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
2022-10-01 09:43:39	ga_ls8c_ard_3-2-1_094079_2022-10-01_final
2022-10-01 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-10-01_final
2022-10-05 10:59:23	ga_ls8c_ard_3-2-1_106083_2022-10-05_final
2022-10-08 11:29:51	ga_ls8c_ard_3-2-1_111082_2022-10-08_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-10 11:15:52	ga_ls8c_ard_3-2-1_109078_2022-10-10_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-15 11:35:34	ga_ls8c_ard_3-2-1_112081_2022-10-15_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-19 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-10-19_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-22 10:00:57	ga_ls8c_ard_3-2-1_097076_2022-10-22_final
2022-10-23 10:44:37	ga_ls8c_ard_3-2-1_104077_2022-10-23_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-27 10:18:20	ga_ls8c_ard_3-2-1_100073_2022-10-27_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-11 09:37:02	ga_ls8c_ard_3-2-1_093078_2022-11-11_final
2022-11-12 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-11-12_final
2022-11-15 10:48:21	ga_ls8c_ard_3-2-1_105071_2022-11-15_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-19 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-11-19_final
2022-11-19 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-11-19_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-12-03 10:38:48	ga_ls8c_ard_3-2-1_103078_2022-12-03_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-20 11:21:55	ga_ls8c_ard_3-2-1_110078_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2022-12-25 10:01:33	ga_ls8c_ard_3-2-1_097078_2022-12-25_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-31 09:24:53	ga_ls8c_ard_3-2-1_091079_2022-12-30_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 11:22:43	ga_ls8c_ard_3-2-1_110080_2023-01-05_final
2023-01-05 11:23:07	ga_ls8c_ard_3-2-1_110081_2023-01-05_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-09 10:58:22	ga_ls8c_ard_3-2-1_106081_2023-01-09_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-30 11:15:42	ga_ls8c_ard_3-2-1_109078_2023-01-30_final
2023-02-05 10:35:49	ga_ls8c_ard_3-2-1_103071_2023-02-05_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-10 09:19:02	ga_ls8c_ard_3-2-1_090080_2023-02-09_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-15 09:39:54	ga_ls8c_ard_3-2-1_093086_2023-02-15_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-24 09:31:32	ga_ls8c_ard_3-2-1_092081_2023-02-24_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-04 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-03-04_final
2023-03-12 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-03-12_final
2023-03-12 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-03-12_final
2023-03-14 10:57:57	ga_ls8c_ard_3-2-1_106081_2023-03-14_final
2023-03-23 10:51:38	ga_ls8c_ard_3-2-1_105081_2023-03-23_final
2023-03-26 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-03-26_final
2023-03-29 10:14:32	ga_ls8c_ard_3-2-1_099081_2023-03-29_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 10:02:09	ga_ls8c_ard_3-2-1_097081_2023-03-31_final
2023-04-05 11:58:17	ga_ls8c_ard_3-2-1_116078_2023-04-05_final
2023-04-10 10:36:13	ga_ls8c_ard_3-2-1_103074_2023-04-10_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-15 10:57:32	ga_ls8c_ard_3-2-1_106081_2023-04-15_final
2023-04-18 11:29:12	ga_ls8c_ard_3-2-1_111083_2023-04-18_final
2023-04-30 11:50:17	ga_ls8c_ard_3-2-1_115074_2023-04-30_final
2023-05-04 11:28:19	ga_ls8c_ard_3-2-1_111081_2023-05-04_final
2023-05-05 10:29:05	ga_ls8c_ard_3-2-1_102072_2023-05-05_final
2023-05-08 09:23:03	ga_ls8c_ard_3-2-1_091077_2023-05-07_final
2023-05-09 11:44:47	ga_ls8c_ard_3-2-1_114076_2023-05-09_final
2023-05-11 09:52:18	ga_ls8c_ard_3-2-1_096073_2023-05-11_final
2023-05-11 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-11_final
2023-05-12 10:37:56	ga_ls8c_ard_3-2-1_103079_2023-05-12_final
2023-05-13 09:43:06	ga_ls8c_ard_3-2-1_094081_2023-05-13_final
2023-05-17 09:19:09	ga_ls8c_ard_3-2-1_090083_2023-05-16_final
2023-05-18 11:38:54	ga_ls8c_ard_3-2-1_113077_2023-05-18_final
2023-05-20 09:50:04	ga_ls8c_ard_3-2-1_095083_2023-05-20_final
2023-05-22 11:15:49	ga_ls8c_ard_3-2-1_109081_2023-05-22_final
2023-05-23 11:57:29	ga_ls8c_ard_3-2-1_116077_2023-05-23_final
2023-05-24 09:22:59	ga_ls8c_ard_3-2-1_091077_2023-05-23_final
2023-05-30 10:24:00	ga_ls8c_ard_3-2-1_101075_2023-05-30_nrt
2023-05-31 09:28:46	ga_ls8c_ard_3-2-1_092076_2023-05-30_nrt
2023-06-02 10:56:53	ga_ls8c_ard_3-2-1_106080_2023-06-02_nrt
2023-06-04 10:39:46	ga_ls8c_ard_3-2-1_104068_2023-06-04_nrt
2023-06-04 10:42:58	ga_ls8c_ard_3-2-1_104076_2023-06-04_nrt

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