Search ga_ls8c_ard_3 whole collection

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:

Add field

First 100 results (query limit)

Time (local)	Label
2022-03-29 10:40:11	ga_ls8c_ard_3-2-1_104068_2022-03-29_final
2022-03-29 10:40:35	ga_ls8c_ard_3-2-1_104069_2022-03-29_final
2022-03-29 10:40:58	ga_ls8c_ard_3-2-1_104070_2022-03-29_final
2022-03-29 10:41:22	ga_ls8c_ard_3-2-1_104071_2022-03-29_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-03-29 10:42:10	ga_ls8c_ard_3-2-1_104073_2022-03-29_final
2022-03-31 10:27:48	ga_ls8c_ard_3-2-1_102068_2022-03-31_final
2022-03-31 10:28:12	ga_ls8c_ard_3-2-1_102069_2022-03-31_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-03-31 10:29:00	ga_ls8c_ard_3-2-1_102071_2022-03-31_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-03-31 10:29:48	ga_ls8c_ard_3-2-1_102073_2022-03-31_final
2022-03-31 10:30:12	ga_ls8c_ard_3-2-1_102074_2022-03-31_final
2022-03-31 10:30:36	ga_ls8c_ard_3-2-1_102075_2022-03-31_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-03-31 10:31:24	ga_ls8c_ard_3-2-1_102077_2022-03-31_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-03-31 10:32:12	ga_ls8c_ard_3-2-1_102079_2022-03-31_final
2022-03-31 10:32:36	ga_ls8c_ard_3-2-1_102080_2022-03-31_final
2022-03-31 10:33:00	ga_ls8c_ard_3-2-1_102081_2022-03-31_final
2022-03-31 10:33:23	ga_ls8c_ard_3-2-1_102082_2022-03-31_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-02 10:19:02	ga_ls8c_ard_3-2-1_100077_2022-04-02_final
2022-04-02 10:19:26	ga_ls8c_ard_3-2-1_100078_2022-04-02_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-02 10:20:14	ga_ls8c_ard_3-2-1_100080_2022-04-02_final
2022-04-02 10:20:38	ga_ls8c_ard_3-2-1_100081_2022-04-02_final
2022-04-02 10:21:02	ga_ls8c_ard_3-2-1_100082_2022-04-02_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-04 10:09:29	ga_ls8c_ard_3-2-1_098084_2022-04-04_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-05 10:45:58	ga_ls8c_ard_3-2-1_105067_2022-04-05_final
2022-04-05 10:46:22	ga_ls8c_ard_3-2-1_105068_2022-04-05_final
2022-04-07 10:34:02	ga_ls8c_ard_3-2-1_103068_2022-04-07_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-07 10:34:50	ga_ls8c_ard_3-2-1_103070_2022-04-07_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-07 10:36:50	ga_ls8c_ard_3-2-1_103075_2022-04-07_final
2022-04-07 10:37:13	ga_ls8c_ard_3-2-1_103076_2022-04-07_final
2022-04-07 10:37:37	ga_ls8c_ard_3-2-1_103077_2022-04-07_final
2022-04-09 10:22:29	ga_ls8c_ard_3-2-1_101070_2022-04-09_final
2022-04-09 10:22:53	ga_ls8c_ard_3-2-1_101071_2022-04-09_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:24:05	ga_ls8c_ard_3-2-1_101074_2022-04-09_final
2022-04-09 10:24:29	ga_ls8c_ard_3-2-1_101075_2022-04-09_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-09 10:25:17	ga_ls8c_ard_3-2-1_101077_2022-04-09_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-09 10:26:29	ga_ls8c_ard_3-2-1_101080_2022-04-09_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-09 10:27:17	ga_ls8c_ard_3-2-1_101082_2022-04-09_final
2022-04-09 10:27:41	ga_ls8c_ard_3-2-1_101083_2022-04-09_final
2022-04-11 10:13:44	ga_ls8c_ard_3-2-1_099079_2022-04-11_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-11 10:14:32	ga_ls8c_ard_3-2-1_099081_2022-04-11_final
2022-04-11 10:14:56	ga_ls8c_ard_3-2-1_099082_2022-04-11_final
2022-04-11 10:15:20	ga_ls8c_ard_3-2-1_099083_2022-04-11_final
2022-04-11 10:15:44	ga_ls8c_ard_3-2-1_099084_2022-04-11_final
2022-04-11 10:16:08	ga_ls8c_ard_3-2-1_099085_2022-04-11_final
2022-04-14 10:40:16	ga_ls8c_ard_3-2-1_104068_2022-04-14_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-14 10:41:28	ga_ls8c_ard_3-2-1_104071_2022-04-14_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-14 10:42:16	ga_ls8c_ard_3-2-1_104073_2022-04-14_final
2022-04-16 10:27:54	ga_ls8c_ard_3-2-1_102068_2022-04-16_final
2022-04-16 10:28:18	ga_ls8c_ard_3-2-1_102069_2022-04-16_final
2022-04-16 10:28:42	ga_ls8c_ard_3-2-1_102070_2022-04-16_final
2022-04-16 10:29:06	ga_ls8c_ard_3-2-1_102071_2022-04-16_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-16 10:29:54	ga_ls8c_ard_3-2-1_102073_2022-04-16_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-04-16 10:33:06	ga_ls8c_ard_3-2-1_102081_2022-04-16_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-18 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-04-18_final
2022-04-18 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-04-18_final
2022-04-18 10:19:08	ga_ls8c_ard_3-2-1_100077_2022-04-18_final
2022-04-18 10:19:32	ga_ls8c_ard_3-2-1_100078_2022-04-18_final
2022-04-18 10:19:56	ga_ls8c_ard_3-2-1_100079_2022-04-18_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-18 10:21:08	ga_ls8c_ard_3-2-1_100082_2022-04-18_final
2022-04-18 10:21:32	ga_ls8c_ard_3-2-1_100083_2022-04-18_final
2022-04-18 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-04-18_final
2022-04-20 10:09:09	ga_ls8c_ard_3-2-1_098083_2022-04-20_final
2022-04-20 10:09:33	ga_ls8c_ard_3-2-1_098084_2022-04-20_final

Return to ga_ls8c_ard_3 whole collection 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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years