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
2019-10-28 10:45:05	ga_s2bm_ard_3-2-1_53JNJ_2019-10-28_final
2019-10-28 10:45:09	ga_s2bm_ard_3-2-1_53JMJ_2019-10-28_final
2019-10-28 10:45:12	ga_s2bm_ard_3-2-1_53JLJ_2019-10-28_final
2019-10-28 10:45:15	ga_s2bm_ard_3-2-1_53JKJ_2019-10-28_final
2019-10-28 10:45:20	ga_s2bm_ard_3-2-1_53JNH_2019-10-28_final
2019-10-28 10:45:23	ga_s2bm_ard_3-2-1_53JMH_2019-10-28_final
2019-10-28 10:45:33	ga_s2bm_ard_3-2-1_53JNG_2019-10-28_final
2019-10-28 10:45:38	ga_s2bm_ard_3-2-1_53JMG_2019-10-28_final
2019-10-28 10:45:41	ga_s2bm_ard_3-2-1_53JLG_2019-10-28_final
2019-10-28 10:45:44	ga_s2bm_ard_3-2-1_53JKG_2019-10-28_final
2019-10-28 10:45:48	ga_s2bm_ard_3-2-1_52JGM_2019-10-28_final
2019-10-28 10:45:56	ga_s2bm_ard_3-2-1_53JLF_2019-10-28_final
2019-10-28 10:46:07	ga_s2bm_ard_3-2-1_53HME_2019-10-28_final
2019-10-28 10:46:10	ga_s2bm_ard_3-2-1_53HLE_2019-10-28_final
2019-10-28 10:46:13	ga_s2bm_ard_3-2-1_53HKE_2019-10-28_final.stac-item
2019-10-28 10:46:16	ga_s2bm_ard_3-2-1_52HGK_2019-10-28_final.stac-item
2019-10-29 10:09:59	ga_s2bm_ard_3-2-1_54LZP_2019-10-29_final
2019-10-29 10:10:12	ga_s2bm_ard_3-2-1_54LZN_2019-10-29_final
2019-10-29 10:10:26	ga_s2bm_ard_3-2-1_54LZM_2019-10-29_final
2019-10-29 10:10:51	ga_s2bm_ard_3-2-1_55LCE_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 10:11:52	ga_s2bm_ard_3-2-1_55KBA_2019-10-29_final
2019-10-29 10:11:54	ga_s2bm_ard_3-2-1_54KZF_2019-10-29_final
2019-10-29 10:11:57	ga_s2bm_ard_3-2-1_54KYF_2019-10-29_final
2019-10-29 10:12:07	ga_s2bm_ard_3-2-1_55KBV_2019-10-29_final
2019-10-29 10:12:08	ga_s2bm_ard_3-2-1_54KZE_2019-10-29_final
2019-10-29 10:12:11	ga_s2bm_ard_3-2-1_54KYE_2019-10-29_final
2019-10-29 10:12:29	ga_s2bm_ard_3-2-1_55KCT_2019-10-29_final
2019-10-29 10:12:44	ga_s2bm_ard_3-2-1_54KXC_2019-10-29_final
2019-10-29 10:12:50	ga_s2bm_ard_3-2-1_55KBS_2019-10-29_final
2019-10-29 10:12:54	ga_s2bm_ard_3-2-1_54KYB_2019-10-29_final
2019-10-29 10:12:56	ga_s2bm_ard_3-2-1_54KXB_2019-10-29_final
2019-10-29 10:12:59	ga_s2bm_ard_3-2-1_55KBS_2019-10-29_final
2019-10-29 10:12:59	ga_s2bm_ard_3-2-1_55KBR_2019-10-29_final
2019-10-29 10:13:01	ga_s2bm_ard_3-2-1_54KWB_2019-10-29_final
2019-10-29 10:13:01	ga_s2bm_ard_3-2-1_54KYB_2019-10-29_final
2019-10-29 10:13:01	ga_s2bm_ard_3-2-1_54KYA_2019-10-29_final
2019-10-29 10:13:03	ga_s2bm_ard_3-2-1_54KXB_2019-10-29_final
2019-10-29 10:13:05	ga_s2bm_ard_3-2-1_54KWB_2019-10-29_final
2019-10-29 10:13:06	ga_s2bm_ard_3-2-1_55KBR_2019-10-29_final
2019-10-29 10:13:09	ga_s2bm_ard_3-2-1_54KYA_2019-10-29_final
2019-10-29 10:13:13	ga_s2bm_ard_3-2-1_54KXA_2019-10-29_final
2019-10-29 10:13:20	ga_s2bm_ard_3-2-1_55KBQ_2019-10-29_final
2019-10-29 10:13:24	ga_s2bm_ard_3-2-1_54KYV_2019-10-29_final
2019-10-29 10:13:27	ga_s2bm_ard_3-2-1_54KXV_2019-10-29_final
2019-10-29 10:13:30	ga_s2bm_ard_3-2-1_54KWV_2019-10-29_final
2019-10-29 10:13:33	ga_s2bm_ard_3-2-1_55KBP_2019-10-29_final
2019-10-29 10:13:38	ga_s2bm_ard_3-2-1_54KYU_2019-10-29_final
2019-10-29 10:13:42	ga_s2bm_ard_3-2-1_54KXU_2019-10-29_final
2019-10-29 10:13:45	ga_s2bm_ard_3-2-1_55JBN_2019-10-29_final
2019-10-29 10:13:45	ga_s2bm_ard_3-2-1_54KWU_2019-10-29_final
2019-10-29 10:13:52	ga_s2bm_ard_3-2-1_54JYT_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 10:14:07	ga_s2bm_ard_3-2-1_54JYS_2019-10-29_final
2019-10-29 10:14:11	ga_s2bm_ard_3-2-1_54JXS_2019-10-29_final
2019-10-29 10:14:14	ga_s2bm_ard_3-2-1_54JWS_2019-10-29_final
2019-10-29 10:14:18	ga_s2bm_ard_3-2-1_54JVS_2019-10-29_final
2019-10-29 10:14:22	ga_s2bm_ard_3-2-1_54JYR_2019-10-29_final
2019-10-29 10:14:25	ga_s2bm_ard_3-2-1_54JXR_2019-10-29_final
2019-10-29 10:14:29	ga_s2bm_ard_3-2-1_54JWR_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 10:14:40	ga_s2bm_ard_3-2-1_54JXQ_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 10:14:48	ga_s2bm_ard_3-2-1_54JYP_2019-10-29_final
2019-10-29 10:14:54	ga_s2bm_ard_3-2-1_54JXP_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 10:15:09	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 10:15:16	ga_s2bm_ard_3-2-1_54JVN_2019-10-29_final
2019-10-29 10:15:23	ga_s2bm_ard_3-2-1_54JXM_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 10:15:33	ga_s2bm_ard_3-2-1_54JUM_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 10:15:51	ga_s2bm_ard_3-2-1_54HXK_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 10:16:03	ga_s2bm_ard_3-2-1_54HUK_2019-10-29_final
2019-10-29 10:16:32	ga_s2bm_ard_3-2-1_54HUH_2019-10-29_final
2019-10-29 10:16:46	ga_s2bm_ard_3-2-1_54HUG_2019-10-29_final
2019-10-29 10:16:49	ga_s2bm_ard_3-2-1_54HTG_2019-10-29_final
2019-10-29 10:16:53	ga_s2bm_ard_3-2-1_53HQB_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 10:17:16	ga_s2bm_ard_3-2-1_54HUE_2019-10-29_final.stac-item
2019-10-29 10:17:19	ga_s2bm_ard_3-2-1_54HTE_2019-10-29_final.stac-item
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

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