019-05-14_final
2019-05-14 10:03:13	ga_s2am_ard_3-2-1_54KZA_2019-05-14_final
2019-05-14 10:03:21	ga_s2am_ard_3-2-1_55KDQ_2019-05-14_final
2019-05-14 10:03:24	ga_s2am_ard_3-2-1_55KCQ_2019-05-14_final
2019-05-14 10:03:27	ga_s2am_ard_3-2-1_55KBQ_2019-05-14_final
2019-05-14 10:03:28	ga_s2am_ard_3-2-1_54KZV_2019-05-14_final
2019-05-14 10:03:39	ga_s2am_ard_3-2-1_55KCP_2019-05-14_final
2019-05-14 10:03:42	ga_s2am_ard_3-2-1_55KBP_2019-05-14_final
2019-05-14 10:03:42	ga_s2am_ard_3-2-1_54KZU_2019-05-14_final
2019-05-14 10:03:46	ga_s2am_ard_3-2-1_54KYU_2019-05-14_final
2019-05-14 10:03:56	ga_s2am_ard_3-2-1_54JZT_2019-05-14_final
2019-05-14 10:04:04	ga_s2am_ard_3-2-1_55JDM_2019-05-14_final
2019-05-14 10:04:26	ga_s2am_ard_3-2-1_55JBL_2019-05-14_final
2019-05-14 10:04:29	ga_s2am_ard_3-2-1_54JYR_2019-05-14_final
2019-05-14 10:04:37	ga_s2am_ard_3-2-1_55JCK_2019-05-14_final
2019-05-14 10:04:55	ga_s2am_ard_3-2-1_55JBJ_2019-05-14_final
2019-05-14 10:05:30	ga_s2am_ard_3-2-1_54JXM_2019-05-14_final
2019-05-14 10:05:49	ga_s2am_ard_3-2-1_54JWL_2019-05-14_final
2019-05-14 10:05:59	ga_s2am_ard_3-2-1_54HXK_2019-05-14_final
2019-05-14 10:06:28	ga_s2am_ard_3-2-1_54HXH_2019-05-14_final
2019-05-14 10:06:49	ga_s2am_ard_3-2-1_55HBA_2019-05-14_final
2019-05-14 10:06:53	ga_s2am_ard_3-2-1_54HYF_2019-05-14_final
2019-05-14 10:07:01	ga_s2am_ard_3-2-1_54HWF_2019-05-14_final
2019-05-14 10:07:04	ga_s2am_ard_3-2-1_54HVF_2019-05-14_final
2019-05-14 10:07:18	ga_s2am_ard_3-2-1_54HYD_2019-05-14_final
2019-05-14 10:07:26	ga_s2am_ard_3-2-1_54HXD_2019-05-14_final
2019-05-14 10:07:40	ga_s2am_ard_3-2-1_54HXC_2019-05-14_final
2019-05-14 11:41:30	ga_s2am_ard_3-2-1_51LWE_2019-05-14_final
2019-05-14 11:41:33	ga_s2am_ard_3-2-1_51LVE_2019-05-14_final
2019-05-14 11:41:37	ga_s2am_ard_3-2-1_51LUE_2019-05-14_final
2019-05-14 11:41:51	ga_s2am_ard_3-2-1_51LUD_2019-05-14_final.stac-item
2019-05-14 11:41:59	ga_s2am_ard_3-2-1_51LWC_2019-05-14_final
2019-05-14 11:42:02	ga_s2am_ard_3-2-1_51LVC_2019-05-14_final
2019-05-14 11:42:06	ga_s2am_ard_3-2-1_51LUC_2019-05-14_final.stac-item
2019-05-14 11:42:13	ga_s2am_ard_3-2-1_51KWB_2019-05-14_final
2019-05-14 11:42:17	ga_s2am_ard_3-2-1_51KVB_2019-05-14_final
2019-05-14 11:42:25	ga_s2am_ard_3-2-1_51KWA_2019-05-14_final
2019-05-14 11:42:31	ga_s2am_ard_3-2-1_51KVA_2019-05-14_final
2019-05-14 11:42:35	ga_s2am_ard_3-2-1_51KUA_2019-05-14_final
2019-05-14 11:42:46	ga_s2am_ard_3-2-1_51KVV_2019-05-14_final
2019-05-14 11:42:49	ga_s2am_ard_3-2-1_51KUV_2019-05-14_final
2019-05-14 11:43:00	ga_s2am_ard_3-2-1_51KVU_2019-05-14_final
2019-05-14 11:43:04	ga_s2am_ard_3-2-1_51KUU_2019-05-14_final
2019-05-14 11:43:15	ga_s2am_ard_3-2-1_51KVT_2019-05-14_final
2019-05-14 11:43:18	ga_s2am_ard_3-2-1_51KUT_2019-05-14_final
2019-05-14 11:43:22	ga_s2am_ard_3-2-1_50KRC_2019-05-14_final
2019-05-14 11:43:28	ga_s2am_ard_3-2-1_51KVS_2019-05-14_final
2019-05-14 11:43:33	ga_s2am_ard_3-2-1_51KUS_2019-05-14_final
2019-05-14 11:43:36	ga_s2am_ard_3-2-1_51KTS_2019-05-14_final
2019-05-14 11:43:37	ga_s2am_ard_3-2-1_50KRB_2019-05-14_final
2019-05-14 11:43:40	ga_s2am_ard_3-2-1_51KVR_2019-05-14_final
2019-05-14 11:43:40	ga_s2am_ard_3-2-1_50KQB_2019-05-14_final
2019-05-14 11:43:47	ga_s2am_ard_3-2-1_51KUR_2019-05-14_final
2019-05-14 11:43:51	ga_s2am_ard_3-2-1_51KTR_2019-05-14_final
2019-05-14 11:43:55	ga_s2am_ard_3-2-1_50KQA_2019-05-14_final
2019-05-14 11:44:02	ga_s2am_ard_3-2-1_51KUQ_2019-05-14_final
2019-05-14 11:44:05	ga_s2am_ard_3-2-1_51KTQ_2019-05-14_final
2019-05-14 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-05-14_final
2019-05-14 11:44:09	ga_s2am_ard_3-2-1_50KQV_2019-05-14_final
2019-05-14 11:44:14	ga_s2am_ard_3-2-1_50KPV_2019-05-14_final
2019-05-14 11:44:17	ga_s2am_ard_3-2-1_51KUP_2019-05-14_final
2019-05-14 11:44:20	ga_s2am_ard_3-2-1_50KRU_2019-05-14_final
2019-05-14 11:44:20	ga_s2am_ard_3-2-1_51KTP_2019-05-14_final
2019-05-14 11:44:23	ga_s2am_ard_3-2-1_50KQU_2019-05-14_final
2019-05-14 11:44:27	ga_s2am_ard_3-2-1_50KPU_2019-05-14_final
2019-05-14 11:44:52	ga_s2am_ard_3-2-1_50JQS_2019-05-14_final
2019-05-14 11:45:11	ga_s2am_ard_3-2-1_50JPR_2019-05-14_final
2019-05-14 11:45:15	ga_s2am_ard_3-2-1_50JNR_2019-05-14_final
2019-05-14 11:45:33	ga_s2am_ard_3-2-1_51JTJ_2019-05-14_final
2019-05-14 11:46:09	ga_s2am_ard_3-2-1_50JPM_2019-05-14_final
2019-05-14 11:46:12	ga_s2am_ard_3-2-1_50JNM_2019-05-14_final
2019-05-14 11:46:16	ga_s2am_ard_3-2-1_50JMM_2019-05-14_final
2019-05-14 11:46:26	ga_s2am_ard_3-2-1_50JNL_2019-05-14_final
2019-05-14 11:46:30	ga_s2am_ard_3-2-1_50JML_2019-05-14_final
2019-05-14 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-05-14_final
2019-05-14 11:46:41	ga_s2am_ard_3-2-1_50HNK_2019-05-14_final
2019-05-14 11:46:44	ga_s2am_ard_3-2-1_50HMK_2019-05-14_final

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