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
2016-05-21 11:44:13	ga_ls8c_ard_3-0-0_114074_2016-05-21_final
2016-07-08 11:44:32	ga_ls8c_ard_3-0-0_114074_2016-07-08_final
2016-07-10 11:33:47	ga_ls8c_ard_3-0-0_112078_2016-07-10_final
2016-07-10 11:34:11	ga_ls8c_ard_3-0-0_112079_2016-07-10_final
2016-07-10 11:34:35	ga_ls8c_ard_3-0-0_112080_2016-07-10_final
2016-07-10 11:34:59	ga_ls8c_ard_3-0-0_112081_2016-07-10_final
2016-07-10 11:35:23	ga_ls8c_ard_3-0-0_112082_2016-07-10_final
2016-07-10 11:35:47	ga_ls8c_ard_3-0-0_112083_2016-07-10_final
2016-08-20 11:29:23	ga_ls8c_ard_3-0-0_111082_2016-08-20_final
2016-08-20 11:29:47	ga_ls8c_ard_3-0-0_111083_2016-08-20_final
2016-08-20 11:30:11	ga_ls8c_ard_3-0-0_111084_2016-08-20_final
2016-08-20 11:30:35	ga_ls8c_ard_3-0-0_111085_2016-08-20_final
2016-09-05 11:29:29	ga_ls8c_ard_3-0-0_111082_2016-09-05_final
2016-09-05 11:29:53	ga_ls8c_ard_3-0-0_111083_2016-09-05_final
2016-09-05 11:30:17	ga_ls8c_ard_3-0-0_111084_2016-09-05_final
2016-09-05 11:30:41	ga_ls8c_ard_3-0-0_111085_2016-09-05_final
2016-09-12 11:34:05	ga_ls8c_ard_3-0-0_112078_2016-09-12_final
2016-09-12 11:34:29	ga_ls8c_ard_3-0-0_112079_2016-09-12_final
2016-09-12 11:34:53	ga_ls8c_ard_3-0-0_112080_2016-09-12_final
2016-09-12 11:35:17	ga_ls8c_ard_3-0-0_112081_2016-09-12_final
2016-09-12 11:35:41	ga_ls8c_ard_3-0-0_112082_2016-09-12_final
2016-09-12 11:36:05	ga_ls8c_ard_3-0-0_112083_2016-09-12_final
2016-09-21 11:29:31	ga_ls8c_ard_3-0-0_111082_2016-09-21_final
2016-09-21 11:29:55	ga_ls8c_ard_3-0-0_111083_2016-09-21_final
2016-09-21 11:30:19	ga_ls8c_ard_3-0-0_111084_2016-09-21_final
2016-09-21 11:30:43	ga_ls8c_ard_3-0-0_111085_2016-09-21_final
2016-10-23 11:29:37	ga_ls8c_ard_3-0-0_111082_2016-10-23_final
2016-10-23 11:30:01	ga_ls8c_ard_3-0-0_111083_2016-10-23_final
2016-10-23 11:30:25	ga_ls8c_ard_3-0-0_111084_2016-10-23_final
2016-10-23 11:30:49	ga_ls8c_ard_3-0-0_111085_2016-10-23_final
2016-10-30 11:34:13	ga_ls8c_ard_3-0-0_112078_2016-10-30_final
2016-10-30 11:34:37	ga_ls8c_ard_3-0-0_112079_2016-10-30_final
2016-10-30 11:35:01	ga_ls8c_ard_3-0-0_112080_2016-10-30_final
2016-10-30 11:35:25	ga_ls8c_ard_3-0-0_112081_2016-10-30_final
2016-10-30 11:35:48	ga_ls8c_ard_3-0-0_112082_2016-10-30_final
2016-10-30 11:36:12	ga_ls8c_ard_3-0-0_112083_2016-10-30_final
2016-11-01 11:24:39	ga_ls8c_ard_3-0-0_110085_2016-11-01_final
2016-11-06 11:38:23	ga_ls8c_ard_3-1-0_113073_2016-11-06_final
2016-11-06 11:38:47	ga_ls8c_ard_3-0-0_113074_2016-11-06_final
2016-11-06 11:39:11	ga_ls8c_ard_3-0-0_113075_2016-11-06_final
2016-11-06 11:39:35	ga_ls8c_ard_3-0-0_113076_2016-11-06_final
2016-11-06 11:39:59	ga_ls8c_ard_3-0-0_113077_2016-11-06_final
2016-11-06 11:40:23	ga_ls8c_ard_3-0-0_113078_2016-11-06_final
2016-11-08 11:29:37	ga_ls8c_ard_3-0-0_111082_2016-11-08_final
2016-11-08 11:30:01	ga_ls8c_ard_3-0-0_111083_2016-11-08_final
2016-11-08 11:30:24	ga_ls8c_ard_3-0-0_111084_2016-11-08_final
2016-11-08 11:30:48	ga_ls8c_ard_3-0-0_111085_2016-11-08_final
2016-11-17 11:24:38	ga_ls8c_ard_3-0-0_110085_2016-11-17_final
2021-10-26 11:45:04	ga_ls8c_ard_3-2-0_114074_2021-10-26_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-31 11:38:01	ga_ls8c_ard_3-2-1_113073_2022-05-31_final
2022-05-31 11:38:25	ga_ls8c_ard_3-2-1_113074_2022-05-31_final
2022-05-31 11:38:49	ga_ls8c_ard_3-2-1_113075_2022-05-31_final
2022-05-31 11:39:13	ga_ls8c_ard_3-2-1_113076_2022-05-31_final
2022-05-31 11:39:37	ga_ls8c_ard_3-2-1_113077_2022-05-31_final
2022-05-31 11:40:01	ga_ls8c_ard_3-2-1_113078_2022-05-31_final
2022-05-31 11:40:25	ga_ls8c_ard_3-2-1_113079_2022-05-31_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-02 11:29:41	ga_ls8c_ard_3-2-1_111083_2022-06-02_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-07 11:44:42	ga_ls8c_ard_3-2-1_114074_2022-06-07_final
2022-06-09 11:33:58	ga_ls8c_ard_3-2-1_112078_2022-06-09_final
2022-06-09 11:34:22	ga_ls8c_ard_3-2-1_112079_2022-06-09_final
2022-06-09 11:34:46	ga_ls8c_ard_3-2-1_112080_2022-06-09_final
2022-06-09 11:35:10	ga_ls8c_ard_3-2-1_112081_2022-06-09_final
2022-06-09 11:35:34	ga_ls8c_ard_3-2-1_112082_2022-06-09_final
2022-06-09 11:35:58	ga_ls8c_ard_3-2-1_112083_2022-06-09_final
2022-06-11 11:24:25	ga_ls8c_ard_3-2-1_110085_2022-06-11_final
2022-06-16 11:38:14	ga_ls8c_ard_3-2-1_113073_2022-06-16_final
2022-06-16 11:38:38	ga_ls8c_ard_3-2-1_113074_2022-06-16_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-16 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-06-16_final
2022-06-16 11:39:49	ga_ls8c_ard_3-2-1_113077_2022-06-16_final
2022-06-16 11:40:13	ga_ls8c_ard_3-2-1_113078_2022-06-16_final
2022-06-16 11:40:37	ga_ls8c_ard_3-2-1_113079_2022-06-16_final
2022-06-18 11:29:28	ga_ls8c_ard_3-2-1_111082_2022-06-18_final
2022-06-18 11:29:52	ga_ls8c_ard_3-2-1_111083_2022-06-18_final
2022-06-18 11:30:16	ga_ls8c_ard_3-2-1_111084_2022-06-18_final
2022-06-23 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-06-23_final
2022-06-25 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-06-25_final
2022-06-25 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-06-25_final
2022-06-25 11:34:54	ga_ls8c_ard_3-2-1_112080_2022-06-25_final
2022-06-25 11:35:17	ga_ls8c_ard_3-2-1_112081_2022-06-25_final
2022-06-25 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-06-25_final
2022-06-25 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-06-25_final
2022-06-27 11:24:32	ga_ls8c_ard_3-2-1_110085_2022-06-27_final
2022-07-02 11:38:18	ga_ls8c_ard_3-2-1_113073_2022-07-02_final
2022-07-02 11:38:41	ga_ls8c_ard_3-2-1_113074_2022-07-02_final
2022-07-02 11:39:05	ga_ls8c_ard_3-2-1_113075_2022-07-02_final
2022-07-02 11:39:29	ga_ls8c_ard_3-2-1_113076_2022-07-02_final
2022-07-02 11:39:53	ga_ls8c_ard_3-2-1_113077_2022-07-02_final
2022-07-02 11:40:17	ga_ls8c_ard_3-2-1_113078_2022-07-02_final
2022-07-02 11:40:41	ga_ls8c_ard_3-2-1_113079_2022-07-02_final
2022-07-09 11:44:52	ga_ls8c_ard_3-2-1_114074_2022-07-09_final
2022-07-11 11:34:06	ga_ls8c_ard_3-2-1_112078_2022-07-11_final
2022-07-11 11:34:30	ga_ls8c_ard_3-2-1_112079_2022-07-11_final
2022-07-11 11:34:54	ga_ls8c_ard_3-2-1_112080_2022-07-11_final
2022-07-11 11:35:18	ga_ls8c_ard_3-2-1_112081_2022-07-11_final
2022-07-11 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-07-11_final
2022-07-11 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-07-11_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