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

95 results

Time (local)	Label
2022-12-02 09:52:45	ga_ls8c_ard_3-2-1_096071_2022-12-02_final
2022-12-02 09:53:09	ga_ls8c_ard_3-2-1_096072_2022-12-02_final
2022-12-02 09:56:20	ga_ls8c_ard_3-2-1_096080_2022-12-02_final
2022-12-02 09:56:44	ga_ls8c_ard_3-2-1_096081_2022-12-02_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-02 09:57:56	ga_ls8c_ard_3-2-1_096084_2022-12-02_final
2022-12-02 11:32:02	ga_ls8c_ard_3-2-1_112072_2022-12-02_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-03 10:39:12	ga_ls8c_ard_3-2-1_103079_2022-12-03_final
2022-12-04 09:40:23	ga_ls8c_ard_3-2-1_094071_2022-12-04_final
2022-12-04 09:40:47	ga_ls8c_ard_3-2-1_094072_2022-12-04_final
2022-12-04 09:42:23	ga_ls8c_ard_3-2-1_094076_2022-12-04_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-04 09:43:59	ga_ls8c_ard_3-2-1_094080_2022-12-04_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-04 09:45:58	ga_ls8c_ard_3-2-1_094085_2022-12-04_final
2022-12-04 09:46:22	ga_ls8c_ard_3-2-1_094086_2022-12-04_final
2022-12-04 11:18:28	ga_ls8c_ard_3-2-1_110069_2022-12-04_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-04 11:24:27	ga_ls8c_ard_3-2-1_110084_2022-12-04_final
2022-12-04 11:24:51	ga_ls8c_ard_3-2-1_110085_2022-12-04_final
2022-12-05 10:23:39	ga_ls8c_ard_3-2-1_101071_2022-12-05_final
2022-12-05 10:24:03	ga_ls8c_ard_3-2-1_101072_2022-12-05_final
2022-12-05 10:24:50	ga_ls8c_ard_3-2-1_101074_2022-12-05_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-05 10:27:14	ga_ls8c_ard_3-2-1_101080_2022-12-05_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-07 10:10:53	ga_ls8c_ard_3-2-1_099070_2022-12-07_final
2022-12-07 10:12:28	ga_ls8c_ard_3-2-1_099074_2022-12-07_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-07 10:14:28	ga_ls8c_ard_3-2-1_099079_2022-12-07_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-07 10:15:16	ga_ls8c_ard_3-2-1_099081_2022-12-07_final
2022-12-07 10:16:04	ga_ls8c_ard_3-2-1_099083_2022-12-07_final
2022-12-07 11:51:21	ga_ls8c_ard_3-2-1_115074_2022-12-07_final
2022-12-07 11:53:21	ga_ls8c_ard_3-2-1_115079_2022-12-07_final
2022-12-07 11:53:45	ga_ls8c_ard_3-2-1_115080_2022-12-07_final
2022-12-08 09:16:51	ga_ls8c_ard_3-2-1_090074_2022-12-07_final
2022-12-08 09:17:15	ga_ls8c_ard_3-2-1_090075_2022-12-07_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-08 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-12-07_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-08 09:23:14	ga_ls8c_ard_3-2-1_090090_2022-12-07_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-08 10:54:56	ga_ls8c_ard_3-2-1_106072_2022-12-08_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-08 10:56:08	ga_ls8c_ard_3-2-1_106075_2022-12-08_final
2022-12-08 10:56:32	ga_ls8c_ard_3-2-1_106076_2022-12-08_final
2022-12-08 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-12-08_final
2022-12-09 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-12-09_final
2022-12-09 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-12-09_final
2022-12-09 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-12-09_final
2022-12-09 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-12-09_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-09 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-12-09_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-09 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-12-09_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-09 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-12-09_final
2022-12-09 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-12-09_final
2022-12-09 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-12-09_final
2022-12-09 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-12-09_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-10 10:44:09	ga_ls8c_ard_3-2-1_104076_2022-12-10_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-12-11_final
2022-12-11 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-12-11_final
2022-12-11 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-12-11_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-11 09:51:19	ga_ls8c_ard_3-2-1_095083_2022-12-11_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-11 11:24:13	ga_ls8c_ard_3-2-1_111068_2022-12-11_final
2022-12-11 11:24:37	ga_ls8c_ard_3-2-1_111069_2022-12-11_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2022-12-11 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-12-11_final
2022-12-11 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-12-11_final
2022-12-11 11:28:36	ga_ls8c_ard_3-2-1_111079_2022-12-11_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years