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
2023-10-03 10:14:15	ga_s2am_ard_3-2-1_54JWS_2023-10-03_final.stac-item
2023-10-03 10:14:30	ga_s2am_ard_3-2-1_54JWR_2023-10-03_final.stac-item
2023-10-03 10:15:02	ga_s2am_ard_3-2-1_54JVP_2023-10-03_final.stac-item
2023-10-03 10:15:11	ga_s2am_ard_3-2-1_54JVN_2023-10-03_final.stac-item
2023-10-03 10:15:18	ga_s2am_ard_3-2-1_54JVN_2023-10-03_final.stac-item
2023-10-03 10:15:24	ga_s2am_ard_3-2-1_54JXM_2023-10-03_final.stac-item
2023-10-03 10:15:28	ga_s2am_ard_3-2-1_54JWM_2023-10-03_final.stac-item
2023-10-03 10:15:42	ga_s2am_ard_3-2-1_54JWL_2023-10-03_final.stac-item
2023-10-03 10:15:49	ga_s2am_ard_3-2-1_54JUL_2023-10-03_final.stac-item
2023-10-03 10:16:00	ga_s2am_ard_3-2-1_54HVK_2023-10-03_final.stac-item
2023-10-03 10:16:02	ga_s2am_ard_3-2-1_54HXJ_2023-10-03_final.stac-item
2023-10-03 10:16:11	ga_s2am_ard_3-2-1_54HWJ_2023-10-03_final.stac-item
2023-10-03 10:16:18	ga_s2am_ard_3-2-1_54HUJ_2023-10-03_final.stac-item
2023-10-03 10:16:26	ga_s2am_ard_3-2-1_54HWH_2023-10-03_final.stac-item
2023-10-03 10:16:33	ga_s2am_ard_3-2-1_54HUH_2023-10-03_final.stac-item
2023-10-03 10:16:44	ga_s2am_ard_3-2-1_54HVG_2023-10-03_final.stac-item
2023-10-03 10:16:58	ga_s2am_ard_3-2-1_54HVF_2023-10-03_final.stac-item
2023-10-03 10:17:05	ga_s2am_ard_3-2-1_54HTF_2023-10-03_final.stac-item
2023-10-03 10:17:17	ga_s2am_ard_3-2-1_54HUE_2023-10-03_final.stac-item
2023-10-03 10:17:20	ga_s2am_ard_3-2-1_54HTE_2023-10-03_final.stac-item
2023-10-03 10:17:31	ga_s2am_ard_3-2-1_54HUD_2023-10-03_final.stac-item
2023-10-03 10:17:38	ga_s2am_ard_3-2-1_54HVC_2023-10-03_final.stac-item
2023-10-03 11:51:15	ga_s2am_ard_3-2-1_51LUF_2023-10-03_final.stac-item
2023-10-03 11:52:36	ga_s2am_ard_3-2-1_50KQF_2023-10-03_final.stac-item
2023-10-03 11:52:39	ga_s2am_ard_3-2-1_50KPF_2023-10-03_final.stac-item
2023-10-03 11:52:50	ga_s2am_ard_3-2-1_50KQE_2023-10-03_final.stac-item
2023-10-03 11:52:56	ga_s2am_ard_3-2-1_51KTU_2023-10-03_final.stac-item
2023-10-03 11:53:00	ga_s2am_ard_3-2-1_50KRD_2023-10-03_final.stac-item
2023-10-03 11:53:19	ga_s2am_ard_3-2-1_50KQC_2023-10-03_final.stac-item
2023-10-03 11:53:32	ga_s2am_ard_3-2-1_50KMC_2023-10-03_final.stac-item
2023-10-03 11:53:33	ga_s2am_ard_3-2-1_50KQB_2023-10-03_final.stac-item
2023-10-03 11:53:41	ga_s2am_ard_3-2-1_50KNB_2023-10-03_final.stac-item
2023-10-03 11:53:52	ga_s2am_ard_3-2-1_50KPA_2023-10-03_final.stac-item
2023-10-03 11:54:02	ga_s2am_ard_3-2-1_50KQV_2023-10-03_final.stac-item
2023-10-03 11:54:10	ga_s2am_ard_3-2-1_50KNV_2023-10-03_final.stac-item
2023-10-03 11:54:20	ga_s2am_ard_3-2-1_50KPU_2023-10-03_final.stac-item
2023-10-03 11:54:24	ga_s2am_ard_3-2-1_50KNU_2023-10-03_final.stac-item
2023-10-03 11:54:25	ga_s2am_ard_3-2-1_50JQT_2023-10-03_final.stac-item
2023-10-03 11:54:28	ga_s2am_ard_3-2-1_50KMU_2023-10-03_final.stac-item
2023-10-03 11:54:35	ga_s2am_ard_3-2-1_50KLU_2023-10-03_final.stac-item
2023-10-03 11:54:42	ga_s2am_ard_3-2-1_50JMT_2023-10-03_final.stac-item
2023-10-03 11:54:50	ga_s2am_ard_3-2-1_50JPS_2023-10-03_final.stac-item
2023-10-03 11:55:04	ga_s2am_ard_3-2-1_50JPR_2023-10-03_final.stac-item
2023-10-03 11:55:14	ga_s2am_ard_3-2-1_50JLR_2023-10-03_final.stac-item
2023-10-03 11:55:22	ga_s2am_ard_3-2-1_50JNQ_2023-10-03_final.stac-item
2023-10-03 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2023-10-03_final.stac-item
2023-10-03 11:55:36	ga_s2am_ard_3-2-1_50JNP_2023-10-03_final.stac-item
2023-10-03 11:55:53	ga_s2am_ard_3-2-1_50JKN_2023-10-03_final.stac-item
2023-10-03 11:56:01	ga_s2am_ard_3-2-1_50JKN_2023-10-03_final.stac-item
2023-10-03 11:56:09	ga_s2am_ard_3-2-1_50JMM_2023-10-03_final.stac-item
2023-10-03 11:56:13	ga_s2am_ard_3-2-1_50JLM_2023-10-03_final.stac-item
2023-10-03 11:56:16	ga_s2am_ard_3-2-1_50JKM_2023-10-03_final.stac-item
2023-10-03 11:56:20	ga_s2am_ard_3-2-1_50JNL_2023-10-03_final.stac-item
2023-10-03 11:56:24	ga_s2am_ard_3-2-1_50JML_2023-10-03_final.stac-item
2023-10-03 11:56:27	ga_s2am_ard_3-2-1_50JLL_2023-10-03_final.stac-item
2023-10-03 11:56:31	ga_s2am_ard_3-2-1_50HNK_2023-10-03_final.stac-item
2023-10-03 11:56:38	ga_s2am_ard_3-2-1_50HMK_2023-10-03_final.stac-item
2023-10-03 11:56:42	ga_s2am_ard_3-2-1_50HLK_2023-10-03_final.stac-item
2023-10-03 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2023-10-03_final.stac-item
2023-10-03 11:57:11	ga_s2am_ard_3-2-1_50HLH_2023-10-03_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 11:50:27	ga_s2am_ard_3-2-1_51LUJ_2023-10-13_nrt.stac-item
2023-10-13 11:50:32	ga_s2am_ard_3-2-1_51LVH_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 11:50:36	ga_s2am_ard_3-2-1_50LQP_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 11:50:46	ga_s2am_ard_3-2-1_51LTH_2023-10-13_nrt.stac-item
2023-10-13 11:50:47	ga_s2am_ard_3-2-1_50LRN_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 11:50:56	ga_s2am_ard_3-2-1_51LUG_2023-10-13_nrt.stac-item
2023-10-13 11:51:00	ga_s2am_ard_3-2-1_51LTG_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 11:51:15	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 11:51:29	ga_s2am_ard_3-2-1_51LTE_2023-10-13_nrt.stac-item
2023-10-13 11:51:30	ga_s2am_ard_3-2-1_50LRK_2023-10-13_nrt.stac-item
2023-10-13 11:51:43	ga_s2am_ard_3-2-1_51LTD_2023-10-13_nrt.stac-item
2023-10-13 11:51:45	ga_s2am_ard_3-2-1_50LRJ_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 11:52:13	ga_s2am_ard_3-2-1_51KTB_2023-10-13_nrt.stac-item
2023-10-13 11:52:13	ga_s2am_ard_3-2-1_50KRG_2023-10-13_nrt.stac-item
2023-10-13 11:52:21	ga_s2am_ard_3-2-1_50KPG_2023-10-13_nrt.stac-item
2023-10-13 11:52:28	ga_s2am_ard_3-2-1_50KRF_2023-10-13_nrt.stac-item
2023-10-13 11:52:41	ga_s2am_ard_3-2-1_51KTV_2023-10-13_nrt.stac-item
2023-10-13 11:52:43	ga_s2am_ard_3-2-1_50KRE_2023-10-13_nrt.stac-item
2023-10-13 11:56:31	ga_s2am_ard_3-2-1_49JGF_2023-10-13_nrt.stac-item
2023-10-13 11:56:41	ga_s2am_ard_3-2-1_50HKK_2023-10-13_nrt.stac-item
2023-10-13 11:56:43	ga_s2am_ard_3-2-1_49HGE_2023-10-13_nrt.stac-item
2023-10-13 11:56:56	ga_s2am_ard_3-2-1_50HKJ_2023-10-13_nrt.stac-item
2023-10-13 11:56:58	ga_s2am_ard_3-2-1_49HGD_2023-10-13_nrt.stac-item
2023-10-13 11:57:10	ga_s2am_ard_3-2-1_50HKH_2023-10-13_nrt.stac-item
2023-10-13 11:57:12	ga_s2am_ard_3-2-1_49HGC_2023-10-13_nrt.stac-item
2023-10-13 11:57:22	ga_s2am_ard_3-2-1_50HKG_2023-10-13_nrt.stac-item
2023-10-13 11:57:25	ga_s2am_ard_3-2-1_49HFB_2023-10-13_nrt.stac-item
2023-10-13 11:57:25	ga_s2am_ard_3-2-1_50HMF_2023-10-13_nrt.stac-item
2023-10-13 11:57:27	ga_s2am_ard_3-2-1_50HLF_2023-10-13_nrt.stac-item
2023-10-14 09:48:36	ga_s2am_ard_3-2-1_54GYU_2023-10-14_nrt.stac-item
2023-10-14 09:48:54	ga_s2am_ard_3-2-1_54GYT_2023-10-14_nrt.stac-item
2023-10-14 09:48:58	ga_s2am_ard_3-2-1_54GYS_2023-10-14_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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