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
2019-05-01 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-05-01_final
2019-05-01 11:34:53	ga_s2am_ard_3-2-1_50JRS_2019-05-01_final
2019-05-01 11:34:53	ga_s2am_ard_3-2-1_51JTM_2019-05-01_final
2019-05-01 11:35:54	ga_s2am_ard_3-2-1_50JQN_2019-05-01_final
2019-05-04 11:43:22	ga_s2am_ard_3-2-1_50KRC_2019-05-04_final
2019-05-04 11:43:37	ga_s2am_ard_3-2-1_50KRB_2019-05-04_final
2019-05-04 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-05-04_final
2019-05-04 11:44:23	ga_s2am_ard_3-2-1_50KQU_2019-05-04_final
2019-05-04 11:44:27	ga_s2am_ard_3-2-1_50KPU_2019-05-04_final
2019-05-04 11:44:49	ga_s2am_ard_3-2-1_50JRS_2019-05-04_final
2019-05-04 11:44:49	ga_s2am_ard_3-2-1_51JTM_2019-05-04_final
2019-05-04 11:44:56	ga_s2am_ard_3-2-1_50JPS_2019-05-04_final
2019-05-04 11:45:11	ga_s2am_ard_3-2-1_50JPR_2019-05-04_final
2019-05-04 11:45:28	ga_s2am_ard_3-2-1_50JNQ_2019-05-04_final
2019-05-04 11:45:43	ga_s2am_ard_3-2-1_50JNP_2019-05-04_final
2019-05-04 11:45:50	ga_s2am_ard_3-2-1_50JQN_2019-05-04_final
2019-05-04 11:45:54	ga_s2am_ard_3-2-1_50JPN_2019-05-04_final
2019-05-07 11:53:21	ga_s2am_ard_3-2-1_50KQC_2019-05-07_final
2019-05-07 11:53:57	ga_s2am_ard_3-2-1_50KNA_2019-05-07_final
2019-05-07 11:54:23	ga_s2am_ard_3-2-1_50KPU_2019-05-07_final
2019-05-07 11:54:50	ga_s2am_ard_3-2-1_50JMT_2019-05-07_final
2019-05-07 11:55:02	ga_s2am_ard_3-2-1_50JLS_2019-05-07_final
2019-05-07 11:55:06	ga_s2am_ard_3-2-1_50JPR_2019-05-07_final
2019-05-07 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2019-05-07_final
2019-05-07 11:55:39	ga_s2am_ard_3-2-1_50JNP_2019-05-07_final
2019-05-07 11:55:46	ga_s2am_ard_3-2-1_50JLP_2019-05-07_final
2019-05-07 11:55:50	ga_s2am_ard_3-2-1_50JKP_2019-05-07_final
2019-05-07 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-05-07_final
2019-05-10 12:03:30	ga_s2am_ard_3-2-1_50KLC_2019-05-10_final
2019-05-10 12:03:41	ga_s2am_ard_3-2-1_50KMB_2019-05-10_final
2019-05-10 12:04:07	ga_s2am_ard_3-2-1_50KMV_2019-05-10_final
2019-05-10 12:04:39	ga_s2am_ard_3-2-1_50JMT_2019-05-10_final
2019-05-10 12:04:57	ga_s2am_ard_3-2-1_50JLS_2019-05-10_final
2019-05-10 12:05:19	ga_s2am_ard_3-2-1_49JGL_2019-05-10_final
2019-05-10 12:05:30	ga_s2am_ard_3-2-1_50JKQ_2019-05-10_final
2019-05-10 12:05:33	ga_s2am_ard_3-2-1_49JGK_2019-05-10_final
2019-05-11 11:34:41	ga_s2am_ard_3-2-1_50JRT_2019-05-11_final
2019-05-11 11:34:53	ga_s2am_ard_3-2-1_51JTM_2019-05-11_final
2019-05-13 12:15:00	ga_s2am_ard_3-2-1_49JGM_2019-05-13_final
2019-05-14 11:43:22	ga_s2am_ard_3-2-1_50KRC_2019-05-14_final
2019-05-14 11:44:06	ga_s2am_ard_3-2-1_50KRV_2019-05-14_final
2019-05-14 11:44:27	ga_s2am_ard_3-2-1_50KPU_2019-05-14_final
2019-05-14 11:44:34	ga_s2am_ard_3-2-1_50JRT_2019-05-14_final
2019-05-14 11:44:35	ga_s2am_ard_3-2-1_51JTN_2019-05-14_final
2019-05-14 11:44:56	ga_s2am_ard_3-2-1_50JPS_2019-05-14_final
2019-05-14 11:45:43	ga_s2am_ard_3-2-1_50JNP_2019-05-14_final
2019-05-14 11:45:53	ga_s2am_ard_3-2-1_50JPN_2019-05-14_final
2019-05-14 11:45:56	ga_s2am_ard_3-2-1_51JTG_2019-05-14_final
2019-05-14 11:45:58	ga_s2am_ard_3-2-1_50JQM_2019-05-14_final
2019-05-14 11:45:58	ga_s2am_ard_3-2-1_50JQN_2019-05-14_final
2019-05-14 11:45:59	ga_s2am_ard_3-2-1_50JPM_2019-05-14_final
2019-05-14 11:45:59	ga_s2am_ard_3-2-1_50JPN_2019-05-14_final
2019-05-17 11:53:48	ga_s2am_ard_3-2-1_50KPA_2019-05-17_final
2019-05-17 11:54:12	ga_s2am_ard_3-2-1_50KNV_2019-05-17_final
2019-05-17 11:54:15	ga_s2am_ard_3-2-1_50KMV_2019-05-17_final
2019-05-17 11:54:17	ga_s2am_ard_3-2-1_50KQU_2019-05-17_final
2019-05-17 11:54:26	ga_s2am_ard_3-2-1_50KNU_2019-05-17_final
2019-05-17 11:54:44	ga_s2am_ard_3-2-1_50JMT_2019-05-17_final
2019-05-17 11:54:52	ga_s2am_ard_3-2-1_50JPS_2019-05-17_final
2019-05-17 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2019-05-17_final
2019-05-17 11:55:28	ga_s2am_ard_3-2-1_50JMQ_2019-05-17_final
2019-05-17 11:55:42	ga_s2am_ard_3-2-1_50JMP_2019-05-17_final
2019-05-17 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-05-17_final
2019-05-17 11:55:50	ga_s2am_ard_3-2-1_50JKP_2019-05-17_final
2019-05-17 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-05-17_final
2019-05-20 12:03:44	ga_s2am_ard_3-2-1_50KLB_2019-05-20_final
2019-05-20 12:04:43	ga_s2am_ard_3-2-1_50JLT_2019-05-20_final
2019-05-20 12:04:57	ga_s2am_ard_3-2-1_50JLS_2019-05-20_final
2019-05-20 12:05:55	ga_s2am_ard_3-2-1_50JLN_2019-05-20_final
2019-05-20 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-05-20_final
2019-05-21 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-05-21_final
2019-05-21 11:34:49	ga_s2am_ard_3-2-1_50JRS_2019-05-21_final
2019-05-21 11:34:49	ga_s2am_ard_3-2-1_51JTM_2019-05-21_final
2019-05-21 11:34:55	ga_s2am_ard_3-2-1_50JRS_2019-05-21_final
2019-05-21 11:34:55	ga_s2am_ard_3-2-1_51JTM_2019-05-21_final
2019-05-21 11:35:54	ga_s2am_ard_3-2-1_50JQN_2019-05-21_final
2019-05-24 11:43:22	ga_s2am_ard_3-2-1_50KRC_2019-05-24_final
2019-05-24 11:44:48	ga_s2am_ard_3-2-1_50JRS_2019-05-24_final
2019-05-24 11:44:59	ga_s2am_ard_3-2-1_50JPS_2019-05-24_final
2019-05-24 11:45:28	ga_s2am_ard_3-2-1_50JNQ_2019-05-24_final
2019-05-24 11:45:53	ga_s2am_ard_3-2-1_50JPN_2019-05-24_final
2019-05-27 11:53:14	ga_s2am_ard_3-2-1_50KRC_2019-05-27_final
2019-05-27 11:53:46	ga_s2am_ard_3-2-1_50KMB_2019-05-27_final
2019-05-27 11:53:56	ga_s2am_ard_3-2-1_50KNA_2019-05-27_final
2019-05-27 11:54:14	ga_s2am_ard_3-2-1_50KMV_2019-05-27_final
2019-05-27 11:54:25	ga_s2am_ard_3-2-1_50KNU_2019-05-27_final
2019-05-27 11:54:51	ga_s2am_ard_3-2-1_50JPS_2019-05-27_final
2019-05-27 11:55:01	ga_s2am_ard_3-2-1_50JLS_2019-05-27_final
2019-05-27 11:55:05	ga_s2am_ard_3-2-1_50JPR_2019-05-27_final
2019-05-27 11:55:23	ga_s2am_ard_3-2-1_50JNQ_2019-05-27_final
2019-05-27 11:55:38	ga_s2am_ard_3-2-1_50JNP_2019-05-27_final
2019-05-27 11:55:56	ga_s2am_ard_3-2-1_50JMN_2019-05-27_final
2019-05-30 12:03:40	ga_s2am_ard_3-2-1_50KMB_2019-05-30_final
2019-05-30 12:03:47	ga_s2am_ard_3-2-1_50KNA_2019-05-30_final
2019-05-30 12:03:55	ga_s2am_ard_3-2-1_50KMA_2019-05-30_final
2019-05-30 12:03:58	ga_s2am_ard_3-2-1_50KLA_2019-05-30_final
2019-05-30 12:04:56	ga_s2am_ard_3-2-1_50JLS_2019-05-30_final
2019-05-30 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2019-05-30_final
2019-05-30 12:05:54	ga_s2am_ard_3-2-1_50JLN_2019-05-30_final
2019-05-31 11:34:39	ga_s2am_ard_3-2-1_50JRT_2019-05-31_final

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

Other products

All years