Search ga_s2bm_ard_3 across 2018

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n 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\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n 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\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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)\n 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.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KMU_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HKF_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GCN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HKG_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HKH_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GCP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HKJ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HKK_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GDN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HLJ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GDP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HLK_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GDQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HMJ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GDR_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56HMK_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GEN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKL_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKM_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GEP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GEQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GER_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GFN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKR_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GFP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JKS_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GFQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLL_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55GFR_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLM_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLR_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLS_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JLT_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JML_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMM_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMP_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMQ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMR_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMS_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JMT_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JNN_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JNS_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56JNT_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KLA_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HDS_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KLB_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HDT_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KLU_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HEA_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KLV_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_56KMA_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HES_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HET_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HEU_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HEV_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFA_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFB_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFC_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFD_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFE_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HFV_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGA_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGB_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGC_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGD_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGE_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55HGV_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55JGF_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55JGG_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55JGH_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55JGJ_2018-05-25_final.stac-item
2018-05-25 09:32:37	ga_s2bm_ard_3-2-1_55JHM_2018-05-25_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KTS_2018-06-23_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KTT_2018-06-23_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KTU_2018-06-23_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KUA_2018-06-23_final.stac-item
2018-06-23 11:37:58	ga_s2bm_ard_3-2-1_51KUS_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51JTM_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51JTN_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51JUM_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51JUN_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JPS_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JPT_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JQS_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JQT_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JRS_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_50JRT_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KTP_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KTQ_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KTR_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KTS_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KUP_2018-06-23_final.stac-item
2018-06-23 11:43:22	ga_s2bm_ard_3-2-1_51KUQ_2018-06-23_final.stac-item

Return to ga_s2bm_ard_3 across 2018 overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2018

All months