Search ga_s2bm_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
2018-05-07 11:53:53	ga_s2bm_ard_3-2-1_50JKM_2018-05-07_final
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JLL_2018-05-10_final
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JKM_2018-05-10_final
2018-05-10 12:05:05	ga_s2bm_ard_3-2-1_50JLM_2018-05-10_final
2018-05-17 11:49:25	ga_s2bm_ard_3-2-1_50JKM_2018-05-17_final
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JLL_2018-05-20_final
2018-05-20 12:02:47	ga_s2bm_ard_3-2-1_50JKM_2018-05-20_final
2018-05-30 12:04:45	ga_s2bm_ard_3-2-1_50JLL_2018-05-30_final
2018-05-30 12:04:45	ga_s2bm_ard_3-2-1_50JKM_2018-05-30_final
2022-06-02 11:43:36	ga_s2bm_ard_3-2-1_50KQB_2022-06-02_final
2022-06-02 11:43:51	ga_s2bm_ard_3-2-1_50KQA_2022-06-02_final
2022-06-02 11:44:30	ga_s2bm_ard_3-2-1_50JRT_2022-06-02_final
2022-06-02 11:44:37	ga_s2bm_ard_3-2-1_50JPT_2022-06-02_final
2022-06-05 11:53:31	ga_s2bm_ard_3-2-1_50KMC_2022-06-05_final
2022-06-05 11:53:32	ga_s2bm_ard_3-2-1_50KQB_2022-06-05_final
2022-06-05 11:53:39	ga_s2bm_ard_3-2-1_50KNB_2022-06-05_final
2022-06-05 11:53:47	ga_s2bm_ard_3-2-1_50KQA_2022-06-05_final
2022-06-05 11:53:51	ga_s2bm_ard_3-2-1_50KPA_2022-06-05_final
2022-06-05 11:54:03	ga_s2bm_ard_3-2-1_50KNV_2022-06-05_final
2022-06-05 11:54:09	ga_s2bm_ard_3-2-1_50KNV_2022-06-05_final
2022-06-05 11:54:23	ga_s2bm_ard_3-2-1_50KNU_2022-06-05_final
2022-06-05 11:54:26	ga_s2bm_ard_3-2-1_50KMU_2022-06-05_final
2022-06-05 11:54:34	ga_s2bm_ard_3-2-1_50JPT_2022-06-05_final
2022-06-05 11:54:34	ga_s2bm_ard_3-2-1_50KLU_2022-06-05_final
2022-06-05 11:54:41	ga_s2bm_ard_3-2-1_50JMT_2022-06-05_final
2022-06-05 11:54:45	ga_s2bm_ard_3-2-1_50JLT_2022-06-05_final
2022-06-05 11:55:47	ga_s2bm_ard_3-2-1_50JKP_2022-06-05_final
2022-06-08 12:03:25	ga_s2bm_ard_3-2-1_50KMC_2022-06-08_final
2022-06-08 12:03:28	ga_s2bm_ard_3-2-1_50KLC_2022-06-08_final
2022-06-08 12:03:35	ga_s2bm_ard_3-2-1_50KNB_2022-06-08_final
2022-06-08 12:04:12	ga_s2bm_ard_3-2-1_50KLV_2022-06-08_final
2022-06-08 12:04:23	ga_s2bm_ard_3-2-1_50KMU_2022-06-08_final
2022-06-08 12:04:26	ga_s2bm_ard_3-2-1_50KLU_2022-06-08_final
2022-06-08 12:04:37	ga_s2bm_ard_3-2-1_50JMT_2022-06-08_final
2022-06-08 12:04:39	ga_s2bm_ard_3-2-1_50JLT_2022-06-08_final
2022-06-08 12:04:48	ga_s2bm_ard_3-2-1_50JKT_2022-06-08_final
2022-06-08 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2022-06-08_final
2022-06-08 12:05:28	ga_s2bm_ard_3-2-1_50JKQ_2022-06-08_final
2022-06-08 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2022-06-08_final
2022-06-08 12:05:57	ga_s2bm_ard_3-2-1_50JKN_2022-06-08_final
2022-06-11 12:14:58	ga_s2bm_ard_3-2-1_49JGM_2022-06-11_final
2022-06-12 11:43:39	ga_s2bm_ard_3-2-1_50KQB_2022-06-12_final
2022-06-12 11:43:50	ga_s2bm_ard_3-2-1_50KRA_2022-06-12_final
2022-06-12 11:43:54	ga_s2bm_ard_3-2-1_50KQA_2022-06-12_final
2022-06-12 11:44:33	ga_s2bm_ard_3-2-1_50JRT_2022-06-12_final
2022-06-12 11:44:40	ga_s2bm_ard_3-2-1_50JPT_2022-06-12_final
2022-06-15 11:53:34	ga_s2bm_ard_3-2-1_50KMC_2022-06-15_final
2022-06-15 11:53:35	ga_s2bm_ard_3-2-1_50KQB_2022-06-15_final
2022-06-15 11:53:42	ga_s2bm_ard_3-2-1_50KNB_2022-06-15_final
2022-06-15 11:53:50	ga_s2bm_ard_3-2-1_50KQA_2022-06-15_final
2022-06-15 11:53:53	ga_s2bm_ard_3-2-1_50KPA_2022-06-15_final
2022-06-15 11:54:06	ga_s2bm_ard_3-2-1_50KNV_2022-06-15_final
2022-06-15 11:54:12	ga_s2bm_ard_3-2-1_50KNV_2022-06-15_final
2022-06-15 11:54:26	ga_s2bm_ard_3-2-1_50KNU_2022-06-15_final
2022-06-15 11:54:29	ga_s2bm_ard_3-2-1_50KMU_2022-06-15_final
2022-06-15 11:54:36	ga_s2bm_ard_3-2-1_50KLU_2022-06-15_final
2022-06-15 11:54:37	ga_s2bm_ard_3-2-1_50JPT_2022-06-15_final
2022-06-15 11:54:44	ga_s2bm_ard_3-2-1_50JMT_2022-06-15_final
2022-06-15 11:54:48	ga_s2bm_ard_3-2-1_50JLT_2022-06-15_final
2022-06-18 12:03:27	ga_s2bm_ard_3-2-1_50KMC_2022-06-18_final
2022-06-18 12:03:31	ga_s2bm_ard_3-2-1_50KLC_2022-06-18_final
2022-06-18 12:03:37	ga_s2bm_ard_3-2-1_50KNB_2022-06-18_final
2022-06-18 12:04:14	ga_s2bm_ard_3-2-1_50KLV_2022-06-18_final
2022-06-18 12:04:25	ga_s2bm_ard_3-2-1_50KMU_2022-06-18_final
2022-06-18 12:04:29	ga_s2bm_ard_3-2-1_50KLU_2022-06-18_final
2022-06-18 12:04:42	ga_s2bm_ard_3-2-1_50JLT_2022-06-18_final
2022-06-18 12:04:50	ga_s2bm_ard_3-2-1_50JKT_2022-06-18_final
2022-06-18 12:05:01	ga_s2bm_ard_3-2-1_49JHM_2022-06-18_final
2022-06-18 12:05:16	ga_s2bm_ard_3-2-1_50JKR_2022-06-18_final
2022-06-18 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2022-06-18_final
2022-06-18 12:05:48	ga_s2bm_ard_3-2-1_49JGJ_2022-06-18_final
2022-06-21 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2022-06-21_final
2022-06-22 11:43:41	ga_s2bm_ard_3-2-1_50KQB_2022-06-22_final
2022-06-22 11:43:56	ga_s2bm_ard_3-2-1_50KQA_2022-06-22_final
2022-06-22 11:44:35	ga_s2bm_ard_3-2-1_50JRT_2022-06-22_final
2022-06-22 11:44:42	ga_s2bm_ard_3-2-1_50JPT_2022-06-22_final
2022-06-25 11:53:35	ga_s2bm_ard_3-2-1_50KMC_2022-06-25_final
2022-06-25 11:53:36	ga_s2bm_ard_3-2-1_50KQB_2022-06-25_final
2022-06-25 11:53:44	ga_s2bm_ard_3-2-1_50KNB_2022-06-25_final
2022-06-25 11:53:51	ga_s2bm_ard_3-2-1_50KQA_2022-06-25_final
2022-06-25 11:53:55	ga_s2bm_ard_3-2-1_50KPA_2022-06-25_final
2022-06-25 11:54:07	ga_s2bm_ard_3-2-1_50KNV_2022-06-25_final
2022-06-25 11:54:14	ga_s2bm_ard_3-2-1_50KNV_2022-06-25_final
2022-06-25 11:54:27	ga_s2bm_ard_3-2-1_50KNU_2022-06-25_final
2022-06-25 11:54:31	ga_s2bm_ard_3-2-1_50KMU_2022-06-25_final
2022-06-25 11:54:38	ga_s2bm_ard_3-2-1_50KLU_2022-06-25_final
2022-06-25 11:54:38	ga_s2bm_ard_3-2-1_50JPT_2022-06-25_final
2022-06-25 11:54:49	ga_s2bm_ard_3-2-1_50JLT_2022-06-25_final
2022-06-25 11:55:51	ga_s2bm_ard_3-2-1_50JKP_2022-06-25_final
2022-06-28 12:03:28	ga_s2bm_ard_3-2-1_50KMC_2022-06-28_final
2022-06-28 12:03:32	ga_s2bm_ard_3-2-1_50KLC_2022-06-28_final
2022-06-28 12:03:38	ga_s2bm_ard_3-2-1_50KNB_2022-06-28_final
2022-06-28 12:04:15	ga_s2bm_ard_3-2-1_50KLV_2022-06-28_final
2022-06-28 12:04:26	ga_s2bm_ard_3-2-1_50KMU_2022-06-28_final
2022-06-28 12:04:30	ga_s2bm_ard_3-2-1_50KLU_2022-06-28_final
2022-06-28 12:04:40	ga_s2bm_ard_3-2-1_50JMT_2022-06-28_final
2022-06-28 12:04:43	ga_s2bm_ard_3-2-1_50JLT_2022-06-28_final
2022-06-28 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2022-06-28_final
2022-06-28 12:05:02	ga_s2bm_ard_3-2-1_50JKS_2022-06-28_final
2022-06-28 12:05:20	ga_s2bm_ard_3-2-1_49JGL_2022-06-28_final

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years