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
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-23 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-08-23_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-25 11:01:54	ga_ls8c_ard_3-2-1_107074_2022-08-25_final
2022-08-27 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-08-27_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-09-01 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-09-01_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-07 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-09-07_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-10 11:01:58	ga_ls8c_ard_3-2-1_107074_2022-09-10_final
2022-09-12 10:46:49	ga_ls8c_ard_3-2-1_105067_2022-09-12_final
2022-09-15 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-09-15_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-19 10:55:26	ga_ls8c_ard_3-2-1_106073_2022-09-19_final
2022-09-21 10:41:29	ga_ls8c_ard_3-2-1_104069_2022-09-21_final
2022-09-21 10:46:40	ga_ls8c_ard_3-2-1_104082_2022-09-21_final
2022-09-22 09:47:51	ga_ls8c_ard_3-2-1_095074_2022-09-22_final
2022-09-22 11:25:56	ga_ls8c_ard_3-2-1_111072_2022-09-22_final
2022-09-24 09:35:29	ga_ls8c_ard_3-2-1_093074_2022-09-24_final
2022-09-24 09:37:53	ga_ls8c_ard_3-2-1_093080_2022-09-24_final
2022-09-24 11:13:35	ga_ls8c_ard_3-2-1_109072_2022-09-24_final
2022-09-26 11:02:25	ga_ls8c_ard_3-2-1_107075_2022-09-26_final
2022-10-01 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-10-01_final
2022-10-02 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-10-02_final
2022-10-02 10:27:18	ga_ls8c_ard_3-2-1_101080_2022-10-02_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-10-31 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-10-31_final
2022-11-01 10:35:18	ga_ls8c_ard_3-2-1_103069_2022-11-01_final
2022-11-11 11:13:55	ga_ls8c_ard_3-2-1_109073_2022-11-11_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-23 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-11-23_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-27 11:13:53	ga_ls8c_ard_3-2-1_109073_2022-11-27_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-01 10:52:46	ga_ls8c_ard_3-2-1_105082_2022-12-01_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-10 10:44:09	ga_ls8c_ard_3-2-1_104076_2022-12-10_final
2022-12-11 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-12-11_final
2022-12-12 10:29:23	ga_ls8c_ard_3-2-1_102070_2022-12-12_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-21 10:28:16	ga_ls8c_ard_3-2-1_101083_2022-12-21_final
2022-12-23 11:53:35	ga_ls8c_ard_3-2-1_115080_2022-12-23_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-01 11:46:14	ga_ls8c_ard_3-2-1_114077_2023-01-01_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-17 11:45:18	ga_ls8c_ard_3-2-1_114075_2023-01-17_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-15 11:13:35	ga_ls8c_ard_3-2-1_109073_2023-02-15_final
2023-02-18 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-02-18_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-24 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-02-24_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-12 11:05:56	ga_ls8c_ard_3-2-1_108070_2023-03-12_final
2023-03-14 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-03-14_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-26 09:44:50	ga_ls8c_ard_3-2-1_094084_2023-03-26_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-15 09:20:14	ga_ls8c_ard_3-2-1_090085_2023-04-14_final
2023-04-16 10:01:30	ga_ls8c_ard_3-2-1_097080_2023-04-16_final
2023-04-17 10:40:22	ga_ls8c_ard_3-2-1_104069_2023-04-17_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-05-02 11:40:42	ga_ls8c_ard_3-2-1_113081_2023-05-02_final
2023-05-10 09:09:27	ga_ls8c_ard_3-2-1_089074_2023-05-09_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-13 11:19:12	ga_ls8c_ard_3-2-1_110074_2023-05-13_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-18 09:58:01	ga_ls8c_ard_3-2-1_097072_2023-05-18_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