Search ga_s2bm_ard_3 on 16th 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
2019-10-16 10:01:15	ga_s2bm_ard_3-2-1_55LFC_2019-10-16_final
2019-10-16 10:01:25	ga_s2bm_ard_3-2-1_55LCC_2019-10-16_final
2019-10-16 10:02:06	ga_s2bm_ard_3-2-1_55KFU_2019-10-16_final
2019-10-16 10:02:09	ga_s2bm_ard_3-2-1_55KCV_2019-10-16_final
2019-10-16 10:02:31	ga_s2bm_ard_3-2-1_55KET_2019-10-16_final
2019-10-16 10:02:35	ga_s2bm_ard_3-2-1_55KDT_2019-10-16_final
2019-10-16 10:02:46	ga_s2bm_ard_3-2-1_55KES_2019-10-16_final
2019-10-16 10:02:49	ga_s2bm_ard_3-2-1_55KDS_2019-10-16_final
2019-10-16 10:02:53	ga_s2bm_ard_3-2-1_55KCS_2019-10-16_final
2019-10-16 10:02:56	ga_s2bm_ard_3-2-1_55KBS_2019-10-16_final
2019-10-16 10:02:59	ga_s2bm_ard_3-2-1_55KER_2019-10-16_final
2019-10-16 10:03:04	ga_s2bm_ard_3-2-1_55KDR_2019-10-16_final
2019-10-16 10:03:07	ga_s2bm_ard_3-2-1_55KCR_2019-10-16_final
2019-10-16 10:03:10	ga_s2bm_ard_3-2-1_55KBR_2019-10-16_final
2019-10-16 10:03:22	ga_s2bm_ard_3-2-1_55KCQ_2019-10-16_final
2019-10-16 10:03:25	ga_s2bm_ard_3-2-1_55KBQ_2019-10-16_final
2019-10-16 10:03:36	ga_s2bm_ard_3-2-1_55KCP_2019-10-16_final
2019-10-16 10:03:39	ga_s2bm_ard_3-2-1_55KBP_2019-10-16_final
2019-10-16 10:03:44	ga_s2bm_ard_3-2-1_54KYU_2019-10-16_final
2019-10-16 10:03:54	ga_s2bm_ard_3-2-1_55JBN_2019-10-16_final
2019-10-16 10:03:57	ga_s2bm_ard_3-2-1_54JYT_2019-10-16_final
2019-10-16 10:04:02	ga_s2bm_ard_3-2-1_55JDM_2019-10-16_final
2019-10-16 10:04:05	ga_s2bm_ard_3-2-1_55JCM_2019-10-16_final
2019-10-16 10:04:09	ga_s2bm_ard_3-2-1_55JBM_2019-10-16_final
2019-10-16 10:04:12	ga_s2bm_ard_3-2-1_54JYS_2019-10-16_final
2019-10-16 10:04:19	ga_s2bm_ard_3-2-1_54JYS_2019-10-16_final
2019-10-16 10:05:36	ga_s2bm_ard_3-2-1_55JBF_2019-10-16_final
2019-10-16 10:05:39	ga_s2bm_ard_3-2-1_54JYL_2019-10-16_final
2019-10-16 10:05:46	ga_s2bm_ard_3-2-1_54JWL_2019-10-16_final
2019-10-16 10:05:57	ga_s2bm_ard_3-2-1_54HXK_2019-10-16_final
2019-10-16 10:06:05	ga_s2bm_ard_3-2-1_55HBD_2019-10-16_final
2019-10-16 10:06:07	ga_s2bm_ard_3-2-1_54HYJ_2019-10-16_final
2019-10-16 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2019-10-16_final
2019-10-16 10:06:15	ga_s2bm_ard_3-2-1_54HWJ_2019-10-16_final
2019-10-16 10:06:20	ga_s2bm_ard_3-2-1_55HBC_2019-10-16_final
2019-10-16 10:06:21	ga_s2bm_ard_3-2-1_54HYH_2019-10-16_final
2019-10-16 10:06:29	ga_s2bm_ard_3-2-1_54HWH_2019-10-16_final
2019-10-16 10:06:34	ga_s2bm_ard_3-2-1_55HBB_2019-10-16_final
2019-10-16 10:06:35	ga_s2bm_ard_3-2-1_54HVH_2019-10-16_final
2019-10-16 10:06:36	ga_s2bm_ard_3-2-1_54HYG_2019-10-16_final
2019-10-16 10:06:44	ga_s2bm_ard_3-2-1_54HWG_2019-10-16_final
2019-10-16 10:06:47	ga_s2bm_ard_3-2-1_54HVG_2019-10-16_final
2019-10-16 10:06:57	ga_s2bm_ard_3-2-1_55HBV_2019-10-16_final
2019-10-16 10:06:58	ga_s2bm_ard_3-2-1_54HWF_2019-10-16_final
2019-10-16 10:07:02	ga_s2bm_ard_3-2-1_54HVF_2019-10-16_final
2019-10-16 10:07:04	ga_s2bm_ard_3-2-1_54HYE_2019-10-16_final
2019-10-16 10:07:09	ga_s2bm_ard_3-2-1_54HXE_2019-10-16_final
2019-10-16 10:07:13	ga_s2bm_ard_3-2-1_54HWE_2019-10-16_final
2019-10-16 10:07:16	ga_s2bm_ard_3-2-1_54HVE_2019-10-16_final
2019-10-16 10:07:38	ga_s2bm_ard_3-2-1_54HXC_2019-10-16_final
2019-10-16 11:41:19	ga_s2bm_ard_3-2-1_51LUF_2019-10-16_final
2019-10-16 11:41:27	ga_s2bm_ard_3-2-1_51LWE_2019-10-16_final
2019-10-16 11:41:31	ga_s2bm_ard_3-2-1_51LVE_2019-10-16_final
2019-10-16 11:41:34	ga_s2bm_ard_3-2-1_51LUE_2019-10-16_final
2019-10-16 11:42:03	ga_s2bm_ard_3-2-1_51LUC_2019-10-16_final.stac-item
2019-10-16 11:42:47	ga_s2bm_ard_3-2-1_51KUV_2019-10-16_final
2019-10-16 11:43:05	ga_s2bm_ard_3-2-1_50KRD_2019-10-16_final
2019-10-16 11:43:12	ga_s2bm_ard_3-2-1_51KVT_2019-10-16_final
2019-10-16 11:43:16	ga_s2bm_ard_3-2-1_51KUT_2019-10-16_final
2019-10-16 11:43:34	ga_s2bm_ard_3-2-1_51KTS_2019-10-16_final
2019-10-16 11:43:37	ga_s2bm_ard_3-2-1_51KVR_2019-10-16_final
2019-10-16 11:43:37	ga_s2bm_ard_3-2-1_50KQB_2019-10-16_final
2019-10-16 11:43:45	ga_s2bm_ard_3-2-1_51KUR_2019-10-16_final
2019-10-16 11:43:48	ga_s2bm_ard_3-2-1_51KTR_2019-10-16_final
2019-10-16 11:43:52	ga_s2bm_ard_3-2-1_50KQA_2019-10-16_final
2019-10-16 11:43:59	ga_s2bm_ard_3-2-1_51KUQ_2019-10-16_final
2019-10-16 11:44:03	ga_s2bm_ard_3-2-1_51KTQ_2019-10-16_final
2019-10-16 11:44:14	ga_s2bm_ard_3-2-1_51KUP_2019-10-16_final
2019-10-16 11:44:17	ga_s2bm_ard_3-2-1_51KTP_2019-10-16_final
2019-10-16 11:44:21	ga_s2bm_ard_3-2-1_50KQU_2019-10-16_final
2019-10-16 11:44:23	ga_s2bm_ard_3-2-1_50KPU_2019-10-16_final
2019-10-16 11:44:27	ga_s2bm_ard_3-2-1_51JTN_2019-10-16_final
2019-10-16 11:44:28	ga_s2bm_ard_3-2-1_50KQU_2019-10-16_final
2019-10-16 11:44:28	ga_s2bm_ard_3-2-1_50JQT_2019-10-16_final
2019-10-16 11:44:29	ga_s2bm_ard_3-2-1_50KPU_2019-10-16_final
2019-10-16 11:44:33	ga_s2bm_ard_3-2-1_51JTN_2019-10-16_final
2019-10-16 11:44:36	ga_s2bm_ard_3-2-1_50JQT_2019-10-16_final
2019-10-16 11:44:42	ga_s2bm_ard_3-2-1_51JUM_2019-10-16_final
2019-10-16 11:44:46	ga_s2bm_ard_3-2-1_51JTM_2019-10-16_final
2019-10-16 11:44:50	ga_s2bm_ard_3-2-1_50JQS_2019-10-16_final
2019-10-16 11:44:54	ga_s2bm_ard_3-2-1_50JPS_2019-10-16_final
2019-10-16 11:45:40	ga_s2bm_ard_3-2-1_50JNP_2019-10-16_final
2019-10-16 11:46:09	ga_s2bm_ard_3-2-1_51JTF_2019-10-16_final
2019-10-16 11:46:16	ga_s2bm_ard_3-2-1_50JQL_2019-10-16_final
2019-10-16 11:46:24	ga_s2bm_ard_3-2-1_50JNL_2019-10-16_final
2019-10-16 11:46:27	ga_s2bm_ard_3-2-1_50JML_2019-10-16_final
2019-10-16 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2019-10-16_final
2019-10-16 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2019-10-16_final
2019-10-16 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2019-10-16_final
2019-10-16 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2019-10-16_final
2019-10-16 11:46:55	ga_s2bm_ard_3-2-1_50HQH_2019-10-16_final
2019-10-16 11:46:57	ga_s2bm_ard_3-2-1_50HMJ_2019-10-16_final
2019-10-16 11:47:08	ga_s2bm_ard_3-2-1_50HNH_2019-10-16_final
2019-10-16 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2019-10-16_final
2019-10-16 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2019-10-16_final
2019-10-16 11:47:16	ga_s2bm_ard_3-2-1_50HNG_2019-10-16_final.stac-item
2019-10-16 11:47:18	ga_s2bm_ard_3-2-1_50HMH_2019-10-16_final
2019-10-16 11:47:18	ga_s2bm_ard_3-2-1_50HMG_2019-10-16_final.stac-item
2019-10-16 11:47:21	ga_s2bm_ard_3-2-1_50HPG_2019-10-16_final.stac-item
2019-10-16 11:47:23	ga_s2bm_ard_3-2-1_50HNG_2019-10-16_final.stac-item

Return to ga_s2bm_ard_3 on 16th 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

16th