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
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50JLL_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50JLS_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50JMT_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KKA_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KLV_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KMU_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JGL_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2016-10-02_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HQH_2016-10-03_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HQK_2016-10-03_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50JPL_2016-10-03_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50JQN_2016-10-03_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51HTC_2016-10-03_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49JGM_2016-10-05_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_50KKA_2016-10-05_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-10-05_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49JHN_2016-10-05_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HLH_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HLJ_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HMK_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JLS_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JMT_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KMU_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KNU_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KQA_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KQB_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KQU_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50KRC_2016-10-09_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50HLK_2016-10-09_final.stac-item
2016-10-10 11:22:34	ga_s2am_ard_3-2-1_51HUE_2016-10-10_final.stac-item
2016-10-10 11:22:34	ga_s2am_ard_3-2-1_51HVE_2016-10-10_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_49KHR_2016-10-12_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KKA_2016-10-12_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KKV_2016-10-12_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KLV_2016-10-12_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_49KHQ_2016-10-12_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-10-12_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_50JLS_2016-10-12_final.stac-item
2016-10-13 11:35:59	ga_s2am_ard_3-2-1_50JPL_2016-10-13_final.stac-item
2016-10-13 11:35:59	ga_s2am_ard_3-2-1_51HUE_2016-10-13_final.stac-item
2016-10-15 12:13:39	ga_s2am_ard_3-2-1_49KHR_2016-10-15_final.stac-item
2016-10-15 12:13:39	ga_s2am_ard_3-2-1_49KHQ_2016-10-15_final.stac-item
2016-10-15 12:14:55	ga_s2am_ard_3-2-1_49JGM_2016-10-15_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HLH_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HPH_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50HQK_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JPQ_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JPT_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50JQP_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50KQA_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50KRB_2016-10-16_final.stac-item
2016-10-16 11:40:08	ga_s2am_ard_3-2-1_50KRC_2016-10-16_final.stac-item
2016-10-19 11:56:02	ga_s2am_ard_3-2-1_50JMM_2016-10-19_final.stac-item
2016-10-20 11:26:04	ga_s2am_ard_3-2-1_51HUE_2016-10-20_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGM_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHR_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JKT_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JLP_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JLS_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50JMT_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KKA_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KLU_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KLV_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KMU_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_50KNC_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JGL_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-22_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KHQ_2016-10-22_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HPH_2016-10-23_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQH_2016-10-23_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50JPL_2016-10-23_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50JQN_2016-10-23_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50JQP_2016-10-23_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49KHR_2016-10-25_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_50KKV_2016-10-25_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JGL_2016-10-25_final.stac-item
2016-10-25 12:13:17	ga_s2am_ard_3-2-1_49JHN_2016-10-25_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HMK_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HPH_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HQK_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JPQ_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JPT_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JQN_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50JQP_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50KQA_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50KRB_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50KRC_2016-10-26_final.stac-item
2016-10-29 11:43:41	ga_s2am_ard_3-2-1_50JPT_2016-10-29_final.stac-item
2016-10-29 11:43:41	ga_s2am_ard_3-2-1_50KMU_2016-10-29_final.stac-item
2016-10-29 11:43:41	ga_s2am_ard_3-2-1_50KNU_2016-10-29_final.stac-item
2016-10-29 11:43:41	ga_s2am_ard_3-2-1_50KQA_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLH_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLJ_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JMN_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JPQ_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50KLU_2016-10-29_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLK_2016-10-29_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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