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
2022-05-31 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-05-31_final
2022-05-31 10:01:32	ga_ls8c_ard_3-2-1_097079_2022-05-31_final
2022-06-01 09:06:20	ga_ls8c_ard_3-2-1_088080_2022-05-31_final
2022-06-04 09:36:04	ga_ls8c_ard_3-2-1_093077_2022-06-04_final
2022-06-04 11:12:10	ga_ls8c_ard_3-2-1_109070_2022-06-04_final
2022-06-06 09:27:20	ga_ls8c_ard_3-2-1_091086_2022-06-05_final
2022-06-13 11:11:41	ga_ls8c_ard_3-2-1_108084_2022-06-13_final
2022-06-15 09:18:28	ga_ls8c_ard_3-2-1_090079_2022-06-14_final
2022-06-16 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-06-16_final
2022-06-18 11:24:17	ga_ls8c_ard_3-2-1_111069_2022-06-18_final
2022-06-20 11:12:20	ga_ls8c_ard_3-2-1_109070_2022-06-20_final
2022-06-23 11:46:03	ga_ls8c_ard_3-2-1_114077_2022-06-23_final
2022-06-24 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-06-23_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-04 09:48:15	ga_ls8c_ard_3-2-1_095076_2022-07-04_final
2022-07-08 09:25:07	ga_ls8c_ard_3-2-1_091080_2022-07-07_final
2022-07-10 09:13:33	ga_ls8c_ard_3-2-1_089082_2022-07-09_final
2022-07-16 11:52:37	ga_ls8c_ard_3-2-1_115078_2022-07-16_final
2022-07-24 09:25:13	ga_ls8c_ard_3-2-1_091080_2022-07-23_final
2022-07-26 09:12:05	ga_ls8c_ard_3-2-1_089078_2022-07-25_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-08-04 09:07:35	ga_ls8c_ard_3-2-1_088082_2022-08-03_final
2022-08-09 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-08-08_final
2022-08-18 09:19:37	ga_ls8c_ard_3-2-1_090081_2022-08-17_final
2022-08-24 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-08-24_final
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-09-01 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-09-01_final
2022-09-04 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-09-04_final
2022-09-18 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-09-18_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-20 09:57:49	ga_ls8c_ard_3-2-1_097068_2022-09-20_final
2022-09-24 09:35:53	ga_ls8c_ard_3-2-1_093075_2022-09-24_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-25 10:19:33	ga_ls8c_ard_3-2-1_100076_2022-09-25_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-10-03 11:06:34	ga_ls8c_ard_3-2-1_108070_2022-10-03_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-12 09:25:47	ga_ls8c_ard_3-2-1_091081_2022-10-11_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-20 11:52:34	ga_ls8c_ard_3-2-1_115077_2022-10-20_final
2022-10-26 11:18:20	ga_ls8c_ard_3-2-1_109084_2022-10-26_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-30 09:12:21	ga_ls8c_ard_3-2-1_089078_2022-10-29_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-05 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-11-05_final
2022-11-15 09:13:52	ga_ls8c_ard_3-2-1_089082_2022-11-14_final
2022-11-19 10:26:00	ga_ls8c_ard_3-2-1_101077_2022-11-19_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-23 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-11-23_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_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
2022-12-04 11:18:28	ga_ls8c_ard_3-2-1_110069_2022-12-04_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-07 11:53:45	ga_ls8c_ard_3-2-1_115080_2022-12-07_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-13 09:34:09	ga_ls8c_ard_3-2-1_093071_2022-12-13_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-16 10:05:01	ga_ls8c_ard_3-2-1_098071_2022-12-16_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-12 09:47:10	ga_ls8c_ard_3-2-1_095073_2023-01-12_final
2023-01-15 10:20:01	ga_ls8c_ard_3-2-1_100078_2023-01-15_final
2023-01-17 10:07:13	ga_ls8c_ard_3-2-1_098077_2023-01-17_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-18 10:48:29	ga_ls8c_ard_3-2-1_105072_2023-01-18_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-18 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-02-18_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-25 11:52:03	ga_ls8c_ard_3-2-1_115077_2023-02-25_final
2023-02-26 09:22:44	ga_ls8c_ard_3-2-1_090090_2023-02-25_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-07 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-03-06_final
2023-03-10 11:18:41	ga_ls8c_ard_3-2-1_110071_2023-03-10_final
2023-03-13 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-03-13_final
2023-03-13 11:52:47	ga_ls8c_ard_3-2-1_115079_2023-03-13_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-14 09:22:15	ga_ls8c_ard_3-2-1_090089_2023-03-13_final
2023-03-15 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-03-15_final
2023-03-16 09:07:05	ga_ls8c_ard_3-2-1_088082_2023-03-15_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-04-06 09:24:57	ga_ls8c_ard_3-2-1_091081_2023-04-05_final
2023-04-07 10:04:36	ga_ls8c_ard_3-2-1_098072_2023-04-07_final
2023-04-07 11:45:29	ga_ls8c_ard_3-2-1_114077_2023-04-07_final
2023-04-07 11:45:53	ga_ls8c_ard_3-2-1_114078_2023-04-07_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-11 09:39:23	ga_ls8c_ard_3-2-1_094071_2023-04-11_final
2023-04-12 10:25:02	ga_ls8c_ard_3-2-1_101077_2023-04-12_final
2023-04-13 09:33:48	ga_ls8c_ard_3-2-1_092088_2023-04-13_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-05-01 09:17:22	ga_ls8c_ard_3-2-1_090078_2023-04-30_final
2023-05-03 10:41:53	ga_ls8c_ard_3-2-1_104073_2023-05-03_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-16 11:50:52	ga_ls8c_ard_3-2-1_115076_2023-05-16_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