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
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53HLD_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53HMD_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQB_2018-10-28_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KRB_2018-10-28_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53LPC_2018-10-28_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53LPD_2018-10-28_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53LQC_2018-10-28_final
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_54KTF_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_54KTG_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53HLE_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53HME_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKF_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKG_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKK_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JKL_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLF_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLG_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLK_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLL_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLM_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JLN_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMF_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMG_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMK_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JML_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_52JGL_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMM_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JMN_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_52JGM_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNF_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNG_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNH_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNJ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNK_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNL_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNM_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JNN_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JPL_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JPM_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53JPN_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KLP_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KLQ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMP_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMQ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMR_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMS_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMT_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KMU_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNA_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNB_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNP_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNQ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNR_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNS_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNT_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNU_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KNV_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPA_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPB_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPP_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPQ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPR_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPS_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPT_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPU_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KPV_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQA_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQQ_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQR_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQS_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQT_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQU_2018-10-28_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_53KQV_2018-10-28_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HTF_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HTG_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HTH_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HTJ_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HUF_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HUG_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HUH_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HUJ_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVD_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVE_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVF_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVG_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVH_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HVJ_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HWE_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HWF_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HWG_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HWH_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HWJ_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54HXJ_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_53HQA_2018-10-29_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

Other products

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