Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-12-07 10:15:08	ga_s2am_ard_3-2-1_54JUP_2022-12-07_final.stac-item
2022-12-07 10:15:08	ga_s2am_ard_3-2-1_54JXN_2022-12-07_final.stac-item
2022-12-07 10:15:12	ga_s2am_ard_3-2-1_54JWN_2022-12-07_final.stac-item
2022-12-07 10:15:15	ga_s2am_ard_3-2-1_54JVN_2022-12-07_final.stac-item
2022-12-07 10:15:19	ga_s2am_ard_3-2-1_54JUN_2022-12-07_final.stac-item
2022-12-07 10:15:23	ga_s2am_ard_3-2-1_54JXM_2022-12-07_final.stac-item
2022-12-07 10:15:27	ga_s2am_ard_3-2-1_54JWM_2022-12-07_final.stac-item
2022-12-07 10:15:30	ga_s2am_ard_3-2-1_54JVM_2022-12-07_final.stac-item
2022-12-07 10:15:33	ga_s2am_ard_3-2-1_54JUM_2022-12-07_final.stac-item
2022-12-07 10:15:37	ga_s2am_ard_3-2-1_54JXL_2022-12-07_final.stac-item
2022-12-07 10:15:41	ga_s2am_ard_3-2-1_54JWL_2022-12-07_final.stac-item
2022-12-07 10:15:45	ga_s2am_ard_3-2-1_54JVL_2022-12-07_final.stac-item
2022-12-07 10:15:48	ga_s2am_ard_3-2-1_54JUL_2022-12-07_final.stac-item
2022-12-07 10:15:50	ga_s2am_ard_3-2-1_54HXK_2022-12-07_final.stac-item
2022-12-07 10:17:26	ga_s2am_ard_3-2-1_54HVD_2022-12-07_final.stac-item
2022-12-07 10:17:33	ga_s2am_ard_3-2-1_54HTD_2022-12-07_nrt.stac-item
2022-12-07 10:17:34	ga_s2am_ard_3-2-1_53HQU_2022-12-07_nrt.stac-item
2022-12-07 10:17:40	ga_s2am_ard_3-2-1_54HUC_2022-12-07_nrt.stac-item
2022-12-07 10:17:40	ga_s2am_ard_3-2-1_53HPU_2022-12-07_nrt.stac-item
2022-12-07 10:17:41	ga_s2am_ard_3-2-1_54HTC_2022-12-07_nrt.stac-item
2022-12-07 10:17:42	ga_s2am_ard_3-2-1_53HQT_2022-12-07_nrt.stac-item
2022-12-07 10:17:44	ga_s2am_ard_3-2-1_53HPT_2022-12-07_nrt.stac-item
2022-12-07 11:50:24	ga_s2am_ard_3-2-1_51LVJ_2022-12-07_nrt.stac-item
2022-12-07 11:50:35	ga_s2am_ard_3-2-1_50LRP_2022-12-07_nrt.stac-item
2022-12-07 11:50:59	ga_s2am_ard_3-2-1_51LUG_2022-12-07_nrt.stac-item
2022-12-07 11:51:14	ga_s2am_ard_3-2-1_51LUF_2022-12-07_final.stac-item
2022-12-07 11:51:27	ga_s2am_ard_3-2-1_50LPL_2022-12-07_nrt.stac-item
2022-12-07 11:51:27	ga_s2am_ard_3-2-1_51LUE_2022-12-07_final.stac-item
2022-12-07 11:52:01	ga_s2am_ard_3-2-1_51LTC_2022-12-07_nrt.stac-item
2022-12-07 11:52:06	ga_s2am_ard_3-2-1_50LQH_2022-12-07_nrt.stac-item
2022-12-07 11:52:09	ga_s2am_ard_3-2-1_50LPH_2022-12-07_nrt.stac-item
2022-12-07 11:52:24	ga_s2am_ard_3-2-1_50KPG_2022-12-07_nrt.stac-item
2022-12-07 11:52:43	ga_s2am_ard_3-2-1_51KTV_2022-12-07_nrt.stac-item
2022-12-07 11:52:54	ga_s2am_ard_3-2-1_51KTU_2022-12-07_final.stac-item
2022-12-07 11:52:56	ga_s2am_ard_3-2-1_50KNE_2022-12-07_nrt.stac-item
2022-12-07 11:52:59	ga_s2am_ard_3-2-1_50KRD_2022-12-07_final.stac-item
2022-12-07 11:53:11	ga_s2am_ard_3-2-1_50KRC_2022-12-07_final.stac-item
2022-12-07 11:53:18	ga_s2am_ard_3-2-1_50KQC_2022-12-07_final.stac-item
2022-12-07 11:53:22	ga_s2am_ard_3-2-1_50KPC_2022-12-07_final.stac-item
2022-12-07 11:53:25	ga_s2am_ard_3-2-1_50KNC_2022-12-07_final.stac-item
2022-12-07 11:53:31	ga_s2am_ard_3-2-1_50KMC_2022-12-07_final.stac-item
2022-12-07 11:53:32	ga_s2am_ard_3-2-1_50KQB_2022-12-07_final.stac-item
2022-12-07 11:53:36	ga_s2am_ard_3-2-1_50KPB_2022-12-07_final.stac-item
2022-12-07 11:53:39	ga_s2am_ard_3-2-1_50KNB_2022-12-07_final.stac-item
2022-12-07 11:53:43	ga_s2am_ard_3-2-1_50KMB_2022-12-07_final.stac-item
2022-12-07 11:53:47	ga_s2am_ard_3-2-1_50KQA_2022-12-07_final.stac-item
2022-12-07 11:53:51	ga_s2am_ard_3-2-1_50KPA_2022-12-07_final.stac-item
2022-12-07 11:53:54	ga_s2am_ard_3-2-1_50KNA_2022-12-07_final.stac-item
2022-12-07 11:53:57	ga_s2am_ard_3-2-1_50KMA_2022-12-07_final.stac-item
2022-12-07 11:54:01	ga_s2am_ard_3-2-1_50KQV_2022-12-07_final.stac-item
2022-12-07 11:54:05	ga_s2am_ard_3-2-1_50KPV_2022-12-07_final.stac-item
2022-12-07 11:54:09	ga_s2am_ard_3-2-1_50KNV_2022-12-07_final.stac-item
2022-12-07 11:54:12	ga_s2am_ard_3-2-1_50KMV_2022-12-07_final.stac-item
2022-12-07 11:54:14	ga_s2am_ard_3-2-1_50KQU_2022-12-07_final.stac-item
2022-12-07 11:54:19	ga_s2am_ard_3-2-1_50KPU_2022-12-07_final.stac-item
2022-12-07 11:54:23	ga_s2am_ard_3-2-1_50KNU_2022-12-07_final.stac-item
2022-12-07 11:54:24	ga_s2am_ard_3-2-1_50JQT_2022-12-07_final.stac-item
2022-12-07 11:54:26	ga_s2am_ard_3-2-1_50KMU_2022-12-07_final.stac-item
2022-12-07 11:54:34	ga_s2am_ard_3-2-1_50JPT_2022-12-07_final.stac-item
2022-12-07 11:54:34	ga_s2am_ard_3-2-1_50KLU_2022-12-07_final.stac-item
2022-12-07 11:54:38	ga_s2am_ard_3-2-1_50JNT_2022-12-07_final.stac-item
2022-12-07 11:54:41	ga_s2am_ard_3-2-1_50JMT_2022-12-07_final.stac-item
2022-12-07 11:54:45	ga_s2am_ard_3-2-1_50JLT_2022-12-07_final.stac-item
2022-12-07 11:54:48	ga_s2am_ard_3-2-1_50JPS_2022-12-07_final.stac-item
2022-12-07 11:54:52	ga_s2am_ard_3-2-1_50JNS_2022-12-07_final.stac-item
2022-12-07 11:54:55	ga_s2am_ard_3-2-1_50JMS_2022-12-07_final.stac-item
2022-12-07 11:54:58	ga_s2am_ard_3-2-1_50JLS_2022-12-07_final.stac-item
2022-12-07 11:55:03	ga_s2am_ard_3-2-1_50JPR_2022-12-07_final.stac-item
2022-12-07 11:55:07	ga_s2am_ard_3-2-1_50JNR_2022-12-07_final.stac-item
2022-12-07 11:55:10	ga_s2am_ard_3-2-1_50JMR_2022-12-07_final.stac-item
2022-12-07 11:55:13	ga_s2am_ard_3-2-1_50JLR_2022-12-07_final.stac-item
2022-12-07 11:55:16	ga_s2am_ard_3-2-1_50JPQ_2022-12-07_final.stac-item
2022-12-07 11:55:21	ga_s2am_ard_3-2-1_50JNQ_2022-12-07_final.stac-item
2022-12-07 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2022-12-07_final.stac-item
2022-12-07 11:55:27	ga_s2am_ard_3-2-1_50JPP_2022-12-07_final.stac-item
2022-12-07 11:55:28	ga_s2am_ard_3-2-1_50JLQ_2022-12-07_final.stac-item
2022-12-07 11:55:35	ga_s2am_ard_3-2-1_50JNP_2022-12-07_final.stac-item
2022-12-07 11:55:39	ga_s2am_ard_3-2-1_50JMP_2022-12-07_final.stac-item
2022-12-07 11:55:42	ga_s2am_ard_3-2-1_50JLP_2022-12-07_final.stac-item
2022-12-08 09:46:03	ga_s2am_ard_3-2-1_55HED_2022-12-08_final.stac-item
2022-12-08 09:46:06	ga_s2am_ard_3-2-1_55HDD_2022-12-08_final.stac-item
2022-12-08 09:46:17	ga_s2am_ard_3-2-1_55HEC_2022-12-08_final.stac-item
2022-12-08 09:46:21	ga_s2am_ard_3-2-1_55HDC_2022-12-08_final.stac-item
2022-12-08 09:46:28	ga_s2am_ard_3-2-1_55HCC_2022-12-08_final.stac-item
2022-12-08 09:46:32	ga_s2am_ard_3-2-1_55HEB_2022-12-08_final.stac-item
2022-12-08 09:46:35	ga_s2am_ard_3-2-1_55HDB_2022-12-08_final.stac-item
2022-12-08 09:46:39	ga_s2am_ard_3-2-1_55HCB_2022-12-08_final.stac-item
2022-12-08 09:46:46	ga_s2am_ard_3-2-1_55HEA_2022-12-08_final.stac-item
2022-12-08 09:46:50	ga_s2am_ard_3-2-1_55HDA_2022-12-08_final.stac-item
2022-12-08 09:46:53	ga_s2am_ard_3-2-1_55HCA_2022-12-08_final.stac-item
2022-12-08 09:47:01	ga_s2am_ard_3-2-1_55HEV_2022-12-08_final.stac-item
2022-12-08 09:47:04	ga_s2am_ard_3-2-1_55HDV_2022-12-08_final.stac-item
2022-12-08 09:47:08	ga_s2am_ard_3-2-1_55HCV_2022-12-08_final.stac-item
2022-12-08 09:47:15	ga_s2am_ard_3-2-1_55HEU_2022-12-08_final.stac-item
2022-12-08 09:47:17	ga_s2am_ard_3-2-1_55HDU_2022-12-08_final.stac-item
2022-12-08 09:47:19	ga_s2am_ard_3-2-1_55HCU_2022-12-08_final.stac-item
2022-12-08 09:47:22	ga_s2am_ard_3-2-1_55HET_2022-12-08_final.stac-item
2022-12-08 09:47:22	ga_s2am_ard_3-2-1_55HEU_2022-12-08_final.stac-item
2022-12-08 09:47:24	ga_s2am_ard_3-2-1_55HDU_2022-12-08_final.stac-item
2022-12-08 09:47:24	ga_s2am_ard_3-2-1_55HDT_2022-12-08_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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