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
2022-01-14 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-01-14_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-20 11:44:27	ga_ls8c_ard_3-2-1_114074_2022-04-20_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 11:10:55	ga_ls8c_ard_3-2-1_108083_2022-04-26_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-10 11:20:36	ga_ls8c_ard_3-2-1_110076_2022-05-10_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-05-18 10:28:25	ga_ls8c_ard_3-2-1_102069_2022-05-18_final
2022-05-19 11:17:16	ga_ls8c_ard_3-2-1_109083_2022-05-19_final
2022-05-21 09:26:25	ga_ls8c_ard_3-2-1_091084_2022-05-20_final
2022-05-21 11:04:54	ga_ls8c_ard_3-2-1_107083_2022-05-21_final
2022-05-23 10:46:33	ga_ls8c_ard_3-2-1_105068_2022-05-23_final
2022-05-28 09:29:23	ga_ls8c_ard_3-2-1_092076_2022-05-27_final
2022-05-28 11:07:04	ga_ls8c_ard_3-2-1_108073_2022-05-28_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-17 10:41:25	ga_ls8c_ard_3-2-1_104070_2022-06-17_final
2022-06-20 11:12:44	ga_ls8c_ard_3-2-1_109071_2022-06-20_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_final
2022-06-24 09:11:57	ga_ls8c_ard_3-2-1_089078_2022-06-23_final
2022-06-26 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-06-26_final
2022-07-02 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-02_final
2022-07-06 11:12:22	ga_ls8c_ard_3-2-1_109070_2022-07-06_final
2022-07-08 09:25:55	ga_ls8c_ard_3-2-1_091082_2022-07-07_final
2022-07-08 11:00:01	ga_ls8c_ard_3-2-1_107070_2022-07-08_final
2022-07-12 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-07-12_final
2022-07-12 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-07-12_final
2022-07-29 09:45:24	ga_ls8c_ard_3-2-1_094084_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-08-11 10:48:42	ga_ls8c_ard_3-2-1_105072_2022-08-11_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-08-30 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-08-30_final
2022-09-13 11:34:29	ga_ls8c_ard_3-2-1_112078_2022-09-13_final
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-17 09:34:29	ga_ls8c_ard_3-2-1_092087_2022-09-17_final
2022-09-24 09:35:53	ga_ls8c_ard_3-2-1_093075_2022-09-24_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-10-12 09:26:35	ga_ls8c_ard_3-2-1_091083_2022-10-11_final
2022-10-12 11:02:17	ga_ls8c_ard_3-2-1_107075_2022-10-12_final
2022-10-17 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-10-17_final
2022-10-19 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-10-19_final
2022-10-26 11:13:57	ga_ls8c_ard_3-2-1_109073_2022-10-26_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-11-04 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-11-04_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 10:51:58	ga_ls8c_ard_3-2-1_105080_2022-12-01_final
2022-12-14 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-12-14_final
2022-12-16 10:05:25	ga_ls8c_ard_3-2-1_098072_2022-12-16_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-23 10:15:53	ga_ls8c_ard_3-2-1_099083_2022-12-23_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-16 10:22:21	ga_ls8c_ard_3-2-1_100084_2023-02-16_final
2023-02-20 09:57:57	ga_ls8c_ard_3-2-1_096085_2023-02-20_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-10 09:40:36	ga_ls8c_ard_3-2-1_094073_2023-03-10_final
2023-03-11 10:25:51	ga_ls8c_ard_3-2-1_101078_2023-03-11_final
2023-03-14 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-03-14_final
2023-03-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2023-03-17_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-04-03 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-04-03_nrt
2023-04-04 09:35:22	ga_ls8c_ard_3-2-1_093076_2023-04-04_final
2023-04-07 10:07:24	ga_ls8c_ard_3-2-1_098079_2023-04-07_final
2023-04-08 09:16:08	ga_ls8c_ard_3-2-1_089090_2023-04-07_final
2023-04-15 09:19:51	ga_ls8c_ard_3-2-1_090084_2023-04-14_final
2023-04-16 09:59:06	ga_ls8c_ard_3-2-1_097074_2023-04-16_final
2023-04-18 09:47:08	ga_ls8c_ard_3-2-1_095075_2023-04-18_final
2023-04-20 09:34:21	ga_ls8c_ard_3-2-1_093074_2023-04-20_final
2023-04-20 09:39:08	ga_ls8c_ard_3-2-1_093086_2023-04-20_final
2023-04-29 11:05:03	ga_ls8c_ard_3-2-1_108069_2023-04-29_final
2023-05-02 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-05-02_final
2023-05-04 11:24:20	ga_ls8c_ard_3-2-1_111071_2023-05-04_final
2023-05-06 09:39:02	ga_ls8c_ard_3-2-1_093086_2023-05-06_final
2023-05-07 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-05-07_final
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-17 10:54:26	ga_ls8c_ard_3-2-1_106074_2023-05-17_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