Search ga_s2am_ard_3 on 2nd March 2022

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
2022-03-02 10:10:15	ga_s2am_ard_3-2-1_54LZN_2022-03-02_final
2022-03-02 10:10:44	ga_s2am_ard_3-2-1_54LZL_2022-03-02_final
2022-03-02 10:11:26	ga_s2am_ard_3-2-1_55LBC_2022-03-02_final
2022-03-02 10:11:27	ga_s2am_ard_3-2-1_54LZH_2022-03-02_final
2022-03-02 10:11:30	ga_s2am_ard_3-2-1_54LYH_2022-03-02_final
2022-03-02 10:11:42	ga_s2am_ard_3-2-1_54KZG_2022-03-02_final
2022-03-02 10:12:24	ga_s2am_ard_3-2-1_55KBU_2022-03-02_final
2022-03-02 10:12:29	ga_s2am_ard_3-2-1_54KYD_2022-03-02_final
2022-03-02 10:12:38	ga_s2am_ard_3-2-1_55KBT_2022-03-02_final
2022-03-02 10:12:43	ga_s2am_ard_3-2-1_54KYC_2022-03-02_final
2022-03-02 10:13:07	ga_s2am_ard_3-2-1_54KWB_2022-03-02_final
2022-03-02 10:13:15	ga_s2am_ard_3-2-1_54KXA_2022-03-02_final
2022-03-02 10:13:33	ga_s2am_ard_3-2-1_54KWV_2022-03-02_final
2022-03-02 10:13:48	ga_s2am_ard_3-2-1_54KWU_2022-03-02_final
2022-03-02 10:14:17	ga_s2am_ard_3-2-1_54JWS_2022-03-02_final
2022-03-02 10:14:21	ga_s2am_ard_3-2-1_54JVS_2022-03-02_final
2022-03-02 10:14:28	ga_s2am_ard_3-2-1_54JXR_2022-03-02_final
2022-03-02 10:14:35	ga_s2am_ard_3-2-1_54JVR_2022-03-02_final
2022-03-02 10:14:38	ga_s2am_ard_3-2-1_54JYQ_2022-03-02_final
2022-03-02 10:14:42	ga_s2am_ard_3-2-1_54JXQ_2022-03-02_final
2022-03-02 10:14:46	ga_s2am_ard_3-2-1_54JWQ_2022-03-02_final
2022-03-02 10:14:49	ga_s2am_ard_3-2-1_54JVQ_2022-03-02_final
2022-03-02 10:14:51	ga_s2am_ard_3-2-1_54JYP_2022-03-02_final
2022-03-02 10:15:00	ga_s2am_ard_3-2-1_54JWP_2022-03-02_final
2022-03-02 10:15:01	ga_s2am_ard_3-2-1_54JYN_2022-03-02_final
2022-03-02 10:15:04	ga_s2am_ard_3-2-1_54JVP_2022-03-02_final
2022-03-02 10:15:11	ga_s2am_ard_3-2-1_54JUP_2022-03-02_final
2022-03-02 10:15:11	ga_s2am_ard_3-2-1_54JXN_2022-03-02_final
2022-03-02 10:15:15	ga_s2am_ard_3-2-1_54JWN_2022-03-02_final
2022-03-02 10:15:22	ga_s2am_ard_3-2-1_54JUN_2022-03-02_final
2022-03-02 10:15:26	ga_s2am_ard_3-2-1_54JXM_2022-03-02_final
2022-03-02 10:15:29	ga_s2am_ard_3-2-1_54JWM_2022-03-02_final
2022-03-02 10:15:33	ga_s2am_ard_3-2-1_54JVM_2022-03-02_final
2022-03-02 10:15:36	ga_s2am_ard_3-2-1_54JUM_2022-03-02_final
2022-03-02 10:15:44	ga_s2am_ard_3-2-1_54JWL_2022-03-02_final
2022-03-02 10:15:48	ga_s2am_ard_3-2-1_54JVL_2022-03-02_final
2022-03-02 10:15:51	ga_s2am_ard_3-2-1_54JUL_2022-03-02_final
2022-03-02 10:15:53	ga_s2am_ard_3-2-1_54HXK_2022-03-02_final
2022-03-02 10:15:58	ga_s2am_ard_3-2-1_54HWK_2022-03-02_final
2022-03-02 10:16:02	ga_s2am_ard_3-2-1_54HVK_2022-03-02_final
2022-03-02 10:16:03	ga_s2am_ard_3-2-1_54HXJ_2022-03-02_final
2022-03-02 10:16:05	ga_s2am_ard_3-2-1_54HUK_2022-03-02_final
2022-03-02 10:16:13	ga_s2am_ard_3-2-1_54HWJ_2022-03-02_final
2022-03-02 10:16:17	ga_s2am_ard_3-2-1_54HVJ_2022-03-02_final
2022-03-02 10:16:20	ga_s2am_ard_3-2-1_54HUJ_2022-03-02_final
2022-03-02 10:16:34	ga_s2am_ard_3-2-1_54HUH_2022-03-02_final
2022-03-02 10:16:37	ga_s2am_ard_3-2-1_54HTH_2022-03-02_final
2022-03-02 10:16:42	ga_s2am_ard_3-2-1_54HWG_2022-03-02_final
2022-03-02 10:16:46	ga_s2am_ard_3-2-1_54HVG_2022-03-02_final
2022-03-02 10:16:49	ga_s2am_ard_3-2-1_54HUG_2022-03-02_final
2022-03-02 10:16:52	ga_s2am_ard_3-2-1_54HTG_2022-03-02_final
2022-03-02 10:16:55	ga_s2am_ard_3-2-1_53HQB_2022-03-02_final
2022-03-02 10:16:56	ga_s2am_ard_3-2-1_54HWF_2022-03-02_final
2022-03-02 10:17:00	ga_s2am_ard_3-2-1_54HVF_2022-03-02_final
2022-03-02 10:17:07	ga_s2am_ard_3-2-1_54HWE_2022-03-02_final
2022-03-02 10:17:14	ga_s2am_ard_3-2-1_54HVE_2022-03-02_final
2022-03-02 10:17:18	ga_s2am_ard_3-2-1_54HUE_2022-03-02_final.stac-item
2022-03-02 10:17:21	ga_s2am_ard_3-2-1_54HTE_2022-03-02_final.stac-item
2022-03-02 10:17:23	ga_s2am_ard_3-2-1_53HQV_2022-03-02_final.stac-item
2022-03-02 10:17:29	ga_s2am_ard_3-2-1_54HVD_2022-03-02_final
2022-03-02 10:17:41	ga_s2am_ard_3-2-1_54HVC_2022-03-02_final.stac-item
2022-03-02 11:51:17	ga_s2am_ard_3-2-1_51LUF_2022-03-02_final
2022-03-02 11:52:57	ga_s2am_ard_3-2-1_51KTU_2022-03-02_final
2022-03-02 11:53:04	ga_s2am_ard_3-2-1_50KQD_2022-03-02_final.stac-item
2022-03-02 11:53:21	ga_s2am_ard_3-2-1_50KQC_2022-03-02_final
2022-03-02 11:53:28	ga_s2am_ard_3-2-1_50KNC_2022-03-02_final
2022-03-02 11:53:34	ga_s2am_ard_3-2-1_50KMC_2022-03-02_final
2022-03-02 11:53:42	ga_s2am_ard_3-2-1_50KNB_2022-03-02_final
2022-03-02 11:53:46	ga_s2am_ard_3-2-1_50KMB_2022-03-02_final
2022-03-02 11:53:53	ga_s2am_ard_3-2-1_50KPA_2022-03-02_final
2022-03-02 11:54:11	ga_s2am_ard_3-2-1_50KNV_2022-03-02_final
2022-03-02 11:54:15	ga_s2am_ard_3-2-1_50KMV_2022-03-02_final
2022-03-02 11:54:26	ga_s2am_ard_3-2-1_50KNU_2022-03-02_final
2022-03-02 11:54:29	ga_s2am_ard_3-2-1_50KMU_2022-03-02_final
2022-03-02 11:55:06	ga_s2am_ard_3-2-1_50JPR_2022-03-02_final
2022-03-02 11:55:10	ga_s2am_ard_3-2-1_50JNR_2022-03-02_final
2022-03-02 11:55:16	ga_s2am_ard_3-2-1_50JLR_2022-03-02_final
2022-03-02 11:55:19	ga_s2am_ard_3-2-1_50JPQ_2022-03-02_final
2022-03-02 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2022-03-02_final
2022-03-02 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2022-03-02_final
2022-03-02 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2022-03-02_final
2022-03-02 11:55:38	ga_s2am_ard_3-2-1_50JNP_2022-03-02_final
2022-03-02 11:55:42	ga_s2am_ard_3-2-1_50JMP_2022-03-02_final
2022-03-02 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-03-02_final
2022-03-02 11:55:50	ga_s2am_ard_3-2-1_50JKP_2022-03-02_final
2022-03-02 11:55:53	ga_s2am_ard_3-2-1_50JNN_2022-03-02_final
2022-03-02 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-03-02_final
2022-03-02 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-03-02_final
2022-03-02 11:56:03	ga_s2am_ard_3-2-1_50JKN_2022-03-02_final
2022-03-02 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-03-02_final
2022-03-02 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-03-02_final
2022-03-02 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-03-02_final
2022-03-02 11:56:21	ga_s2am_ard_3-2-1_50JNL_2022-03-02_final
2022-03-02 11:56:25	ga_s2am_ard_3-2-1_50JML_2022-03-02_final
2022-03-02 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-03-02_final
2022-03-02 11:56:33	ga_s2am_ard_3-2-1_50HNK_2022-03-02_final
2022-03-02 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-03-02_final
2022-03-02 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2022-03-02_final
2022-03-02 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-03-02_final
2022-03-02 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-03-02_final

Return to ga_s2am_ard_3 on 2nd March 2022 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

2022

March

2nd