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
2023-10-13 10:09:53	ga_s2am_ard_3-2-1_55LBJ_2023-10-13_nrt.stac-item
2023-10-13 10:09:56	ga_s2am_ard_3-2-1_54LZP_2023-10-13_final.stac-item
2023-10-13 10:09:56	ga_s2am_ard_3-2-1_55LEH_2023-10-13_nrt.stac-item
2023-10-13 10:10:01	ga_s2am_ard_3-2-1_55LDH_2023-10-13_nrt.stac-item
2023-10-13 10:10:04	ga_s2am_ard_3-2-1_55LCH_2023-10-13_nrt.stac-item
2023-10-13 10:10:08	ga_s2am_ard_3-2-1_55LBH_2023-10-13_nrt.stac-item
2023-10-13 10:10:09	ga_s2am_ard_3-2-1_54LZN_2023-10-13_final.stac-item
2023-10-13 10:10:30	ga_s2am_ard_3-2-1_55LDF_2023-10-13_nrt.stac-item
2023-10-13 10:10:33	ga_s2am_ard_3-2-1_55LCF_2023-10-13_nrt.stac-item
2023-10-13 10:10:36	ga_s2am_ard_3-2-1_55LBF_2023-10-13_nrt.stac-item
2023-10-13 10:10:38	ga_s2am_ard_3-2-1_54LZL_2023-10-13_final.stac-item
2023-10-13 10:10:45	ga_s2am_ard_3-2-1_55LDE_2023-10-13_nrt.stac-item
2023-10-13 10:10:48	ga_s2am_ard_3-2-1_55LCE_2023-10-13_final.stac-item
2023-10-13 10:11:03	ga_s2am_ard_3-2-1_55LCD_2023-10-13_final.stac-item
2023-10-13 10:11:20	ga_s2am_ard_3-2-1_55LBC_2023-10-13_final.stac-item
2023-10-13 10:11:21	ga_s2am_ard_3-2-1_54LZH_2023-10-13_final.stac-item
2023-10-13 10:11:25	ga_s2am_ard_3-2-1_54LYH_2023-10-13_final.stac-item
2023-10-13 10:11:46	ga_s2am_ard_3-2-1_55KCA_2023-10-13_final.stac-item
2023-10-13 10:11:49	ga_s2am_ard_3-2-1_55KBA_2023-10-13_final.stac-item
2023-10-13 10:11:54	ga_s2am_ard_3-2-1_54KYF_2023-10-13_final.stac-item
2023-10-13 10:12:00	ga_s2am_ard_3-2-1_54KXF_2023-10-13_final.stac-item
2023-10-13 10:12:05	ga_s2am_ard_3-2-1_54KZE_2023-10-13_final.stac-item
2023-10-13 10:12:14	ga_s2am_ard_3-2-1_55KCU_2023-10-13_final.stac-item
2023-10-13 10:12:18	ga_s2am_ard_3-2-1_55KBU_2023-10-13_final.stac-item
2023-10-13 10:12:23	ga_s2am_ard_3-2-1_54KYD_2023-10-13_final.stac-item
2023-10-13 10:12:26	ga_s2am_ard_3-2-1_55KCT_2023-10-13_final.stac-item
2023-10-13 10:12:26	ga_s2am_ard_3-2-1_54KXD_2023-10-13_final.stac-item
2023-10-13 10:12:33	ga_s2am_ard_3-2-1_55KBT_2023-10-13_final.stac-item
2023-10-13 10:12:37	ga_s2am_ard_3-2-1_54KYC_2023-10-13_final.stac-item
2023-10-13 10:12:41	ga_s2am_ard_3-2-1_54KXC_2023-10-13_final.stac-item
2023-10-13 10:12:47	ga_s2am_ard_3-2-1_55KBS_2023-10-13_final.stac-item
2023-10-13 10:12:52	ga_s2am_ard_3-2-1_54KYB_2023-10-13_final.stac-item
2023-10-13 10:12:55	ga_s2am_ard_3-2-1_54KXB_2023-10-13_final.stac-item
2023-10-13 10:13:06	ga_s2am_ard_3-2-1_54KYA_2023-10-13_final.stac-item
2023-10-13 10:13:17	ga_s2am_ard_3-2-1_55KBQ_2023-10-13_final.stac-item
2023-10-13 10:13:24	ga_s2am_ard_3-2-1_54KXV_2023-10-13_final.stac-item
2023-10-13 10:13:27	ga_s2am_ard_3-2-1_54KWV_2023-10-13_final.stac-item
2023-10-13 10:13:30	ga_s2am_ard_3-2-1_55KBP_2023-10-13_final.stac-item
2023-10-13 10:13:39	ga_s2am_ard_3-2-1_54KXU_2023-10-13_final.stac-item
2023-10-13 10:13:42	ga_s2am_ard_3-2-1_54KWU_2023-10-13_final.stac-item
2023-10-13 10:14:11	ga_s2am_ard_3-2-1_54JWS_2023-10-13_final.stac-item
2023-10-13 10:14:15	ga_s2am_ard_3-2-1_54JVS_2023-10-13_final.stac-item
2023-10-13 10:14:26	ga_s2am_ard_3-2-1_54JWR_2023-10-13_final.stac-item
2023-10-13 10:14:29	ga_s2am_ard_3-2-1_54JVR_2023-10-13_final.stac-item
2023-10-13 10:14:55	ga_s2am_ard_3-2-1_54JWP_2023-10-13_final.stac-item
2023-10-13 10:14:58	ga_s2am_ard_3-2-1_54JVP_2023-10-13_final.stac-item
2023-10-13 10:15:27	ga_s2am_ard_3-2-1_54JVM_2023-10-13_final.stac-item
2023-10-13 10:15:38	ga_s2am_ard_3-2-1_54JWL_2023-10-13_final.stac-item
2023-10-13 10:15:42	ga_s2am_ard_3-2-1_54JVL_2023-10-13_final.stac-item
2023-10-13 10:16:32	ga_s2am_ard_3-2-1_54HTH_2023-10-13_final.stac-item
2023-10-13 10:17:01	ga_s2am_ard_3-2-1_54HWE_2023-10-13_final.stac-item
2023-10-13 10:17:09	ga_s2am_ard_3-2-1_54HVE_2023-10-13_final.stac-item
2023-10-13 10:17:12	ga_s2am_ard_3-2-1_54HUE_2023-10-13_final.stac-item
2023-10-13 10:17:16	ga_s2am_ard_3-2-1_54HTE_2023-10-13_final.stac-item
2023-10-13 10:17:17	ga_s2am_ard_3-2-1_53HQV_2023-10-13_final.stac-item
2023-10-13 11:50:22	ga_s2am_ard_3-2-1_51LVJ_2023-10-13_nrt.stac-item
2023-10-13 11:50:32	ga_s2am_ard_3-2-1_50LRP_2023-10-13_nrt.stac-item
2023-10-13 11:50:42	ga_s2am_ard_3-2-1_51LUH_2023-10-13_nrt.stac-item
2023-10-13 11:50:50	ga_s2am_ard_3-2-1_50LQN_2023-10-13_nrt.stac-item
2023-10-13 11:51:01	ga_s2am_ard_3-2-1_50LRM_2023-10-13_nrt.stac-item
2023-10-13 11:51:11	ga_s2am_ard_3-2-1_51LUF_2023-10-13_final.stac-item
2023-10-13 11:51:15	ga_s2am_ard_3-2-1_51LTF_2023-10-13_nrt.stac-item
2023-10-13 11:51:16	ga_s2am_ard_3-2-1_50LRL_2023-10-13_nrt.stac-item
2023-10-13 11:51:19	ga_s2am_ard_3-2-1_50LQL_2023-10-13_nrt.stac-item
2023-10-13 11:51:25	ga_s2am_ard_3-2-1_51LUE_2023-10-13_final.stac-item
2023-10-13 11:51:37	ga_s2am_ard_3-2-1_50LPK_2023-10-13_nrt.stac-item
2023-10-13 11:51:51	ga_s2am_ard_3-2-1_50LPJ_2023-10-13_nrt.stac-item
2023-10-13 11:51:58	ga_s2am_ard_3-2-1_51LTC_2023-10-13_nrt.stac-item
2023-10-13 11:51:59	ga_s2am_ard_3-2-1_50LRH_2023-10-13_nrt.stac-item
2023-10-13 11:52:03	ga_s2am_ard_3-2-1_50LQH_2023-10-13_nrt.stac-item
2023-10-13 11:52:27	ga_s2am_ard_3-2-1_51KTA_2023-10-13_nrt.stac-item
2023-10-13 11:52:32	ga_s2am_ard_3-2-1_50KQF_2023-10-13_final.stac-item
2023-10-13 11:52:35	ga_s2am_ard_3-2-1_50KPF_2023-10-13_final.stac-item
2023-10-13 11:52:43	ga_s2am_ard_3-2-1_50KRE_2023-10-13_nrt.stac-item
2023-10-13 11:53:01	ga_s2am_ard_3-2-1_50KQD_2023-10-13_final.stac-item
2023-10-13 11:53:08	ga_s2am_ard_3-2-1_50KND_2023-10-13_nrt.stac-item
2023-10-13 11:53:15	ga_s2am_ard_3-2-1_50KQC_2023-10-13_final.stac-item
2023-10-13 11:53:19	ga_s2am_ard_3-2-1_50KPC_2023-10-13_final.stac-item
2023-10-13 11:53:22	ga_s2am_ard_3-2-1_50KNC_2023-10-13_final.stac-item
2023-10-13 11:53:29	ga_s2am_ard_3-2-1_50KMC_2023-10-13_final.stac-item
2023-10-13 11:53:29	ga_s2am_ard_3-2-1_50KQB_2023-10-13_final.stac-item
2023-10-13 11:53:33	ga_s2am_ard_3-2-1_50KPB_2023-10-13_final.stac-item
2023-10-13 11:53:37	ga_s2am_ard_3-2-1_50KNB_2023-10-13_final.stac-item
2023-10-13 11:53:40	ga_s2am_ard_3-2-1_50KMB_2023-10-13_final.stac-item
2023-10-13 11:53:44	ga_s2am_ard_3-2-1_50KQA_2023-10-13_final.stac-item
2023-10-13 11:53:51	ga_s2am_ard_3-2-1_50KNA_2023-10-13_final.stac-item
2023-10-13 11:53:54	ga_s2am_ard_3-2-1_50KMA_2023-10-13_final.stac-item
2023-10-13 11:54:02	ga_s2am_ard_3-2-1_50KPV_2023-10-13_final.stac-item
2023-10-13 11:54:17	ga_s2am_ard_3-2-1_50KPU_2023-10-13_final.stac-item
2023-10-13 11:54:49	ga_s2am_ard_3-2-1_50JNS_2023-10-13_final.stac-item
2023-10-13 11:55:04	ga_s2am_ard_3-2-1_50JNR_2023-10-13_final.stac-item
2023-10-13 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-10-13_final.stac-item
2023-10-13 11:55:18	ga_s2am_ard_3-2-1_50JNQ_2023-10-13_final.stac-item
2023-10-13 11:55:22	ga_s2am_ard_3-2-1_50JMQ_2023-10-13_final.stac-item
2023-10-13 11:55:32	ga_s2am_ard_3-2-1_50JNP_2023-10-13_final.stac-item
2023-10-13 11:55:36	ga_s2am_ard_3-2-1_50JMP_2023-10-13_final.stac-item
2023-10-13 11:56:12	ga_s2am_ard_3-2-1_50JKM_2023-10-13_final.stac-item
2023-10-13 11:56:16	ga_s2am_ard_3-2-1_50JNL_2023-10-13_final.stac-item
2023-10-13 11:56:20	ga_s2am_ard_3-2-1_50JML_2023-10-13_final.stac-item
2023-10-13 11:57:10	ga_s2am_ard_3-2-1_50HKH_2023-10-13_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

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