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
2022-03-23 11:22:32	ga_ls8c_ard_3-2-1_110081_2022-03-23_final
2022-04-17 09:36:16	ga_ls8c_ard_3-2-1_093078_2022-04-17_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-05-13 11:51:31	ga_ls8c_ard_3-2-1_115076_2022-05-13_final
2022-05-23 10:46:09	ga_ls8c_ard_3-2-1_105067_2022-05-23_final
2022-06-10 10:37:10	ga_ls8c_ard_3-2-1_103075_2022-06-10_final
2022-06-10 10:37:57	ga_ls8c_ard_3-2-1_103077_2022-06-10_final
2022-06-22 09:24:42	ga_ls8c_ard_3-2-1_091079_2022-06-21_final
2022-07-12 10:38:04	ga_ls8c_ard_3-2-1_103077_2022-07-12_final
2022-07-12 10:38:52	ga_ls8c_ard_3-2-1_103079_2022-07-12_final
2022-07-17 10:55:25	ga_ls8c_ard_3-2-1_106074_2022-07-17_final
2022-07-17 10:57:49	ga_ls8c_ard_3-2-1_106080_2022-07-17_final
2022-07-24 09:24:25	ga_ls8c_ard_3-2-1_091078_2022-07-23_final
2022-07-31 11:06:46	ga_ls8c_ard_3-2-1_108071_2022-07-31_final
2022-08-02 10:55:37	ga_ls8c_ard_3-2-1_106074_2022-08-02_final
2022-08-04 10:41:41	ga_ls8c_ard_3-2-1_104070_2022-08-04_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-14 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-08-14_final
2022-08-19 10:02:05	ga_ls8c_ard_3-2-1_097079_2022-08-19_final
2022-08-21 09:51:20	ga_ls8c_ard_3-2-1_095083_2022-08-21_final
2022-08-30 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-08-30_final
2022-09-10 09:22:17	ga_ls8c_ard_3-2-1_091072_2022-09-09_final
2022-09-19 10:55:50	ga_ls8c_ard_3-2-1_106074_2022-09-19_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-26 11:02:49	ga_ls8c_ard_3-2-1_107076_2022-09-26_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-09-28 09:13:10	ga_ls8c_ard_3-2-1_089080_2022-09-27_final
2022-10-04 10:12:32	ga_ls8c_ard_3-2-1_099074_2022-10-04_final
2022-10-04 11:51:25	ga_ls8c_ard_3-2-1_115074_2022-10-04_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-20 10:12:30	ga_ls8c_ard_3-2-1_099074_2022-10-20_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-11-19 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-11-19_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-15 11:17:11	ga_ls8c_ard_3-2-1_109082_2023-02-15_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-06 11:45:02	ga_ls8c_ard_3-2-1_114075_2023-03-06_final
2023-03-21 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-03-21_final
2023-03-31 11:37:26	ga_ls8c_ard_3-2-1_113072_2023-03-31_final
2023-04-04 09:39:21	ga_ls8c_ard_3-2-1_093086_2023-04-04_final
2023-04-08 09:13:21	ga_ls8c_ard_3-2-1_089083_2023-04-07_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-25 09:57:17	ga_ls8c_ard_3-2-1_096085_2023-04-25_final
2023-05-01 10:55:27	ga_ls8c_ard_3-2-1_106076_2023-05-01_final
2023-05-13 11:18:00	ga_ls8c_ard_3-2-1_110071_2023-05-13_final
2023-05-15 11:05:13	ga_ls8c_ard_3-2-1_108070_2023-05-15_final
2023-05-29 09:40:20	ga_ls8c_ard_3-2-1_094074_2023-05-29_final
2023-06-05 09:46:33	ga_ls8c_ard_3-2-1_095074_2023-06-05_final
2023-06-08 10:21:06	ga_ls8c_ard_3-2-1_100083_2023-06-08_final
2023-06-18 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-06-18_final
2023-06-20 10:40:42	ga_ls8c_ard_3-2-1_104070_2023-06-20_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-21 10:03:15	ga_ls8c_ard_3-2-1_097084_2023-07-21_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-25 09:37:24	ga_ls8c_ard_3-2-1_093081_2023-07-25_final
2023-07-27 09:24:40	ga_ls8c_ard_3-2-1_091080_2023-07-26_final
2023-07-27 09:25:52	ga_ls8c_ard_3-2-1_091083_2023-07-26_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-07-31 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-07-31_final
2023-08-03 09:32:30	ga_ls8c_ard_3-2-1_092084_2023-08-03_final
2023-08-03 11:07:24	ga_ls8c_ard_3-2-1_108074_2023-08-03_final
2023-08-10 09:39:53	ga_ls8c_ard_3-2-1_093087_2023-08-10_final
2023-08-15 11:35:22	ga_ls8c_ard_3-2-1_112082_2023-08-15_final
2023-08-19 11:07:30	ga_ls8c_ard_3-2-1_108074_2023-08-19_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-02 09:39:49	ga_ls8c_ard_3-2-1_094071_2023-09-02_final
2023-09-04 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-09-03_final
2023-09-13 09:27:19	ga_ls8c_ard_3-2-1_091086_2023-09-12_final
2023-09-14 11:45:04	ga_ls8c_ard_3-2-1_114075_2023-09-14_final
2023-09-18 09:45:29	ga_ls8c_ard_3-2-1_094085_2023-09-18_final
2023-09-18 11:20:22	ga_ls8c_ard_3-2-1_110075_2023-09-18_final
2023-09-23 10:00:26	ga_ls8c_ard_3-2-1_097076_2023-09-23_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-26 10:29:46	ga_ls8c_ard_3-2-1_102072_2023-09-26_final
2023-09-27 09:39:21	ga_ls8c_ard_3-2-1_093085_2023-09-27_final
2023-09-30 10:09:27	ga_ls8c_ard_3-2-1_098083_2023-09-30_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-16 10:08:18	ga_ls8c_ard_3-2-1_098080_2023-10-16_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-22 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-10-22_final
2023-11-05 09:42:01	ga_ls8c_ard_3-2-1_094076_2023-11-05_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-12 09:47:21	ga_ls8c_ard_3-2-1_095074_2023-11-12_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