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
2022-06-27 11:45:13	ga_s2am_ard_3-2-1_50JPS_2022-06-27_final
2022-06-30 11:55:33	ga_s2am_ard_3-2-1_50JNQ_2022-06-30_final
2022-08-02 12:04:09	ga_s2am_ard_3-2-1_49KHR_2022-08-02_final
2022-08-02 12:04:37	ga_s2am_ard_3-2-1_49KGP_2022-08-02_final
2022-08-02 12:04:42	ga_s2am_ard_3-2-1_49KHP_2022-08-02_final
2022-08-02 12:04:53	ga_s2am_ard_3-2-1_49JHN_2022-08-02_final
2022-08-02 12:04:53	ga_s2am_ard_3-2-1_50JKT_2022-08-02_final
2022-08-02 12:04:56	ga_s2am_ard_3-2-1_49JGN_2022-08-02_final
2022-08-02 12:04:59	ga_s2am_ard_3-2-1_50JMS_2022-08-02_final
2022-08-02 12:05:04	ga_s2am_ard_3-2-1_50JLS_2022-08-02_final
2022-08-02 12:05:07	ga_s2am_ard_3-2-1_50JKS_2022-08-02_final
2022-08-02 12:05:18	ga_s2am_ard_3-2-1_50JLR_2022-08-02_final
2022-08-02 12:05:48	ga_s2am_ard_3-2-1_50JLP_2022-08-02_final
2022-08-02 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-08-02_final
2022-08-02 12:06:02	ga_s2am_ard_3-2-1_50JLN_2022-08-02_final
2022-08-02 12:06:06	ga_s2am_ard_3-2-1_50JKN_2022-08-02_final
2022-08-02 12:06:14	ga_s2am_ard_3-2-1_50JLM_2022-08-02_final
2022-08-02 12:06:20	ga_s2am_ard_3-2-1_50JKM_2022-08-02_final
2022-08-02 12:06:24	ga_s2am_ard_3-2-1_50JLL_2022-08-02_final
2022-08-03 11:35:00	ga_s2am_ard_3-2-1_50JRS_2022-08-03_final
2022-08-05 12:14:09	ga_s2am_ard_3-2-1_49KGR_2022-08-05_final
2022-08-05 12:14:24	ga_s2am_ard_3-2-1_49KGQ_2022-08-05_final
2022-08-05 12:14:38	ga_s2am_ard_3-2-1_49KGP_2022-08-05_final
2022-08-05 12:14:42	ga_s2am_ard_3-2-1_49JHN_2022-08-05_final
2022-08-05 12:14:52	ga_s2am_ard_3-2-1_49JGN_2022-08-05_final
2022-08-05 12:14:56	ga_s2am_ard_3-2-1_49JFN_2022-08-05_final
2022-08-06 11:44:56	ga_s2am_ard_3-2-1_50JRS_2022-08-06_final
2022-08-06 11:45:04	ga_s2am_ard_3-2-1_50JPS_2022-08-06_final
2022-08-06 11:45:11	ga_s2am_ard_3-2-1_50JPR_2022-08-06_final
2022-08-06 11:45:11	ga_s2am_ard_3-2-1_50JPS_2022-08-06_final
2022-08-06 11:45:18	ga_s2am_ard_3-2-1_50JPR_2022-08-06_final
2022-08-06 11:45:36	ga_s2am_ard_3-2-1_50JNQ_2022-08-06_final
2022-08-06 11:46:05	ga_s2am_ard_3-2-1_50JNN_2022-08-06_final
2022-08-09 11:55:00	ga_s2am_ard_3-2-1_50JPS_2022-08-09_final
2022-08-09 11:55:07	ga_s2am_ard_3-2-1_50JMS_2022-08-09_final
2022-08-09 11:55:14	ga_s2am_ard_3-2-1_50JPR_2022-08-09_final
2022-08-09 11:55:21	ga_s2am_ard_3-2-1_50JMR_2022-08-09_final
2022-08-09 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-08-09_final
2022-08-09 11:55:36	ga_s2am_ard_3-2-1_50JMQ_2022-08-09_final
2022-08-09 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-08-09_final
2022-08-09 11:55:46	ga_s2am_ard_3-2-1_50JNP_2022-08-09_final
2022-08-09 11:55:53	ga_s2am_ard_3-2-1_50JLP_2022-08-09_final
2022-08-09 11:56:05	ga_s2am_ard_3-2-1_50JMN_2022-08-09_final
2022-08-09 11:56:08	ga_s2am_ard_3-2-1_50JLN_2022-08-09_final
2022-08-09 11:56:26	ga_s2am_ard_3-2-1_50JKM_2022-08-09_final
2022-08-12 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-08-12_final
2022-08-12 12:04:30	ga_s2am_ard_3-2-1_49KGQ_2022-08-12_final
2022-08-12 12:04:40	ga_s2am_ard_3-2-1_49KHP_2022-08-12_final
2022-08-12 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-08-12_final
2022-08-12 12:04:54	ga_s2am_ard_3-2-1_49JHN_2022-08-12_final
2022-08-12 12:04:55	ga_s2am_ard_3-2-1_50JKT_2022-08-12_final
2022-08-12 12:04:58	ga_s2am_ard_3-2-1_49JGN_2022-08-12_final
2022-08-12 12:05:01	ga_s2am_ard_3-2-1_50JMS_2022-08-12_final
2022-08-12 12:05:11	ga_s2am_ard_3-2-1_50JMR_2022-08-12_final
2022-08-12 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-08-12_final
2022-08-12 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-08-12_final
2022-08-12 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-08-12_final
2022-08-12 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-12_final
2022-08-12 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-08-12_final
2022-08-12 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-12_final
2022-08-12 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-08-12_final
2022-08-12 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-08-12_final
2022-08-13 11:34:49	ga_s2am_ard_3-2-1_50JRT_2022-08-13_final
2022-08-13 11:35:01	ga_s2am_ard_3-2-1_50JRS_2022-08-13_final
2022-08-15 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-08-15_final
2022-08-15 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-15_final
2022-08-15 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-08-15_final
2022-08-15 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-08-15_final
2022-08-15 12:14:54	ga_s2am_ard_3-2-1_49JGN_2022-08-15_final
2022-08-15 12:14:58	ga_s2am_ard_3-2-1_49JFN_2022-08-15_final
2022-08-15 12:15:08	ga_s2am_ard_3-2-1_49JGM_2022-08-15_final
2022-08-15 12:15:32	ga_s2am_ard_3-2-1_49JGK_2022-08-15_final
2022-08-16 11:44:57	ga_s2am_ard_3-2-1_50JRS_2022-08-16_final
2022-08-16 11:45:05	ga_s2am_ard_3-2-1_50JPS_2022-08-16_final
2022-08-16 11:45:19	ga_s2am_ard_3-2-1_50JPR_2022-08-16_final
2022-08-16 11:45:52	ga_s2am_ard_3-2-1_50JNP_2022-08-16_final
2022-08-16 11:46:06	ga_s2am_ard_3-2-1_50JNN_2022-08-16_final
2022-08-19 11:55:01	ga_s2am_ard_3-2-1_50JPS_2022-08-19_final
2022-08-19 11:55:07	ga_s2am_ard_3-2-1_50JMS_2022-08-19_final
2022-08-19 11:55:10	ga_s2am_ard_3-2-1_50JLS_2022-08-19_final
2022-08-19 11:55:33	ga_s2am_ard_3-2-1_50JNQ_2022-08-19_final
2022-08-19 11:55:51	ga_s2am_ard_3-2-1_50JMP_2022-08-19_final
2022-08-19 11:55:54	ga_s2am_ard_3-2-1_50JLP_2022-08-19_final
2022-08-19 11:56:02	ga_s2am_ard_3-2-1_50JNN_2022-08-19_final
2022-08-19 11:56:09	ga_s2am_ard_3-2-1_50JLN_2022-08-19_final
2022-08-22 12:04:12	ga_s2am_ard_3-2-1_49KHR_2022-08-22_final
2022-08-22 12:04:26	ga_s2am_ard_3-2-1_49KHQ_2022-08-22_final
2022-08-22 12:04:55	ga_s2am_ard_3-2-1_49JHN_2022-08-22_final
2022-08-22 12:04:59	ga_s2am_ard_3-2-1_49JGN_2022-08-22_final
2022-08-22 12:05:01	ga_s2am_ard_3-2-1_50JMS_2022-08-22_final
2022-08-22 12:05:06	ga_s2am_ard_3-2-1_50JLS_2022-08-22_final
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_50JLR_2022-08-22_final
2022-08-22 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-08-22_final
2022-08-22 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-22_final
2022-08-23 11:35:02	ga_s2am_ard_3-2-1_50JRS_2022-08-23_final
2022-08-25 12:14:11	ga_s2am_ard_3-2-1_49KGR_2022-08-25_final
2022-08-25 12:14:21	ga_s2am_ard_3-2-1_49KHQ_2022-08-25_final
2022-08-25 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-08-25_final
2022-08-26 11:45:05	ga_s2am_ard_3-2-1_50JPS_2022-08-26_final
2022-08-26 11:45:13	ga_s2am_ard_3-2-1_50JPS_2022-08-26_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