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
2022-07-20 11:24:22	ga_ls8c_ard_3-2-1_111069_2022-07-20_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-27 11:32:38	ga_ls8c_ard_3-2-1_112074_2022-07-27_final
2022-08-24 10:20:14	ga_ls8c_ard_3-2-1_100078_2022-08-24_final
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-09-17 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-09-17_final
2022-09-18 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-09-18_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-11 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-10-11_final
2022-10-12 09:28:59	ga_ls8c_ard_3-2-1_091089_2022-10-11_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-10-15 11:36:46	ga_ls8c_ard_3-2-1_112084_2022-10-15_final
2022-10-16 10:39:58	ga_ls8c_ard_3-2-1_103081_2022-10-16_final
2022-10-19 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-10-19_final
2022-10-21 10:56:34	ga_ls8c_ard_3-2-1_106076_2022-10-21_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-27 10:22:19	ga_ls8c_ard_3-2-1_100083_2022-10-27_final
2022-10-28 11:00:24	ga_ls8c_ard_3-2-1_107070_2022-10-28_final
2022-10-28 11:02:48	ga_ls8c_ard_3-2-1_107076_2022-10-28_final
2022-10-30 09:11:57	ga_ls8c_ard_3-2-1_089077_2022-10-29_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-05 10:10:34	ga_ls8c_ard_3-2-1_099069_2022-11-05_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-15 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-11-15_final
2022-11-20 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-11-20_final
2022-11-21 10:16:27	ga_ls8c_ard_3-2-1_099084_2022-11-21_final
2022-11-23 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-11-23_final
2022-12-01 10:49:34	ga_ls8c_ard_3-2-1_105074_2022-12-01_final
2022-12-04 11:20:28	ga_ls8c_ard_3-2-1_110074_2022-12-04_final
2022-12-07 10:10:29	ga_ls8c_ard_3-2-1_099069_2022-12-07_final
2022-12-08 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-12-07_final
2022-12-09 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-12-09_final
2022-12-11 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-12-11_final
2022-12-22 11:09:55	ga_ls8c_ard_3-2-1_108079_2022-12-22_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2022-12-26 10:46:25	ga_ls8c_ard_3-2-1_104082_2022-12-26_final
2022-12-27 11:30:29	ga_ls8c_ard_3-2-1_111084_2022-12-27_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-25 09:17:04	ga_ls8c_ard_3-2-1_090075_2023-01-24_final
2023-01-31 10:22:29	ga_ls8c_ard_3-2-1_100084_2023-01-31_final
2023-02-17 09:21:55	ga_ls8c_ard_3-2-1_091072_2023-02-16_final
2023-02-20 09:52:45	ga_ls8c_ard_3-2-1_096072_2023-02-20_final
2023-02-25 10:13:58	ga_ls8c_ard_3-2-1_099079_2023-02-25_final
2023-03-12 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-03-12_final
2023-03-29 10:10:08	ga_ls8c_ard_3-2-1_099070_2023-03-29_final
2023-03-31 11:41:26	ga_ls8c_ard_3-2-1_113082_2023-03-31_final
2023-04-07 10:02:36	ga_ls8c_ard_3-2-1_098067_2023-04-07_final
2023-04-14 10:12:40	ga_ls8c_ard_3-2-1_099077_2023-04-14_final
2023-04-15 09:17:27	ga_ls8c_ard_3-2-1_090078_2023-04-14_final
2023-04-18 09:47:08	ga_ls8c_ard_3-2-1_095075_2023-04-18_final
2023-04-28 10:26:59	ga_ls8c_ard_3-2-1_101082_2023-04-28_final
2023-05-02 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-05-02_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-10 09:11:27	ga_ls8c_ard_3-2-1_089079_2023-05-09_final
2023-05-15 09:28:20	ga_ls8c_ard_3-2-1_092075_2023-05-14_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-16 10:15:11	ga_ls8c_ard_3-2-1_099084_2023-05-16_final
2023-05-18 11:37:42	ga_ls8c_ard_3-2-1_113074_2023-05-18_final
2023-05-31 11:10:27	ga_ls8c_ard_3-2-1_108083_2023-05-31_final
2023-06-07 11:17:06	ga_ls8c_ard_3-2-1_109084_2023-06-07_final
2023-06-12 09:57:37	ga_ls8c_ard_3-2-1_096086_2023-06-12_final
2023-06-18 09:16:10	ga_ls8c_ard_3-2-1_090075_2023-06-17_final
2023-07-02 09:33:04	ga_ls8c_ard_3-2-1_092086_2023-07-02_final
2023-07-05 09:56:49	ga_ls8c_ard_3-2-1_097068_2023-07-05_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-11 09:21:23	ga_ls8c_ard_3-2-1_091072_2023-07-10_final
2023-07-16 11:20:25	ga_ls8c_ard_3-2-1_110076_2023-07-16_final
2023-07-19 10:08:50	ga_ls8c_ard_3-2-1_099067_2023-07-19_final
2023-08-03 09:27:43	ga_ls8c_ard_3-2-1_092072_2023-08-02_final
2023-08-05 10:55:26	ga_ls8c_ard_3-2-1_106075_2023-08-05_final
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-14 09:11:13	ga_ls8c_ard_3-2-1_089077_2023-08-13_final
2023-08-14 10:49:18	ga_ls8c_ard_3-2-1_105075_2023-08-14_final
2023-08-21 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-08-21_final
2023-08-23 10:42:25	ga_ls8c_ard_3-2-1_104073_2023-08-23_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-04 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-09-04_final
2023-09-05 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-09-05_final
2023-09-05 10:13:05	ga_ls8c_ard_3-2-1_099077_2023-09-05_final
2023-09-07 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-09-07_final
2023-09-10 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-09-10_final
2023-09-13 09:22:55	ga_ls8c_ard_3-2-1_091075_2023-09-12_final
2023-09-21 10:10:00	ga_ls8c_ard_3-2-1_099069_2023-09-21_final
2023-09-21 10:15:59	ga_ls8c_ard_3-2-1_099084_2023-09-21_final
2023-09-23 11:38:31	ga_ls8c_ard_3-2-1_113074_2023-09-23_final
2023-10-10 09:07:17	ga_ls8c_ard_3-2-1_088082_2023-10-09_final
2023-10-20 11:18:03	ga_ls8c_ard_3-2-1_110069_2023-10-20_final
2023-10-23 10:10:06	ga_ls8c_ard_3-2-1_099069_2023-10-23_final
2023-10-25 09:57:22	ga_ls8c_ard_3-2-1_097068_2023-10-25_final
2023-10-30 10:21:55	ga_ls8c_ard_3-2-1_100083_2023-10-30_final
2023-11-08 10:10:05	ga_ls8c_ard_3-2-1_099069_2023-11-08_final
2023-11-09 10:55:43	ga_ls8c_ard_3-2-1_106075_2023-11-09_final
2023-11-11 09:06:52	ga_ls8c_ard_3-2-1_088081_2023-11-10_final
2023-11-16 09:21:53	ga_ls8c_ard_3-2-1_091072_2023-11-15_final
2023-11-17 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-17_final
2023-11-21 11:20:33	ga_ls8c_ard_3-2-1_110075_2023-11-21_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