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
2022-03-04 10:48:13	ga_ls8c_ard_3-2-1_105072_2022-03-04_final
2022-03-08 10:23:52	ga_ls8c_ard_3-2-1_101073_2022-03-08_final
2022-03-31 10:30:12	ga_ls8c_ard_3-2-1_102074_2022-03-31_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-20 11:45:39	ga_ls8c_ard_3-2-1_114077_2022-04-20_final
2022-05-03 11:12:44	ga_ls8c_ard_3-2-1_109072_2022-05-03_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-17 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-17_final
2022-07-24 09:26:01	ga_ls8c_ard_3-2-1_091082_2022-07-23_final
2022-07-27 09:52:33	ga_ls8c_ard_3-2-1_096071_2022-07-27_final
2022-07-31 11:05:58	ga_ls8c_ard_3-2-1_108069_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-05 11:28:32	ga_ls8c_ard_3-2-1_111079_2022-08-05_final
2022-08-07 11:13:48	ga_ls8c_ard_3-2-1_109073_2022-08-07_final
2022-08-09 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-08-08_final
2022-08-14 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-08-14_final
2022-08-16 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-08-16_final
2022-08-17 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-08-17_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_final
2022-09-02 10:15:14	ga_ls8c_ard_3-2-1_099081_2022-09-02_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-20 10:01:00	ga_ls8c_ard_3-2-1_097076_2022-09-20_final
2022-09-29 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-09-29_final
2022-10-02 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-10-02_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-15 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-10-15_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-12 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-11-12_final
2022-11-27 11:13:53	ga_ls8c_ard_3-2-1_109073_2022-11-27_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-25 09:59:09	ga_ls8c_ard_3-2-1_097072_2022-12-25_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-02-13 09:47:53	ga_ls8c_ard_3-2-1_095075_2023-02-13_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-15 11:15:11	ga_ls8c_ard_3-2-1_109077_2023-02-15_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-22 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-02-22_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-21 09:27:57	ga_ls8c_ard_3-2-1_091088_2023-03-20_final
2023-03-30 10:56:11	ga_ls8c_ard_3-2-1_106077_2023-03-30_final
2023-03-31 11:38:38	ga_ls8c_ard_3-2-1_113075_2023-03-31_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-02 09:48:09	ga_ls8c_ard_3-2-1_095077_2023-04-02_final
2023-04-09 09:52:11	ga_ls8c_ard_3-2-1_096072_2023-04-09_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-28 10:22:11	ga_ls8c_ard_3-2-1_101070_2023-04-28_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-13 11:20:48	ga_ls8c_ard_3-2-1_110078_2023-05-13_final
2023-05-18 10:00:25	ga_ls8c_ard_3-2-1_097078_2023-05-18_final
2023-05-26 10:47:55	ga_ls8c_ard_3-2-1_105073_2023-05-26_final
2023-05-28 10:37:57	ga_ls8c_ard_3-2-1_103079_2023-05-28_final
2023-05-30 10:24:00	ga_ls8c_ard_3-2-1_101075_2023-05-30_final
2023-06-09 10:59:59	ga_ls8c_ard_3-2-1_107072_2023-06-09_final
2023-06-15 10:23:20	ga_ls8c_ard_3-2-1_101073_2023-06-15_final
2023-06-18 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-06-17_final
2023-06-19 10:00:14	ga_ls8c_ard_3-2-1_097077_2023-06-19_final
2023-06-28 11:34:13	ga_ls8c_ard_3-2-1_112080_2023-06-28_final
2023-07-26 10:20:41	ga_ls8c_ard_3-2-1_100081_2023-07-26_final
2023-07-27 11:00:45	ga_ls8c_ard_3-2-1_107073_2023-07-27_final
2023-08-04 10:11:47	ga_ls8c_ard_3-2-1_099074_2023-08-04_final
2023-08-12 09:23:09	ga_ls8c_ard_3-2-1_091076_2023-08-11_final
2023-08-12 11:00:26	ga_ls8c_ard_3-2-1_107072_2023-08-12_final
2023-08-12 11:03:14	ga_ls8c_ard_3-2-1_107079_2023-08-12_final
2023-08-15 11:34:35	ga_ls8c_ard_3-2-1_112080_2023-08-15_final
2023-08-22 09:58:45	ga_ls8c_ard_3-2-1_097072_2023-08-22_final
2023-09-07 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-09-07_final
2023-09-22 09:18:46	ga_ls8c_ard_3-2-1_090080_2023-09-21_final
2023-10-06 09:31:34	ga_ls8c_ard_3-2-1_092081_2023-10-06_final
2023-10-14 08:42:35	ga_ls8c_ard_3-2-1_084082_2023-10-13_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-23 11:52:11	ga_ls8c_ard_3-2-1_115077_2023-10-23_final
2023-11-01 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-11-01_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-04 10:36:51	ga_ls8c_ard_3-2-1_103074_2023-11-04_final
2023-11-09 10:58:54	ga_ls8c_ard_3-2-1_106083_2023-11-09_final
2023-11-16 09:25:28	ga_ls8c_ard_3-2-1_091081_2023-11-15_final
2023-11-19 11:34:53	ga_ls8c_ard_3-2-1_112080_2023-11-19_final
2023-11-29 10:31:53	ga_ls8c_ard_3-2-1_102077_2023-11-29_final
2023-12-03 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-12-03_final
2023-12-04 10:48:21	ga_ls8c_ard_3-2-1_105072_2023-12-04_final
2023-12-13 10:45:23	ga_ls8c_ard_3-2-1_104080_2023-12-13_final
2024-01-02 10:18:13	ga_ls8c_ard_3-2-1_100074_2024-01-02_final
2024-01-11 10:16:26	ga_ls8c_ard_3-2-1_099085_2024-01-11_final
2024-02-13 10:57:40	ga_ls8c_ard_3-2-1_106080_2024-02-13_final
2024-02-23 09:57:01	ga_ls8c_ard_3-2-1_096083_2024-02-23_final
2024-02-24 10:37:29	ga_ls8c_ard_3-2-1_103076_2024-02-24_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