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
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HLD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HLE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HMD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HME_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HNB_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HNC_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HND_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HNE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HPA_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HPB_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HPC_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HPD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HPE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53HQE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JMF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JMG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JMH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JMJ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNJ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNK_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNL_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNM_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JNN_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPJ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPK_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPL_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPM_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPN_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQJ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQK_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQL_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQM_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JQN_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JRM_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JRN_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KPP_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KPQ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KPR_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KPS_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQA_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQP_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQQ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQR_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQS_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQT_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQU_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KQV_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRA_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRB_2018-10-15_final
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRP_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRQ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRR_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRS_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRT_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRU_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53KRV_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTN_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTP_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTQ_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTR_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTS_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JTT_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54JUT_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTA_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTB_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTC_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTU_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KTV_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUA_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUB_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUC_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUU_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KUV_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KVC_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KVD_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KVE_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KVF_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KVG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54KWG_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54LUH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54LVH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54LWH_2018-10-15_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_54LWJ_2018-10-15_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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