Search ga_s2bm_ard_3 across October 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
2019-10-01 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-10-01_final
2019-10-01 10:52:45	ga_s2bm_ard_3-2-1_52KHD_2019-10-01_final
2019-10-01 10:53:00	ga_s2bm_ard_3-2-1_52KHC_2019-10-01_final
2019-10-02 10:25:36	ga_s2bm_ard_3-2-1_54JVL_2019-10-02_final
2019-10-03 09:52:14	ga_s2bm_ard_3-2-1_55KGU_2019-10-03_final
2019-10-04 11:02:40	ga_s2bm_ard_3-2-1_53KKU_2019-10-04_final
2019-10-04 11:02:41	ga_s2bm_ard_3-2-1_52KHD_2019-10-04_final
2019-10-04 11:02:45	ga_s2bm_ard_3-2-1_52KGD_2019-10-04_final
2019-10-04 11:02:55	ga_s2bm_ard_3-2-1_52KHC_2019-10-04_final
2019-10-05 10:30:27	ga_s2bm_ard_3-2-1_54LWM_2019-10-05_final
2019-10-05 10:30:31	ga_s2bm_ard_3-2-1_54LVM_2019-10-05_final.stac-item
2019-10-05 10:32:34	ga_s2bm_ard_3-2-1_53KRU_2019-10-05_final
2019-10-05 10:35:56	ga_s2bm_ard_3-2-1_53JMF_2019-10-05_final
2019-10-06 10:05:46	ga_s2bm_ard_3-2-1_54JWL_2019-10-06_final
2019-10-06 11:40:58	ga_s2bm_ard_3-2-1_51LWG_2019-10-06_final.stac-item
2019-10-06 11:41:01	ga_s2bm_ard_3-2-1_51LVG_2019-10-06_final
2019-10-06 11:43:05	ga_s2bm_ard_3-2-1_50KRD_2019-10-06_final
2019-10-06 11:43:19	ga_s2bm_ard_3-2-1_50KRC_2019-10-06_final
2019-10-06 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2019-10-06_final.stac-item
2019-10-08 10:42:23	ga_s2bm_ard_3-2-1_53KRU_2019-10-08_final
2019-10-08 10:42:33	ga_s2bm_ard_3-2-1_53KQU_2019-10-08_final
2019-10-09 10:12:23	ga_s2bm_ard_3-2-1_54KZD_2019-10-09_final
2019-10-09 10:15:42	ga_s2bm_ard_3-2-1_54JWL_2019-10-09_final
2019-10-09 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2019-10-09_final
2019-10-09 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-09_final
2019-10-09 11:53:12	ga_s2bm_ard_3-2-1_50KRC_2019-10-09_final
2019-10-09 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2019-10-09_final.stac-item
2019-10-10 09:46:32	ga_s2bm_ard_3-2-1_55HEB_2019-10-10_final
2019-10-10 11:23:08	ga_s2bm_ard_3-2-1_51KZT_2019-10-10_final
2019-10-11 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-10-11_final
2019-10-11 10:52:46	ga_s2bm_ard_3-2-1_52KHD_2019-10-11_final
2019-10-11 10:53:00	ga_s2bm_ard_3-2-1_52KHC_2019-10-11_final
2019-10-12 10:20:32	ga_s2bm_ard_3-2-1_54LWM_2019-10-12_final
2019-10-12 10:25:37	ga_s2bm_ard_3-2-1_54JVL_2019-10-12_final
2019-10-13 09:52:15	ga_s2bm_ard_3-2-1_55KGU_2019-10-13_final
2019-10-14 11:02:41	ga_s2bm_ard_3-2-1_53KKU_2019-10-14_final
2019-10-14 11:02:41	ga_s2bm_ard_3-2-1_52KHD_2019-10-14_final
2019-10-14 11:02:45	ga_s2bm_ard_3-2-1_52KGD_2019-10-14_final
2019-10-14 11:02:56	ga_s2bm_ard_3-2-1_52KHC_2019-10-14_final
2019-10-15 10:30:27	ga_s2bm_ard_3-2-1_54LWM_2019-10-15_final
2019-10-15 10:30:31	ga_s2bm_ard_3-2-1_54LVM_2019-10-15_final.stac-item
2019-10-15 10:32:34	ga_s2bm_ard_3-2-1_53KRU_2019-10-15_final
2019-10-15 10:35:57	ga_s2bm_ard_3-2-1_53JMF_2019-10-15_final
2019-10-16 10:05:46	ga_s2bm_ard_3-2-1_54JWL_2019-10-16_final
2019-10-16 11:40:58	ga_s2bm_ard_3-2-1_51LWG_2019-10-16_final.stac-item
2019-10-16 11:41:02	ga_s2bm_ard_3-2-1_51LVG_2019-10-16_final
2019-10-16 11:43:05	ga_s2bm_ard_3-2-1_50KRD_2019-10-16_final
2019-10-16 11:43:20	ga_s2bm_ard_3-2-1_50KRC_2019-10-16_final
2019-10-16 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2019-10-16_final.stac-item
2019-10-17 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-10-17_final
2019-10-18 10:42:24	ga_s2bm_ard_3-2-1_53KRU_2019-10-18_final
2019-10-18 10:42:33	ga_s2bm_ard_3-2-1_53KQU_2019-10-18_final
2019-10-18 10:45:52	ga_s2bm_ard_3-2-1_53JMF_2019-10-18_final
2019-10-19 10:12:23	ga_s2bm_ard_3-2-1_54KZD_2019-10-19_final
2019-10-19 10:15:42	ga_s2bm_ard_3-2-1_54JWL_2019-10-19_final
2019-10-19 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2019-10-19_final
2019-10-19 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-19_final
2019-10-19 11:53:12	ga_s2bm_ard_3-2-1_50KRC_2019-10-19_final
2019-10-19 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2019-10-19_final.stac-item
2019-10-20 09:46:32	ga_s2bm_ard_3-2-1_55HEB_2019-10-20_final
2019-10-20 11:23:08	ga_s2bm_ard_3-2-1_51KZT_2019-10-20_final
2019-10-21 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-10-21_final
2019-10-21 10:52:46	ga_s2bm_ard_3-2-1_52KHD_2019-10-21_final
2019-10-21 10:53:01	ga_s2bm_ard_3-2-1_52KHC_2019-10-21_final
2019-10-22 10:20:32	ga_s2bm_ard_3-2-1_54LWM_2019-10-22_final
2019-10-22 10:25:37	ga_s2bm_ard_3-2-1_54JVL_2019-10-22_final
2019-10-23 09:52:14	ga_s2bm_ard_3-2-1_55KGU_2019-10-23_final
2019-10-24 11:02:41	ga_s2bm_ard_3-2-1_53KKU_2019-10-24_final
2019-10-24 11:02:41	ga_s2bm_ard_3-2-1_52KHD_2019-10-24_final
2019-10-24 11:02:45	ga_s2bm_ard_3-2-1_52KGD_2019-10-24_final
2019-10-24 11:02:56	ga_s2bm_ard_3-2-1_52KHC_2019-10-24_final
2019-10-25 10:30:27	ga_s2bm_ard_3-2-1_54LWM_2019-10-25_final
2019-10-25 10:30:31	ga_s2bm_ard_3-2-1_54LVM_2019-10-25_final.stac-item
2019-10-25 10:32:34	ga_s2bm_ard_3-2-1_53KRU_2019-10-25_final
2019-10-25 10:35:57	ga_s2bm_ard_3-2-1_53JMF_2019-10-25_final
2019-10-26 10:05:46	ga_s2bm_ard_3-2-1_54JWL_2019-10-26_final
2019-10-26 11:40:57	ga_s2bm_ard_3-2-1_51LWG_2019-10-26_final.stac-item
2019-10-26 11:40:59	ga_s2bm_ard_3-2-1_51LVG_2019-10-26_final
2019-10-26 11:41:04	ga_s2bm_ard_3-2-1_51LWG_2019-10-26_final.stac-item
2019-10-26 11:41:06	ga_s2bm_ard_3-2-1_51LVG_2019-10-26_final
2019-10-26 11:43:05	ga_s2bm_ard_3-2-1_50KRD_2019-10-26_final
2019-10-26 11:43:19	ga_s2bm_ard_3-2-1_50KRC_2019-10-26_final
2019-10-26 11:47:25	ga_s2bm_ard_3-2-1_50HMG_2019-10-26_final.stac-item
2019-10-27 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-10-27_final
2019-10-27 09:38:41	ga_s2bm_ard_3-2-1_55GCP_2019-10-27_final
2019-10-28 10:42:23	ga_s2bm_ard_3-2-1_53KRU_2019-10-28_final
2019-10-28 10:42:33	ga_s2bm_ard_3-2-1_53KQU_2019-10-28_final
2019-10-28 10:45:52	ga_s2bm_ard_3-2-1_53JMF_2019-10-28_final
2019-10-29 10:12:22	ga_s2bm_ard_3-2-1_54KZD_2019-10-29_final
2019-10-29 10:15:41	ga_s2bm_ard_3-2-1_54JWL_2019-10-29_final
2019-10-29 10:15:45	ga_s2bm_ard_3-2-1_54JVL_2019-10-29_final
2019-10-29 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-29_final
2019-10-29 11:53:11	ga_s2bm_ard_3-2-1_50KRC_2019-10-29_final
2019-10-29 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2019-10-29_final.stac-item
2019-10-30 09:46:32	ga_s2bm_ard_3-2-1_55HEB_2019-10-30_final
2019-10-30 11:23:07	ga_s2bm_ard_3-2-1_51KZT_2019-10-30_final
2019-10-31 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-10-31_final
2019-10-31 10:52:45	ga_s2bm_ard_3-2-1_52KHD_2019-10-31_final
2019-10-31 10:52:52	ga_s2bm_ard_3-2-1_52KHD_2019-10-31_final
2019-10-31 10:52:52	ga_s2bm_ard_3-2-1_52KHC_2019-10-31_final

Return to ga_s2bm_ard_3 across October 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

October

All days