Search ga_s2am_ard_3 on 1st 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

95 results

Time (local)	Label
2022-03-01 10:40:31	ga_s2am_ard_3-2-1_53LPH_2022-03-01_final.stac-item
2022-03-01 10:40:40	ga_s2am_ard_3-2-1_53LQG_2022-03-01_final.stac-item
2022-03-01 10:40:43	ga_s2am_ard_3-2-1_53LPG_2022-03-01_final
2022-03-01 10:40:54	ga_s2am_ard_3-2-1_53LQF_2022-03-01_final.stac-item
2022-03-01 10:40:57	ga_s2am_ard_3-2-1_53LPF_2022-03-01_final
2022-03-01 10:41:09	ga_s2am_ard_3-2-1_53LQE_2022-03-01_final.stac-item
2022-03-01 10:41:12	ga_s2am_ard_3-2-1_53LPE_2022-03-01_final
2022-03-01 10:41:23	ga_s2am_ard_3-2-1_53LQD_2022-03-01_final
2022-03-01 10:41:27	ga_s2am_ard_3-2-1_53LPD_2022-03-01_final
2022-03-01 10:41:33	ga_s2am_ard_3-2-1_53LND_2022-03-01_final
2022-03-01 10:41:38	ga_s2am_ard_3-2-1_53LQC_2022-03-01_final
2022-03-01 10:41:41	ga_s2am_ard_3-2-1_53LPC_2022-03-01_final
2022-03-01 10:41:45	ga_s2am_ard_3-2-1_53LNC_2022-03-01_final
2022-03-01 10:41:46	ga_s2am_ard_3-2-1_54KTG_2022-03-01_final
2022-03-01 10:41:49	ga_s2am_ard_3-2-1_53KRB_2022-03-01_final
2022-03-01 10:41:52	ga_s2am_ard_3-2-1_53KQB_2022-03-01_final
2022-03-01 10:41:56	ga_s2am_ard_3-2-1_53KPB_2022-03-01_final
2022-03-01 10:41:57	ga_s2am_ard_3-2-1_54KTF_2022-03-01_final
2022-03-01 10:41:59	ga_s2am_ard_3-2-1_53KNB_2022-03-01_final
2022-03-01 10:42:03	ga_s2am_ard_3-2-1_53KRA_2022-03-01_final
2022-03-01 10:42:07	ga_s2am_ard_3-2-1_53KQA_2022-03-01_final
2022-03-01 10:42:10	ga_s2am_ard_3-2-1_53KPA_2022-03-01_final
2022-03-01 10:42:13	ga_s2am_ard_3-2-1_53KNA_2022-03-01_final
2022-03-01 10:42:15	ga_s2am_ard_3-2-1_53KRV_2022-03-01_final
2022-03-01 10:42:21	ga_s2am_ard_3-2-1_53KQV_2022-03-01_final
2022-03-01 10:42:25	ga_s2am_ard_3-2-1_53KPV_2022-03-01_final
2022-03-01 10:42:25	ga_s2am_ard_3-2-1_53KRU_2022-03-01_final
2022-03-01 10:42:28	ga_s2am_ard_3-2-1_53KNV_2022-03-01_final
2022-03-01 10:42:35	ga_s2am_ard_3-2-1_53KQU_2022-03-01_final
2022-03-01 10:42:39	ga_s2am_ard_3-2-1_53KPU_2022-03-01_final
2022-03-01 10:42:42	ga_s2am_ard_3-2-1_53KNU_2022-03-01_final
2022-03-01 10:42:47	ga_s2am_ard_3-2-1_53KMU_2022-03-01_final
2022-03-01 10:42:50	ga_s2am_ard_3-2-1_53KQT_2022-03-01_final
2022-03-01 10:42:54	ga_s2am_ard_3-2-1_53KPT_2022-03-01_final
2022-03-01 10:42:57	ga_s2am_ard_3-2-1_53KNT_2022-03-01_final
2022-03-01 10:43:00	ga_s2am_ard_3-2-1_53KMT_2022-03-01_final
2022-03-01 10:43:04	ga_s2am_ard_3-2-1_53KQS_2022-03-01_final
2022-03-01 10:43:08	ga_s2am_ard_3-2-1_53KPS_2022-03-01_final
2022-03-01 10:43:12	ga_s2am_ard_3-2-1_53KNS_2022-03-01_final
2022-03-01 10:43:15	ga_s2am_ard_3-2-1_53KMS_2022-03-01_final
2022-03-01 10:43:18	ga_s2am_ard_3-2-1_53KQR_2022-03-01_final
2022-03-01 10:43:22	ga_s2am_ard_3-2-1_53KPR_2022-03-01_final
2022-03-01 10:43:26	ga_s2am_ard_3-2-1_53KNR_2022-03-01_final
2022-03-01 10:43:28	ga_s2am_ard_3-2-1_53KQQ_2022-03-01_final
2022-03-01 10:43:29	ga_s2am_ard_3-2-1_53KMR_2022-03-01_final
2022-03-01 10:43:37	ga_s2am_ard_3-2-1_53KPQ_2022-03-01_final
2022-03-01 10:43:41	ga_s2am_ard_3-2-1_53KNQ_2022-03-01_final
2022-03-01 10:43:44	ga_s2am_ard_3-2-1_53KMQ_2022-03-01_final
2022-03-01 10:43:48	ga_s2am_ard_3-2-1_53KLQ_2022-03-01_final
2022-03-01 10:43:51	ga_s2am_ard_3-2-1_53KPP_2022-03-01_final
2022-03-01 10:43:55	ga_s2am_ard_3-2-1_53KNP_2022-03-01_final
2022-03-01 10:43:58	ga_s2am_ard_3-2-1_53KMP_2022-03-01_final
2022-03-01 10:44:01	ga_s2am_ard_3-2-1_53KLP_2022-03-01_final
2022-03-01 10:44:06	ga_s2am_ard_3-2-1_53JPN_2022-03-01_final
2022-03-01 10:44:10	ga_s2am_ard_3-2-1_53JNN_2022-03-01_final
2022-03-01 10:44:13	ga_s2am_ard_3-2-1_53JMN_2022-03-01_final
2022-03-01 10:44:16	ga_s2am_ard_3-2-1_53JLN_2022-03-01_final
2022-03-01 10:44:20	ga_s2am_ard_3-2-1_53JPM_2022-03-01_final
2022-03-01 10:44:24	ga_s2am_ard_3-2-1_53JNM_2022-03-01_final
2022-03-01 10:44:27	ga_s2am_ard_3-2-1_53JMM_2022-03-01_final
2022-03-01 10:44:31	ga_s2am_ard_3-2-1_53JLM_2022-03-01_final
2022-03-01 10:44:31	ga_s2am_ard_3-2-1_53JPL_2022-03-01_final
2022-03-01 10:44:38	ga_s2am_ard_3-2-1_53JNL_2022-03-01_final
2022-03-01 10:44:42	ga_s2am_ard_3-2-1_53JML_2022-03-01_final
2022-03-01 10:44:45	ga_s2am_ard_3-2-1_53JLL_2022-03-01_final
2022-03-01 10:44:51	ga_s2am_ard_3-2-1_53JKL_2022-03-01_final
2022-03-01 10:44:53	ga_s2am_ard_3-2-1_53JNK_2022-03-01_final
2022-03-01 10:44:57	ga_s2am_ard_3-2-1_53JMK_2022-03-01_final
2022-03-01 10:45:00	ga_s2am_ard_3-2-1_53JLK_2022-03-01_final
2022-03-01 10:45:03	ga_s2am_ard_3-2-1_53JKK_2022-03-01_final
2022-03-01 10:45:08	ga_s2am_ard_3-2-1_53JNJ_2022-03-01_final
2022-03-01 10:45:11	ga_s2am_ard_3-2-1_53JMJ_2022-03-01_final
2022-03-01 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2022-03-01_final
2022-03-01 10:45:17	ga_s2am_ard_3-2-1_53JKJ_2022-03-01_final
2022-03-01 10:45:22	ga_s2am_ard_3-2-1_53JNH_2022-03-01_final
2022-03-01 10:45:26	ga_s2am_ard_3-2-1_53JMH_2022-03-01_final
2022-03-01 10:45:29	ga_s2am_ard_3-2-1_53JLH_2022-03-01_final
2022-03-01 10:45:32	ga_s2am_ard_3-2-1_53JKH_2022-03-01_final
2022-03-01 10:45:35	ga_s2am_ard_3-2-1_53JNG_2022-03-01_final
2022-03-01 10:45:40	ga_s2am_ard_3-2-1_53JMG_2022-03-01_final
2022-03-01 10:45:44	ga_s2am_ard_3-2-1_53JLG_2022-03-01_final
2022-03-01 10:45:45	ga_s2am_ard_3-2-1_53JNF_2022-03-01_final
2022-03-01 10:45:47	ga_s2am_ard_3-2-1_53JKG_2022-03-01_final
2022-03-01 10:45:50	ga_s2am_ard_3-2-1_52JGM_2022-03-01_final
2022-03-01 10:45:54	ga_s2am_ard_3-2-1_53JMF_2022-03-01_final
2022-03-01 10:45:58	ga_s2am_ard_3-2-1_53JLF_2022-03-01_final
2022-03-01 10:46:01	ga_s2am_ard_3-2-1_53JKF_2022-03-01_final
2022-03-01 10:46:03	ga_s2am_ard_3-2-1_52JGL_2022-03-01_final
2022-03-01 10:46:09	ga_s2am_ard_3-2-1_53HME_2022-03-01_final
2022-03-01 10:46:13	ga_s2am_ard_3-2-1_53HLE_2022-03-01_final
2022-03-01 10:46:16	ga_s2am_ard_3-2-1_53HKE_2022-03-01_final.stac-item
2022-03-01 10:46:18	ga_s2am_ard_3-2-1_52HGK_2022-03-01_final.stac-item
2022-03-01 10:46:24	ga_s2am_ard_3-2-1_53HMD_2022-03-01_final
2022-03-01 10:46:27	ga_s2am_ard_3-2-1_53HLD_2022-03-01_final
2022-03-01 10:46:34	ga_s2am_ard_3-2-1_53HMC_2022-03-01_final.stac-item

Return to ga_s2am_ard_3 on 1st 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

1st