Search ga_s2am_ard_3 whole collection

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
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTN_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTP_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTQ_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTR_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTS_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JTT_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54JUT_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54KTU_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HLD_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HLE_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_54KUU_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HMD_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HME_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HNB_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HNC_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HND_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HNE_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HPA_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HPB_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HPC_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HPD_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HPE_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53HQE_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JMF_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JMG_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JMH_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JMJ_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNF_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNG_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNH_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNJ_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNK_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNL_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNM_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JNN_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPF_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPG_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPH_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPJ_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPK_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPL_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPM_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JPN_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQF_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQG_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQH_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQJ_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQK_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQL_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQM_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JQN_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JRM_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53JRN_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53KPP_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53KQP_2017-11-19_final.stac-item
2017-11-19 10:33:38	ga_s2am_ard_3-2-1_53KRP_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKA_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKB_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKU_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_50KKV_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JFM_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JFN_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGK_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGL_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGM_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGN_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JHN_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGP_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGQ_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KGR_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHP_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHQ_2017-11-19_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHR_2017-11-19_final.stac-item
2017-11-20 10:00:29	ga_s2am_ard_3-2-1_54KZB_2017-11-20_final.stac-item
2017-11-20 10:00:29	ga_s2am_ard_3-2-1_54KZC_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KYU_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KZA_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KZB_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KZC_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KZU_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_54KZV_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_55KBP_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_55KBQ_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_55KBR_2017-11-20_final.stac-item
2017-11-20 10:02:35	ga_s2am_ard_3-2-1_55KBS_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HVH_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HWH_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HWJ_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HWK_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HXG_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HXH_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HXJ_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HXK_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HYG_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HYH_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HYJ_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_54HYK_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_55HBB_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_55HBC_2017-11-20_final.stac-item
2017-11-20 10:05:49	ga_s2am_ard_3-2-1_55HBD_2017-11-20_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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