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
2023-09-04 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-09-04_final
2023-09-04 09:35:02	ga_ls8c_ard_3-2-1_092090_2023-09-04_final
2023-09-04 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-09-04_final
2023-09-04 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-09-04_final
2023-09-06 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-09-05_final
2023-09-06 09:19:03	ga_ls8c_ard_3-2-1_090081_2023-09-05_final
2023-09-06 10:58:20	ga_ls8c_ard_3-2-1_106082_2023-09-06_final
2023-09-06 10:58:44	ga_ls8c_ard_3-2-1_106083_2023-09-06_final
2023-09-08 10:45:36	ga_ls8c_ard_3-2-1_104081_2023-09-08_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 11:12:57	ga_ls8c_ard_3-2-1_109072_2023-09-11_final
2023-09-11 11:15:44	ga_ls8c_ard_3-2-1_109079_2023-09-11_final
2023-09-20 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-09-20_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-24 10:40:31	ga_ls8c_ard_3-2-1_104068_2023-09-24_final
2023-09-25 11:29:46	ga_ls8c_ard_3-2-1_111083_2023-09-25_final
2023-09-26 10:31:46	ga_ls8c_ard_3-2-1_102077_2023-09-26_final
2023-09-27 09:38:57	ga_ls8c_ard_3-2-1_093084_2023-09-27_final
2023-09-27 11:12:38	ga_ls8c_ard_3-2-1_109071_2023-09-27_final
2023-09-27 11:13:50	ga_ls8c_ard_3-2-1_109074_2023-09-27_final
2023-09-27 11:15:02	ga_ls8c_ard_3-2-1_109077_2023-09-27_final
2023-09-27 11:15:26	ga_ls8c_ard_3-2-1_109078_2023-09-27_final
2023-09-27 11:15:50	ga_ls8c_ard_3-2-1_109079_2023-09-27_final
2023-09-29 09:25:00	ga_ls8c_ard_3-2-1_091080_2023-09-28_final
2023-09-29 09:28:11	ga_ls8c_ard_3-2-1_091088_2023-09-28_final
2023-09-29 11:01:53	ga_ls8c_ard_3-2-1_107075_2023-09-29_final
2023-09-30 11:46:21	ga_ls8c_ard_3-2-1_114078_2023-09-30_final
2023-10-01 09:12:38	ga_ls8c_ard_3-2-1_089080_2023-09-30_final
2023-10-03 10:37:34	ga_ls8c_ard_3-2-1_103076_2023-10-03_final
2023-10-03 10:39:57	ga_ls8c_ard_3-2-1_103082_2023-10-03_final
2023-10-04 11:21:37	ga_ls8c_ard_3-2-1_110078_2023-10-04_final
2023-10-04 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-10-04_final
2023-10-05 10:25:12	ga_ls8c_ard_3-2-1_101076_2023-10-05_final
2023-10-06 11:08:27	ga_ls8c_ard_3-2-1_108076_2023-10-06_final
2023-10-06 11:10:03	ga_ls8c_ard_3-2-1_108080_2023-10-06_final
2023-10-07 10:12:51	ga_ls8c_ard_3-2-1_099076_2023-10-07_final
2023-10-07 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-10-07_final
2023-10-08 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-10-07_final
2023-10-09 10:02:30	ga_ls8c_ard_3-2-1_097081_2023-10-09_final
2023-10-09 10:04:06	ga_ls8c_ard_3-2-1_097085_2023-10-09_final
2023-10-11 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-10-11_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-13 09:39:00	ga_ls8c_ard_3-2-1_093084_2023-10-13_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-13 11:15:29	ga_ls8c_ard_3-2-1_109078_2023-10-13_final
2023-10-14 10:21:52	ga_ls8c_ard_3-2-1_100083_2023-10-14_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-16 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-10-16_final
2023-10-16 11:46:23	ga_ls8c_ard_3-2-1_114078_2023-10-16_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-20 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-10-20_final
2023-10-20 11:22:50	ga_ls8c_ard_3-2-1_110081_2023-10-20_final
2023-10-21 10:25:14	ga_ls8c_ard_3-2-1_101076_2023-10-21_final
2023-10-22 09:30:25	ga_ls8c_ard_3-2-1_092078_2023-10-22_final
2023-10-22 09:30:49	ga_ls8c_ard_3-2-1_092079_2023-10-22_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-22 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-10-22_final
2023-10-23 10:12:54	ga_ls8c_ard_3-2-1_099076_2023-10-23_final
2023-10-24 09:18:53	ga_ls8c_ard_3-2-1_090080_2023-10-23_final
2023-10-25 10:02:33	ga_ls8c_ard_3-2-1_097081_2023-10-25_final
2023-10-25 11:39:02	ga_ls8c_ard_3-2-1_113075_2023-10-25_final
2023-10-26 10:40:38	ga_ls8c_ard_3-2-1_104068_2023-10-26_final
2023-10-26 10:45:25	ga_ls8c_ard_3-2-1_104080_2023-10-26_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-10-28 10:31:52	ga_ls8c_ard_3-2-1_102077_2023-10-28_final
2023-10-29 11:12:21	ga_ls8c_ard_3-2-1_109070_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-29 11:15:08	ga_ls8c_ard_3-2-1_109077_2023-10-29_final
2023-10-31 09:24:18	ga_ls8c_ard_3-2-1_091078_2023-10-30_final
2023-10-31 09:24:42	ga_ls8c_ard_3-2-1_091079_2023-10-30_final
2023-11-03 11:34:04	ga_ls8c_ard_3-2-1_112078_2023-11-03_final
2023-11-03 11:34:28	ga_ls8c_ard_3-2-1_112079_2023-11-03_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-05 11:22:54	ga_ls8c_ard_3-2-1_110081_2023-11-05_final
2023-11-05 11:23:18	ga_ls8c_ard_3-2-1_110082_2023-11-05_final
2023-11-06 10:25:40	ga_ls8c_ard_3-2-1_101077_2023-11-06_final
2023-11-07 09:30:26	ga_ls8c_ard_3-2-1_092078_2023-11-07_final
2023-11-07 11:08:31	ga_ls8c_ard_3-2-1_108076_2023-11-07_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-08 10:12:52	ga_ls8c_ard_3-2-1_099076_2023-11-08_final
2023-11-10 11:38:58	ga_ls8c_ard_3-2-1_113075_2023-11-10_final
2023-11-11 10:40:34	ga_ls8c_ard_3-2-1_104068_2023-11-11_final
2023-11-12 11:28:14	ga_ls8c_ard_3-2-1_111079_2023-11-12_final
2023-11-12 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-11-12_final
2023-11-13 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-11-13_final
2023-11-13 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-11-13_final
2023-11-14 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-11-14_final
2023-11-14 11:15:06	ga_ls8c_ard_3-2-1_109077_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-15 10:17:30	ga_ls8c_ard_3-2-1_100072_2023-11-15_final
2023-11-18 10:46:50	ga_ls8c_ard_3-2-1_105068_2023-11-18_final
2023-11-18 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-18_final
2023-11-19 09:52:01	ga_ls8c_ard_3-2-1_096070_2023-11-19_final
2023-11-19 11:33:18	ga_ls8c_ard_3-2-1_112076_2023-11-19_final
2023-11-20 10:38:04	ga_ls8c_ard_3-2-1_103077_2023-11-20_final
2023-11-21 11:18:57	ga_ls8c_ard_3-2-1_110071_2023-11-21_final
2023-11-21 11:23:20	ga_ls8c_ard_3-2-1_110082_2023-11-21_final
2023-11-22 10:26:07	ga_ls8c_ard_3-2-1_101078_2023-11-22_final
2023-11-23 11:06:12	ga_ls8c_ard_3-2-1_108070_2023-11-23_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