Search ga_s2bm_ard_3 across September 2019

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
2019-09-01 10:52:15	ga_s2bm_ard_3-2-1_53KLA_2019-09-01_final
2019-09-01 10:53:10	ga_s2bm_ard_3-2-1_53KMS_2019-09-01_final
2019-09-02 10:21:25	ga_s2bm_ard_3-2-1_54LYH_2019-09-02_final
2019-09-02 10:21:58	ga_s2bm_ard_3-2-1_54KXF_2019-09-02_final
2019-09-02 12:04:10	ga_s2bm_ard_3-2-1_50KMV_2019-09-02_final
2019-09-03 09:51:15	ga_s2bm_ard_3-2-1_55LHC_2019-09-03_final.stac-item
2019-09-03 09:52:23	ga_s2bm_ard_3-2-1_55KEU_2019-09-03_final
2019-09-03 11:31:51	ga_s2bm_ard_3-2-1_51LZC_2019-09-03_final
2019-09-03 11:31:56	ga_s2bm_ard_3-2-1_51LYC_2019-09-03_final
2019-09-04 11:01:44	ga_s2bm_ard_3-2-1_53LKC_2019-09-04_final
2019-09-04 11:01:45	ga_s2bm_ard_3-2-1_52LHH_2019-09-04_final
2019-09-04 11:01:49	ga_s2bm_ard_3-2-1_52LGH_2019-09-04_final
2019-09-04 11:02:06	ga_s2bm_ard_3-2-1_53KLA_2019-09-04_final
2019-09-05 10:32:03	ga_s2bm_ard_3-2-1_54KUF_2019-09-05_final
2019-09-06 10:01:55	ga_s2bm_ard_3-2-1_55KCA_2019-09-06_final
2019-09-06 10:02:18	ga_s2bm_ard_3-2-1_55KEU_2019-09-06_final
2019-09-06 10:02:21	ga_s2bm_ard_3-2-1_55KDU_2019-09-06_final
2019-09-07 11:11:42	ga_s2bm_ard_3-2-1_52LGH_2019-09-07_final
2019-09-07 11:13:17	ga_s2bm_ard_3-2-1_52KEB_2019-09-07_final
2019-09-08 10:41:36	ga_s2bm_ard_3-2-1_53LQC_2019-09-08_final
2019-09-08 10:42:03	ga_s2bm_ard_3-2-1_53KPA_2019-09-08_final
2019-09-08 10:42:10	ga_s2bm_ard_3-2-1_53KPA_2019-09-08_final
2019-09-08 10:43:13	ga_s2bm_ard_3-2-1_53KMS_2019-09-08_final
2019-09-08 10:43:39	ga_s2bm_ard_3-2-1_53KNQ_2019-09-08_final
2019-09-09 10:11:24	ga_s2bm_ard_3-2-1_55LBC_2019-09-09_final
2019-09-09 10:11:25	ga_s2bm_ard_3-2-1_54LZH_2019-09-09_final
2019-09-09 10:11:28	ga_s2bm_ard_3-2-1_54LYH_2019-09-09_final
2019-09-09 10:11:50	ga_s2bm_ard_3-2-1_55KCA_2019-09-09_final
2019-09-09 10:12:04	ga_s2bm_ard_3-2-1_54KXF_2019-09-09_final
2019-09-09 11:54:10	ga_s2bm_ard_3-2-1_50KNV_2019-09-09_final
2019-09-09 11:54:13	ga_s2bm_ard_3-2-1_50KMV_2019-09-09_final
2019-09-10 09:42:08	ga_s2bm_ard_3-2-1_56KMD_2019-09-10_final.stac-item
2019-09-10 11:21:55	ga_s2bm_ard_3-2-1_52LBH_2019-09-10_final
2019-09-10 11:21:56	ga_s2bm_ard_3-2-1_51LZC_2019-09-10_final
2019-09-10 11:22:00	ga_s2bm_ard_3-2-1_51LYC_2019-09-10_final
2019-09-11 10:52:13	ga_s2bm_ard_3-2-1_53KLA_2019-09-11_final
2019-09-11 10:53:08	ga_s2bm_ard_3-2-1_53KMS_2019-09-11_final
2019-09-12 10:21:23	ga_s2bm_ard_3-2-1_54LYH_2019-09-12_final
2019-09-12 10:21:56	ga_s2bm_ard_3-2-1_54KXF_2019-09-12_final
2019-09-12 12:04:07	ga_s2bm_ard_3-2-1_50KMV_2019-09-12_final
2019-09-13 09:51:13	ga_s2bm_ard_3-2-1_55LHC_2019-09-13_final.stac-item
2019-09-13 09:52:20	ga_s2bm_ard_3-2-1_55KEU_2019-09-13_final
2019-09-13 11:31:49	ga_s2bm_ard_3-2-1_51LZC_2019-09-13_final
2019-09-13 11:31:54	ga_s2bm_ard_3-2-1_51LYC_2019-09-13_final
2019-09-14 11:01:42	ga_s2bm_ard_3-2-1_53LKC_2019-09-14_final
2019-09-14 11:01:43	ga_s2bm_ard_3-2-1_52LHH_2019-09-14_final
2019-09-14 11:01:46	ga_s2bm_ard_3-2-1_52LGH_2019-09-14_final
2019-09-14 11:02:04	ga_s2bm_ard_3-2-1_53KLA_2019-09-14_final
2019-09-15 10:32:00	ga_s2bm_ard_3-2-1_54KUF_2019-09-15_final
2019-09-16 10:01:53	ga_s2bm_ard_3-2-1_55KCA_2019-09-16_final
2019-09-16 10:02:15	ga_s2bm_ard_3-2-1_55KEU_2019-09-16_final
2019-09-16 10:02:19	ga_s2bm_ard_3-2-1_55KDU_2019-09-16_final
2019-09-17 11:11:39	ga_s2bm_ard_3-2-1_52LGH_2019-09-17_final
2019-09-17 11:13:15	ga_s2bm_ard_3-2-1_52KEB_2019-09-17_final
2019-09-18 10:41:34	ga_s2bm_ard_3-2-1_53LQC_2019-09-18_final
2019-09-18 10:42:01	ga_s2bm_ard_3-2-1_53KPA_2019-09-18_final
2019-09-18 10:42:07	ga_s2bm_ard_3-2-1_53KPA_2019-09-18_final
2019-09-18 10:43:10	ga_s2bm_ard_3-2-1_53KMS_2019-09-18_final
2019-09-18 10:43:36	ga_s2bm_ard_3-2-1_53KNQ_2019-09-18_final
2019-09-19 10:11:22	ga_s2bm_ard_3-2-1_55LBC_2019-09-19_final
2019-09-19 10:11:23	ga_s2bm_ard_3-2-1_54LZH_2019-09-19_final
2019-09-19 10:11:26	ga_s2bm_ard_3-2-1_54LYH_2019-09-19_final
2019-09-19 10:11:47	ga_s2bm_ard_3-2-1_55KCA_2019-09-19_final
2019-09-19 10:12:01	ga_s2bm_ard_3-2-1_54KXF_2019-09-19_final
2019-09-19 11:54:07	ga_s2bm_ard_3-2-1_50KNV_2019-09-19_final
2019-09-19 11:54:10	ga_s2bm_ard_3-2-1_50KMV_2019-09-19_final
2019-09-20 11:21:52	ga_s2bm_ard_3-2-1_52LBH_2019-09-20_final
2019-09-20 11:21:54	ga_s2bm_ard_3-2-1_51LZC_2019-09-20_final
2019-09-20 11:21:58	ga_s2bm_ard_3-2-1_51LYC_2019-09-20_final
2019-09-21 10:52:11	ga_s2bm_ard_3-2-1_53KLA_2019-09-21_final
2019-09-21 10:53:06	ga_s2bm_ard_3-2-1_53KMS_2019-09-21_final
2019-09-22 10:21:22	ga_s2bm_ard_3-2-1_54LYH_2019-09-22_final
2019-09-22 10:21:54	ga_s2bm_ard_3-2-1_54KXF_2019-09-22_final
2019-09-22 12:04:06	ga_s2bm_ard_3-2-1_50KMV_2019-09-22_final
2019-09-23 09:51:12	ga_s2bm_ard_3-2-1_55LHC_2019-09-23_final.stac-item
2019-09-23 09:52:19	ga_s2bm_ard_3-2-1_55KEU_2019-09-23_final
2019-09-23 11:31:48	ga_s2bm_ard_3-2-1_51LZC_2019-09-23_final
2019-09-23 11:31:53	ga_s2bm_ard_3-2-1_51LYC_2019-09-23_final
2019-09-24 11:01:41	ga_s2bm_ard_3-2-1_53LKC_2019-09-24_final
2019-09-24 11:01:42	ga_s2bm_ard_3-2-1_52LHH_2019-09-24_final
2019-09-24 11:01:46	ga_s2bm_ard_3-2-1_52LGH_2019-09-24_final
2019-09-24 11:02:03	ga_s2bm_ard_3-2-1_53KLA_2019-09-24_final
2019-09-25 10:32:00	ga_s2bm_ard_3-2-1_54KUF_2019-09-25_final
2019-09-26 10:01:53	ga_s2bm_ard_3-2-1_55KCA_2019-09-26_final
2019-09-26 10:02:15	ga_s2bm_ard_3-2-1_55KEU_2019-09-26_final
2019-09-26 10:02:19	ga_s2bm_ard_3-2-1_55KDU_2019-09-26_final
2019-09-27 11:11:40	ga_s2bm_ard_3-2-1_52LGH_2019-09-27_final
2019-09-28 10:41:35	ga_s2bm_ard_3-2-1_53LQC_2019-09-28_final
2019-09-28 10:42:02	ga_s2bm_ard_3-2-1_53KPA_2019-09-28_final
2019-09-28 10:42:08	ga_s2bm_ard_3-2-1_53KPA_2019-09-28_final
2019-09-28 10:43:12	ga_s2bm_ard_3-2-1_53KMS_2019-09-28_final
2019-09-28 10:43:37	ga_s2bm_ard_3-2-1_53KNQ_2019-09-28_final
2019-09-29 10:11:23	ga_s2bm_ard_3-2-1_55LBC_2019-09-29_final
2019-09-29 10:11:24	ga_s2bm_ard_3-2-1_54LZH_2019-09-29_final
2019-09-29 10:11:27	ga_s2bm_ard_3-2-1_54LYH_2019-09-29_final
2019-09-29 10:11:49	ga_s2bm_ard_3-2-1_55KCA_2019-09-29_final
2019-09-29 10:12:02	ga_s2bm_ard_3-2-1_54KXF_2019-09-29_final
2019-09-29 11:54:08	ga_s2bm_ard_3-2-1_50KNV_2019-09-29_final
2019-09-30 11:21:54	ga_s2bm_ard_3-2-1_52LBH_2019-09-30_final
2019-09-30 11:21:55	ga_s2bm_ard_3-2-1_51LZC_2019-09-30_final

Return to ga_s2bm_ard_3 across September 2019 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

2019

September

All days