Search ga_ls8c_ard_3 across May 2022

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

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. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

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First 100 results (query limit)

Time (local)	Label
2022-05-01 11:23:29	ga_ls8c_ard_3-2-1_111068_2022-05-01_final
2022-05-01 11:23:53	ga_ls8c_ard_3-2-1_111069_2022-05-01_final
2022-05-01 11:24:16	ga_ls8c_ard_3-2-1_111070_2022-05-01_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-01 11:25:04	ga_ls8c_ard_3-2-1_111072_2022-05-01_final
2022-05-01 11:25:28	ga_ls8c_ard_3-2-1_111073_2022-05-01_final
2022-05-01 11:25:52	ga_ls8c_ard_3-2-1_111074_2022-05-01_final
2022-05-01 11:26:16	ga_ls8c_ard_3-2-1_111075_2022-05-01_final
2022-05-01 11:26:40	ga_ls8c_ard_3-2-1_111076_2022-05-01_final
2022-05-01 11:27:04	ga_ls8c_ard_3-2-1_111077_2022-05-01_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-01 11:29:04	ga_ls8c_ard_3-2-1_111082_2022-05-01_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-02 10:27:28	ga_ls8c_ard_3-2-1_102067_2022-05-02_final
2022-05-02 10:27:52	ga_ls8c_ard_3-2-1_102068_2022-05-02_final
2022-05-02 10:28:16	ga_ls8c_ard_3-2-1_102069_2022-05-02_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-02 10:29:52	ga_ls8c_ard_3-2-1_102073_2022-05-02_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-02 10:30:40	ga_ls8c_ard_3-2-1_102075_2022-05-02_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_final
2022-05-02 10:31:28	ga_ls8c_ard_3-2-1_102077_2022-05-02_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-02 10:32:15	ga_ls8c_ard_3-2-1_102079_2022-05-02_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-02 10:33:03	ga_ls8c_ard_3-2-1_102081_2022-05-02_final
2022-05-02 10:33:27	ga_ls8c_ard_3-2-1_102082_2022-05-02_final
2022-05-03 09:33:27	ga_ls8c_ard_3-2-1_093071_2022-05-03_final
2022-05-03 09:33:51	ga_ls8c_ard_3-2-1_093072_2022-05-03_final
2022-05-03 09:34:15	ga_ls8c_ard_3-2-1_093073_2022-05-03_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-03 09:36:15	ga_ls8c_ard_3-2-1_093078_2022-05-03_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-03 11:11:56	ga_ls8c_ard_3-2-1_109070_2022-05-03_final
2022-05-03 11:12:20	ga_ls8c_ard_3-2-1_109071_2022-05-03_final
2022-05-03 11:12:44	ga_ls8c_ard_3-2-1_109072_2022-05-03_final
2022-05-03 11:13:08	ga_ls8c_ard_3-2-1_109073_2022-05-03_final
2022-05-03 11:13:32	ga_ls8c_ard_3-2-1_109074_2022-05-03_final
2022-05-03 11:13:56	ga_ls8c_ard_3-2-1_109075_2022-05-03_final
2022-05-03 11:14:20	ga_ls8c_ard_3-2-1_109076_2022-05-03_final
2022-05-03 11:14:44	ga_ls8c_ard_3-2-1_109077_2022-05-03_final
2022-05-03 11:15:08	ga_ls8c_ard_3-2-1_109078_2022-05-03_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-03 11:16:20	ga_ls8c_ard_3-2-1_109081_2022-05-03_final
2022-05-03 11:16:44	ga_ls8c_ard_3-2-1_109082_2022-05-03_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-04 08:42:14	ga_ls8c_ard_3-2-1_084082_2022-05-03_final
2022-05-04 10:16:44	ga_ls8c_ard_3-2-1_100071_2022-05-04_final
2022-05-04 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-05-04_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-04 10:19:07	ga_ls8c_ard_3-2-1_100077_2022-05-04_final
2022-05-04 10:19:31	ga_ls8c_ard_3-2-1_100078_2022-05-04_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-04 10:21:07	ga_ls8c_ard_3-2-1_100082_2022-05-04_final
2022-05-04 10:21:31	ga_ls8c_ard_3-2-1_100083_2022-05-04_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-04 11:57:13	ga_ls8c_ard_3-2-1_116075_2022-05-04_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-06 10:07:59	ga_ls8c_ard_3-2-1_098080_2022-05-06_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-06 10:08:47	ga_ls8c_ard_3-2-1_098082_2022-05-06_final
2022-05-06 11:44:29	ga_ls8c_ard_3-2-1_114074_2022-05-06_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-07 09:10:23	ga_ls8c_ard_3-2-1_089075_2022-05-06_final
2022-05-07 09:10:47	ga_ls8c_ard_3-2-1_089076_2022-05-06_final
2022-05-07 09:11:11	ga_ls8c_ard_3-2-1_089077_2022-05-06_final
2022-05-07 09:11:35	ga_ls8c_ard_3-2-1_089078_2022-05-06_final
2022-05-07 09:11:59	ga_ls8c_ard_3-2-1_089079_2022-05-06_final
2022-05-07 10:47:40	ga_ls8c_ard_3-2-1_105071_2022-05-07_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-07 10:48:52	ga_ls8c_ard_3-2-1_105074_2022-05-07_final

Return to ga_ls8c_ard_3 across May 2022 overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2022

May

All days