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
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HLH_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HLJ_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HMK_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JNL_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HMH_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HMJ_2018-05-02_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50HNK_2018-05-02_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50HQH_2018-05-06_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50HPJ_2018-05-06_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HLH_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HMK_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HQH_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50JNL_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HMH_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNJ_2018-05-09_final.stac-item
2018-05-09 11:44:46	ga_s2am_ard_3-2-1_50HNK_2018-05-09_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLH_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HLJ_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HMK_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50JNL_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HMH_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HMJ_2018-05-12_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50HNK_2018-05-12_final.stac-item
2018-05-13 11:26:36	ga_s2am_ard_3-2-1_51HTC_2018-05-13_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HQH_2018-05-16_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HPJ_2018-05-16_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HLH_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HMK_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HQH_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50JNL_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HMH_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HNH_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HNK_2018-05-19_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HPJ_2018-05-19_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLJ_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JNL_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HMH_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HMJ_2018-05-22_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HNK_2018-05-22_final.stac-item
2018-05-23 11:25:37	ga_s2am_ard_3-2-1_51HTC_2018-05-23_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50HQH_2018-05-26_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_50HPJ_2018-05-26_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HLH_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HMK_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HQH_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50JNL_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HMH_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HMJ_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HNK_2018-05-29_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HPJ_2018-05-29_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLN_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JLS_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JMP_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JMQ_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JNR_2018-06-01_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50JNS_2018-06-01_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50JLN_2018-06-04_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JPS_2018-06-08_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50JQN_2018-06-08_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JLS_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JMP_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JMQ_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JNR_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JNS_2018-06-11_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JPS_2018-06-11_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLN_2018-06-14_final.stac-item
2018-06-14 12:03:57	ga_s2am_ard_3-2-1_50JLS_2018-06-14_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50JQN_2018-06-15_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50JQP_2018-06-15_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JNR_2018-06-18_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JPS_2018-06-18_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQN_2018-06-18_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50JQP_2018-06-18_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JLN_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JMQ_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JNR_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JNS_2018-06-21_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JPS_2018-06-21_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JLN_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JLS_2018-06-24_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JPS_2018-06-28_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50JQP_2018-06-28_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JQN_2018-06-28_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51HTC_2018-08-01_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51HVC_2018-08-01_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HTC_2018-08-04_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HTD_2018-08-04_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HVE_2018-08-04_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HNH_2018-08-07_final.stac-item
2018-08-11 11:25:57	ga_s2am_ard_3-2-1_51HTC_2018-08-11_final.stac-item
2018-08-21 11:21:36	ga_s2am_ard_3-2-1_51HTC_2018-08-21_final.stac-item
2018-08-21 11:21:36	ga_s2am_ard_3-2-1_51HVC_2018-08-21_final.stac-item
2018-08-21 11:21:36	ga_s2am_ard_3-2-1_51HVE_2018-08-21_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51HTC_2018-08-24_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51HTD_2018-08-24_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HLH_2018-08-30_final.stac-item
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HTC_2018-08-31_final.stac-item
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HVE_2018-08-31_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50KRD_2018-09-06_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51HTC_2018-09-10_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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