Search ga_s2bm_ard_3 on 29th 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
2019-10-29 10:10:41	ga_s2bm_ard_3-2-1_54LZL_2019-10-29_final
2019-10-29 10:11:06	ga_s2bm_ard_3-2-1_55LCD_2019-10-29_final
2019-10-29 10:11:09	ga_s2bm_ard_3-2-1_55LBD_2019-10-29_final
2019-10-29 10:11:10	ga_s2bm_ard_3-2-1_54LZJ_2019-10-29_final
2019-10-29 10:11:13	ga_s2bm_ard_3-2-1_54LYJ_2019-10-29_final
2019-10-29 10:11:25	ga_s2bm_ard_3-2-1_54LZH_2019-10-29_final
2019-10-29 10:11:34	ga_s2bm_ard_3-2-1_55KCB_2019-10-29_final
2019-10-29 10:11:38	ga_s2bm_ard_3-2-1_55KBB_2019-10-29_final
2019-10-29 10:11:39	ga_s2bm_ard_3-2-1_54KZG_2019-10-29_final
2019-10-29 10:11:42	ga_s2bm_ard_3-2-1_54KYG_2019-10-29_final
2019-10-29 10:11:49	ga_s2bm_ard_3-2-1_55KCA_2019-10-29_final
2019-10-29 10:12:03	ga_s2bm_ard_3-2-1_54KXF_2019-10-29_final
2019-10-29 10:12:17	ga_s2bm_ard_3-2-1_55KCU_2019-10-29_final
2019-10-29 10:12:21	ga_s2bm_ard_3-2-1_55KBU_2019-10-29_final
2019-10-29 10:12:22	ga_s2bm_ard_3-2-1_54KZD_2019-10-29_final
2019-10-29 10:12:26	ga_s2bm_ard_3-2-1_54KYD_2019-10-29_final
2019-10-29 10:12:29	ga_s2bm_ard_3-2-1_54KXD_2019-10-29_final
2019-10-29 10:12:36	ga_s2bm_ard_3-2-1_55KBT_2019-10-29_final
2019-10-29 10:12:37	ga_s2bm_ard_3-2-1_54KZC_2019-10-29_final
2019-10-29 10:12:40	ga_s2bm_ard_3-2-1_54KYC_2019-10-29_final
2019-10-29 10:12:44	ga_s2bm_ard_3-2-1_54KXC_2019-10-29_final
2019-10-29 10:12:59	ga_s2bm_ard_3-2-1_54KZA_2019-10-29_final
2019-10-29 10:13:06	ga_s2bm_ard_3-2-1_54KZA_2019-10-29_final
2019-10-29 10:13:20	ga_s2bm_ard_3-2-1_54KZV_2019-10-29_final
2019-10-29 10:13:30	ga_s2bm_ard_3-2-1_54KWV_2019-10-29_final
2019-10-29 10:13:34	ga_s2bm_ard_3-2-1_54KZU_2019-10-29_final
2019-10-29 10:13:45	ga_s2bm_ard_3-2-1_54KWU_2019-10-29_final
2019-10-29 10:13:46	ga_s2bm_ard_3-2-1_54JZT_2019-10-29_final
2019-10-29 10:13:56	ga_s2bm_ard_3-2-1_54JXT_2019-10-29_final
2019-10-29 10:14:00	ga_s2bm_ard_3-2-1_54JWT_2019-10-29_final
2019-10-29 10:14:06	ga_s2bm_ard_3-2-1_54JVT_2019-10-29_final
2019-10-29 10:14:32	ga_s2bm_ard_3-2-1_54JVR_2019-10-29_final
2019-10-29 10:14:36	ga_s2bm_ard_3-2-1_54JYQ_2019-10-29_final
2019-10-29 10:14:43	ga_s2bm_ard_3-2-1_54JWQ_2019-10-29_final
2019-10-29 10:14:47	ga_s2bm_ard_3-2-1_54JVQ_2019-10-29_final
2019-10-29 10:14:58	ga_s2bm_ard_3-2-1_54JWP_2019-10-29_final
2019-10-29 10:14:58	ga_s2bm_ard_3-2-1_54JYN_2019-10-29_final
2019-10-29 10:15:01	ga_s2bm_ard_3-2-1_54JVP_2019-10-29_final
2019-10-29 10:15:08	ga_s2bm_ard_3-2-1_54JXN_2019-10-29_final
2019-10-29 10:15:09	ga_s2bm_ard_3-2-1_54JUP_2019-10-29_final
2019-10-29 10:15:12	ga_s2bm_ard_3-2-1_54JWN_2019-10-29_final
2019-10-29 10:15:27	ga_s2bm_ard_3-2-1_54JWM_2019-10-29_final
2019-10-29 10:15:30	ga_s2bm_ard_3-2-1_54JVM_2019-10-29_final
2019-10-29 10:15:38	ga_s2bm_ard_3-2-1_54JXL_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 10:15:48	ga_s2bm_ard_3-2-1_54JUL_2019-10-29_final
2019-10-29 10:15:56	ga_s2bm_ard_3-2-1_54HWK_2019-10-29_final
2019-10-29 10:15:59	ga_s2bm_ard_3-2-1_54HVK_2019-10-29_final
2019-10-29 10:16:10	ga_s2bm_ard_3-2-1_54HWJ_2019-10-29_final
2019-10-29 10:16:14	ga_s2bm_ard_3-2-1_54HVJ_2019-10-29_final
2019-10-29 10:16:17	ga_s2bm_ard_3-2-1_54HUJ_2019-10-29_final
2019-10-29 10:16:22	ga_s2bm_ard_3-2-1_54HTJ_2019-10-29_final
2019-10-29 10:16:39	ga_s2bm_ard_3-2-1_54HWG_2019-10-29_final
2019-10-29 10:16:43	ga_s2bm_ard_3-2-1_54HVG_2019-10-29_final
2019-10-29 10:16:46	ga_s2bm_ard_3-2-1_54HUG_2019-10-29_final
2019-10-29 10:17:01	ga_s2bm_ard_3-2-1_54HUF_2019-10-29_final
2019-10-29 10:17:04	ga_s2bm_ard_3-2-1_54HTF_2019-10-29_final
2019-10-29 10:17:04	ga_s2bm_ard_3-2-1_54HWE_2019-10-29_final
2019-10-29 10:17:05	ga_s2bm_ard_3-2-1_53HQA_2019-10-29_final
2019-10-29 10:17:12	ga_s2bm_ard_3-2-1_54HVE_2019-10-29_final
2019-10-29 10:17:20	ga_s2bm_ard_3-2-1_53HQV_2019-10-29_final.stac-item
2019-10-29 10:17:26	ga_s2bm_ard_3-2-1_54HVD_2019-10-29_final
2019-10-29 10:17:30	ga_s2bm_ard_3-2-1_54HUD_2019-10-29_final.stac-item
2019-10-29 11:51:14	ga_s2bm_ard_3-2-1_51LUF_2019-10-29_final
2019-10-29 11:51:39	ga_s2bm_ard_3-2-1_51LUD_2019-10-29_final.stac-item
2019-10-29 11:52:20	ga_s2bm_ard_3-2-1_50KQG_2019-10-29_final.stac-item
2019-10-29 11:52:38	ga_s2bm_ard_3-2-1_50KPF_2019-10-29_final.stac-item
2019-10-29 11:52:55	ga_s2bm_ard_3-2-1_51KTU_2019-10-29_final
2019-10-29 11:53:00	ga_s2bm_ard_3-2-1_50KRD_2019-10-29_final
2019-10-29 11:53:04	ga_s2bm_ard_3-2-1_50KQD_2019-10-29_final.stac-item
2019-10-29 11:53:07	ga_s2bm_ard_3-2-1_50KPD_2019-10-29_final.stac-item
2019-10-29 11:53:11	ga_s2bm_ard_3-2-1_50KRC_2019-10-29_final
2019-10-29 11:53:18	ga_s2bm_ard_3-2-1_50KQC_2019-10-29_final
2019-10-29 11:53:36	ga_s2bm_ard_3-2-1_50KPB_2019-10-29_final
2019-10-29 11:54:09	ga_s2bm_ard_3-2-1_50KNV_2019-10-29_final
2019-10-29 11:54:12	ga_s2bm_ard_3-2-1_50KMV_2019-10-29_final
2019-10-29 11:54:23	ga_s2bm_ard_3-2-1_50KNU_2019-10-29_final
2019-10-29 11:54:27	ga_s2bm_ard_3-2-1_50KMU_2019-10-29_final
2019-10-29 11:54:34	ga_s2bm_ard_3-2-1_50JPT_2019-10-29_final
2019-10-29 11:54:38	ga_s2bm_ard_3-2-1_50JNT_2019-10-29_final
2019-10-29 11:54:41	ga_s2bm_ard_3-2-1_50JMT_2019-10-29_final
2019-10-29 11:54:45	ga_s2bm_ard_3-2-1_50JLT_2019-10-29_final
2019-10-29 11:54:49	ga_s2bm_ard_3-2-1_50JPS_2019-10-29_final
2019-10-29 11:54:59	ga_s2bm_ard_3-2-1_50JLS_2019-10-29_final
2019-10-29 11:55:03	ga_s2bm_ard_3-2-1_50JPR_2019-10-29_final
2019-10-29 11:55:07	ga_s2bm_ard_3-2-1_50JNR_2019-10-29_final
2019-10-29 11:55:10	ga_s2bm_ard_3-2-1_50JMR_2019-10-29_final
2019-10-29 11:55:13	ga_s2bm_ard_3-2-1_50JLR_2019-10-29_final
2019-10-29 11:55:27	ga_s2bm_ard_3-2-1_50JPP_2019-10-29_final
2019-10-29 11:55:43	ga_s2bm_ard_3-2-1_50JLP_2019-10-29_final
2019-10-29 11:55:50	ga_s2bm_ard_3-2-1_50JNN_2019-10-29_final
2019-10-29 11:55:54	ga_s2bm_ard_3-2-1_50JMN_2019-10-29_final
2019-10-29 11:56:00	ga_s2bm_ard_3-2-1_50JKN_2019-10-29_final
2019-10-29 11:56:26	ga_s2bm_ard_3-2-1_50JLL_2019-10-29_final
2019-10-29 11:56:31	ga_s2bm_ard_3-2-1_50HNK_2019-10-29_final
2019-10-29 11:56:37	ga_s2bm_ard_3-2-1_50HMK_2019-10-29_final
2019-10-29 11:56:52	ga_s2bm_ard_3-2-1_50HMJ_2019-10-29_final
2019-10-29 11:56:55	ga_s2bm_ard_3-2-1_50HLJ_2019-10-29_final
2019-10-29 11:57:21	ga_s2bm_ard_3-2-1_50HMG_2019-10-29_final.stac-item

Return to ga_s2bm_ard_3 on 29th 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

29th