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
2023-07-16 09:43:07	ga_ls8c_ard_3-2-1_094080_2023-07-16_final
2023-07-18 09:29:34	ga_ls8c_ard_3-2-1_092077_2023-07-17_final
2023-07-19 10:10:25	ga_ls8c_ard_3-2-1_099071_2023-07-19_final
2023-07-20 09:17:59	ga_ls8c_ard_3-2-1_090079_2023-07-19_final
2023-07-20 09:18:23	ga_ls8c_ard_3-2-1_090080_2023-07-19_final
2023-07-21 11:38:57	ga_ls8c_ard_3-2-1_113076_2023-07-21_final
2023-07-27 09:27:28	ga_ls8c_ard_3-2-1_091087_2023-07-26_final
2023-08-01 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-08-01_final
2023-08-04 10:09:47	ga_ls8c_ard_3-2-1_099069_2023-08-04_final
2023-08-04 11:50:40	ga_ls8c_ard_3-2-1_115074_2023-08-04_final
2023-08-05 09:17:45	ga_ls8c_ard_3-2-1_090078_2023-08-04_final
2023-08-09 10:31:31	ga_ls8c_ard_3-2-1_102077_2023-08-09_final
2023-08-09 10:31:55	ga_ls8c_ard_3-2-1_102078_2023-08-09_final
2023-08-10 09:36:41	ga_ls8c_ard_3-2-1_093079_2023-08-10_final
2023-08-10 11:12:23	ga_ls8c_ard_3-2-1_109071_2023-08-10_final
2023-08-10 11:12:47	ga_ls8c_ard_3-2-1_109072_2023-08-10_final
2023-08-10 11:15:34	ga_ls8c_ard_3-2-1_109079_2023-08-10_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-11 10:19:57	ga_ls8c_ard_3-2-1_100079_2023-08-11_final
2023-08-18 10:24:38	ga_ls8c_ard_3-2-1_101075_2023-08-18_final
2023-08-18 10:26:14	ga_ls8c_ard_3-2-1_101079_2023-08-18_final
2023-08-19 09:29:49	ga_ls8c_ard_3-2-1_092077_2023-08-18_final
2023-08-20 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-08-20_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-22 11:40:49	ga_ls8c_ard_3-2-1_113080_2023-08-22_final
2023-08-24 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-08-24_final
2023-08-24 11:27:40	ga_ls8c_ard_3-2-1_111078_2023-08-24_final
2023-08-26 09:36:50	ga_ls8c_ard_3-2-1_093079_2023-08-26_final
2023-08-27 10:21:42	ga_ls8c_ard_3-2-1_100083_2023-08-27_final
2023-08-28 09:24:05	ga_ls8c_ard_3-2-1_091078_2023-08-27_final
2023-08-29 10:03:21	ga_ls8c_ard_3-2-1_098068_2023-08-29_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-30 10:47:01	ga_ls8c_ard_3-2-1_105069_2023-08-30_final
2023-09-01 10:38:38	ga_ls8c_ard_3-2-1_103079_2023-09-01_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-04 09:30:14	ga_ls8c_ard_3-2-1_092078_2023-09-04_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-04 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-09-04_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-05 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-09-05_final
2023-09-06 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-09-06_final
2023-09-08 10:40:24	ga_ls8c_ard_3-2-1_104068_2023-09-08_final
2023-09-09 11:26:53	ga_ls8c_ard_3-2-1_111076_2023-09-09_final
2023-09-09 11:28:04	ga_ls8c_ard_3-2-1_111079_2023-09-09_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-10 10:32:52	ga_ls8c_ard_3-2-1_102080_2023-09-10_final
2023-09-11 11:12:57	ga_ls8c_ard_3-2-1_109072_2023-09-11_final
2023-09-12 10:21:43	ga_ls8c_ard_3-2-1_100083_2023-09-12_final
2023-09-13 09:23:43	ga_ls8c_ard_3-2-1_091077_2023-09-12_final
2023-09-13 09:25:19	ga_ls8c_ard_3-2-1_091081_2023-09-12_final
2023-09-13 09:28:07	ga_ls8c_ard_3-2-1_091088_2023-09-12_final
2023-09-13 11:01:48	ga_ls8c_ard_3-2-1_107075_2023-09-13_final
2023-09-15 10:52:15	ga_ls8c_ard_3-2-1_105082_2023-09-15_final
2023-09-17 10:37:30	ga_ls8c_ard_3-2-1_103076_2023-09-17_final
2023-09-20 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-09-19_final
2023-09-25 09:51:41	ga_ls8c_ard_3-2-1_095085_2023-09-25_final
2023-09-25 11:26:35	ga_ls8c_ard_3-2-1_111075_2023-09-25_final
2023-09-25 11:28:10	ga_ls8c_ard_3-2-1_111079_2023-09-25_final
2023-09-27 11:15:02	ga_ls8c_ard_3-2-1_109077_2023-09-27_final
2023-09-28 10:22:13	ga_ls8c_ard_3-2-1_100084_2023-09-28_final
2023-10-01 10:50:20	ga_ls8c_ard_3-2-1_105077_2023-10-01_final
2023-10-03 10:37:10	ga_ls8c_ard_3-2-1_103075_2023-10-03_final
2023-10-05 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-10-05_final
2023-10-06 11:08:27	ga_ls8c_ard_3-2-1_108076_2023-10-06_final
2023-10-07 10:12:51	ga_ls8c_ard_3-2-1_099076_2023-10-07_final
2023-10-09 10:04:06	ga_ls8c_ard_3-2-1_097085_2023-10-09_final
2023-10-10 10:40:59	ga_ls8c_ard_3-2-1_104069_2023-10-10_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-13 11:15:53	ga_ls8c_ard_3-2-1_109079_2023-10-13_final
2023-10-17 10:50:21	ga_ls8c_ard_3-2-1_105077_2023-10-17_final
2023-10-17 10:51:33	ga_ls8c_ard_3-2-1_105080_2023-10-17_final
2023-10-19 10:37:35	ga_ls8c_ard_3-2-1_103076_2023-10-19_final
2023-10-22 09:30:01	ga_ls8c_ard_3-2-1_092077_2023-10-22_final
2023-10-22 09:30:25	ga_ls8c_ard_3-2-1_092078_2023-10-22_final
2023-10-22 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-10-22_final
2023-10-22 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-23 11:50:59	ga_ls8c_ard_3-2-1_115074_2023-10-23_final
2023-10-24 10:53:22	ga_ls8c_ard_3-2-1_106069_2023-10-24_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-27 11:26:42	ga_ls8c_ard_3-2-1_111075_2023-10-27_final
2023-10-28 10:32:40	ga_ls8c_ard_3-2-1_102079_2023-10-28_final
2023-10-29 11:12:21	ga_ls8c_ard_3-2-1_109070_2023-10-29_final
2023-11-01 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-11-01_final
2023-11-02 09:11:32	ga_ls8c_ard_3-2-1_089077_2023-11-01_final
2023-11-02 09:13:56	ga_ls8c_ard_3-2-1_089083_2023-11-01_final
2023-11-02 10:48:01	ga_ls8c_ard_3-2-1_105071_2023-11-02_final
2023-11-03 11:34:52	ga_ls8c_ard_3-2-1_112080_2023-11-03_final
2023-11-05 11:19:18	ga_ls8c_ard_3-2-1_110072_2023-11-05_final
2023-11-06 10:26:28	ga_ls8c_ard_3-2-1_101079_2023-11-06_final
2023-11-09 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-11-09_final
2023-11-09 10:58:30	ga_ls8c_ard_3-2-1_106082_2023-11-09_final
2023-11-10 09:57:17	ga_ls8c_ard_3-2-1_097068_2023-11-10_final
2023-11-11 10:40:34	ga_ls8c_ard_3-2-1_104068_2023-11-11_final
2023-11-12 11:26:38	ga_ls8c_ard_3-2-1_111075_2023-11-12_final
2023-11-12 11:27:50	ga_ls8c_ard_3-2-1_111078_2023-11-12_final
2023-11-12 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-11-12_final
2023-11-13 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-11-13_final
2023-11-17 10:05:09	ga_ls8c_ard_3-2-1_098072_2023-11-17_final
2023-11-17 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-17_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