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

38 results

Time (local)	Label
2022-11-12 10:10:25	ga_s2bm_ard_3-2-1_54LZM_2022-11-12_final.stac-item
2022-11-12 10:10:40	ga_s2bm_ard_3-2-1_54LZL_2022-11-12_final.stac-item
2022-11-12 10:10:54	ga_s2bm_ard_3-2-1_54LZK_2022-11-12_final.stac-item
2022-11-12 10:11:18	ga_s2bm_ard_3-2-1_55LCC_2022-11-12_final.stac-item
2022-11-12 10:11:41	ga_s2bm_ard_3-2-1_54KYG_2022-11-12_final.stac-item
2022-11-12 10:12:20	ga_s2bm_ard_3-2-1_55KBU_2022-11-12_final.stac-item
2022-11-12 10:12:39	ga_s2bm_ard_3-2-1_54KYC_2022-11-12_final.stac-item
2022-11-12 10:12:49	ga_s2bm_ard_3-2-1_55KBS_2022-11-12_final.stac-item
2022-11-12 10:13:08	ga_s2bm_ard_3-2-1_54KYA_2022-11-12_final.stac-item
2022-11-12 10:13:11	ga_s2bm_ard_3-2-1_54KXA_2022-11-12_final.stac-item
2022-11-12 10:13:15	ga_s2bm_ard_3-2-1_54KWA_2022-11-12_final.stac-item
2022-11-12 10:13:18	ga_s2bm_ard_3-2-1_55KBQ_2022-11-12_final.stac-item
2022-11-12 10:13:45	ga_s2bm_ard_3-2-1_54JZT_2022-11-12_final.stac-item
2022-11-12 10:13:51	ga_s2bm_ard_3-2-1_54JYT_2022-11-12_final.stac-item
2022-11-12 10:13:55	ga_s2bm_ard_3-2-1_54JXT_2022-11-12_final.stac-item
2022-11-12 10:13:58	ga_s2bm_ard_3-2-1_54JWT_2022-11-12_final.stac-item
2022-11-12 10:14:17	ga_s2bm_ard_3-2-1_54JVS_2022-11-12_final.stac-item
2022-11-12 10:14:38	ga_s2bm_ard_3-2-1_54JXQ_2022-11-12_final.stac-item
2022-11-12 10:14:56	ga_s2bm_ard_3-2-1_54JWP_2022-11-12_final.stac-item
2022-11-12 10:15:01	ga_s2bm_ard_3-2-1_54JXN_2022-11-12_final.stac-item
2022-11-12 10:15:02	ga_s2bm_ard_3-2-1_54JXP_2022-11-12_final.stac-item
2022-11-12 10:15:07	ga_s2bm_ard_3-2-1_54JUP_2022-11-12_final.stac-item
2022-11-12 10:15:14	ga_s2bm_ard_3-2-1_54JVN_2022-11-12_final.stac-item
2022-11-12 10:16:51	ga_s2bm_ard_3-2-1_53HQB_2022-11-12_final.stac-item
2022-11-12 10:16:59	ga_s2bm_ard_3-2-1_54HUF_2022-11-12_final.stac-item
2022-11-12 11:53:10	ga_s2bm_ard_3-2-1_50KRC_2022-11-12_final.stac-item
2022-11-12 11:53:31	ga_s2bm_ard_3-2-1_50KQB_2022-11-12_final.stac-item
2022-11-12 11:53:38	ga_s2bm_ard_3-2-1_50KNB_2022-11-12_final.stac-item
2022-11-12 11:53:42	ga_s2bm_ard_3-2-1_50KMB_2022-11-12_final.stac-item
2022-11-12 11:54:04	ga_s2bm_ard_3-2-1_50KPV_2022-11-12_final.stac-item
2022-11-12 11:54:07	ga_s2bm_ard_3-2-1_50KNV_2022-11-12_final.stac-item
2022-11-12 11:54:44	ga_s2bm_ard_3-2-1_50JLT_2022-11-12_final.stac-item
2022-11-12 11:54:47	ga_s2bm_ard_3-2-1_50JPS_2022-11-12_final.stac-item
2022-11-12 11:55:23	ga_s2bm_ard_3-2-1_50JMQ_2022-11-12_final.stac-item
2022-11-12 11:55:56	ga_s2bm_ard_3-2-1_50JLN_2022-11-12_final.stac-item
2022-11-12 11:55:59	ga_s2bm_ard_3-2-1_50JKN_2022-11-12_final.stac-item
2022-11-12 11:56:03	ga_s2bm_ard_3-2-1_50JNM_2022-11-12_final.stac-item
2022-11-12 11:56:20	ga_s2bm_ard_3-2-1_50JKM_2022-11-12_final.stac-item

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