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
2021-10-05 11:30:27	ga_ls8c_ard_3-2-0_111084_2021-10-05_final
2022-01-17 10:35:16	ga_ls8c_ard_3-2-1_103070_2022-01-17_final
2022-02-05 09:31:11	ga_ls8c_ard_3-2-1_092080_2022-02-05_final
2022-02-09 09:06:27	ga_ls8c_ard_3-2-1_088080_2022-02-08_final
2022-02-20 10:23:31	ga_ls8c_ard_3-2-1_101072_2022-02-20_final
2022-02-20 10:23:55	ga_ls8c_ard_3-2-1_101073_2022-02-20_final
2022-02-23 09:23:07	ga_ls8c_ard_3-2-1_090091_2022-02-22_final
2022-03-02 09:25:41	ga_ls8c_ard_3-2-1_091082_2022-03-01_final
2022-03-04 09:12:08	ga_ls8c_ard_3-2-1_089079_2022-03-03_final
2022-03-05 09:56:59	ga_ls8c_ard_3-2-1_096083_2022-03-05_final
2022-03-16 09:39:57	ga_ls8c_ard_3-2-1_093087_2022-03-16_final
2022-03-18 09:28:46	ga_ls8c_ard_3-2-1_091090_2022-03-17_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2022-05-17_final
2022-06-05 10:20:09	ga_ls8c_ard_3-2-1_100079_2022-06-05_final
2022-06-11 11:22:50	ga_ls8c_ard_3-2-1_110081_2022-06-11_final
2022-06-20 09:33:51	ga_ls8c_ard_3-2-1_093071_2022-06-20_final
2022-06-20 09:37:03	ga_ls8c_ard_3-2-1_093079_2022-06-20_final
2022-06-25 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-06-25_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-07-05 10:31:06	ga_ls8c_ard_3-2-1_102075_2022-07-05_final
2022-07-26 09:10:29	ga_ls8c_ard_3-2-1_089074_2022-07-25_final
2022-07-30 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-07-30_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-08-19 11:40:58	ga_ls8c_ard_3-2-1_113079_2022-08-19_final
2022-09-03 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-09-03_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-13 09:53:36	ga_ls8c_ard_3-2-1_096073_2022-09-13_final
2022-10-01 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-10-01_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-11-01 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-11-01_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-09 11:29:54	ga_ls8c_ard_3-2-1_111082_2022-11-09_final
2022-11-10 10:31:04	ga_ls8c_ard_3-2-1_102074_2022-11-10_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-27 11:30:05	ga_ls8c_ard_3-2-1_111083_2022-12-27_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-19 09:55:16	ga_ls8c_ard_3-2-1_096078_2023-01-19_final
2023-01-25 09:18:16	ga_ls8c_ard_3-2-1_090078_2023-01-24_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-03-06 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-03-06_final
2023-03-13 10:12:18	ga_ls8c_ard_3-2-1_099075_2023-03-13_final
2023-04-05 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-04-05_final
2023-04-08 10:49:50	ga_ls8c_ard_3-2-1_105077_2023-04-08_final
2023-04-13 11:09:06	ga_ls8c_ard_3-2-1_108079_2023-04-13_final
2023-04-28 10:22:59	ga_ls8c_ard_3-2-1_101072_2023-04-28_final
2023-05-04 09:47:02	ga_ls8c_ard_3-2-1_095075_2023-05-04_final
2023-05-09 10:07:30	ga_ls8c_ard_3-2-1_098080_2023-05-09_final
2023-05-10 09:12:15	ga_ls8c_ard_3-2-1_089081_2023-05-09_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_2023-05-13_final
2023-05-17 10:56:26	ga_ls8c_ard_3-2-1_106079_2023-05-17_final
2023-05-20 11:29:21	ga_ls8c_ard_3-2-1_111084_2023-05-20_final
2023-05-27 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-27_final
2023-06-03 11:40:34	ga_ls8c_ard_3-2-1_113081_2023-06-03_final
2023-06-12 09:52:25	ga_ls8c_ard_3-2-1_096073_2023-06-12_final
2023-06-25 11:02:04	ga_ls8c_ard_3-2-1_107077_2023-06-25_final
2023-06-27 09:12:04	ga_ls8c_ard_3-2-1_089080_2023-06-26_final
2023-07-06 10:40:05	ga_ls8c_ard_3-2-1_104068_2023-07-06_final
2023-07-11 09:25:46	ga_ls8c_ard_3-2-1_091083_2023-07-10_final
2023-07-18 09:29:34	ga_ls8c_ard_3-2-1_092077_2023-07-17_final
2023-07-19 11:51:18	ga_ls8c_ard_3-2-1_115076_2023-07-19_final
2023-07-21 10:01:39	ga_ls8c_ard_3-2-1_097080_2023-07-21_final
2023-07-31 10:36:05	ga_ls8c_ard_3-2-1_103073_2023-07-31_final
2023-08-16 10:36:10	ga_ls8c_ard_3-2-1_103073_2023-08-16_final
2023-08-28 11:04:10	ga_ls8c_ard_3-2-1_107081_2023-08-28_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-04 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-09-04_final
2023-09-27 11:11:50	ga_ls8c_ard_3-2-1_109069_2023-09-27_final
2023-09-30 10:08:16	ga_ls8c_ard_3-2-1_098080_2023-09-30_final
2023-10-01 10:50:20	ga_ls8c_ard_3-2-1_105077_2023-10-01_final
2023-10-14 10:17:52	ga_ls8c_ard_3-2-1_100073_2023-10-14_final
2023-10-17 09:16:40	ga_ls8c_ard_3-2-1_089090_2023-10-16_final
2023-11-07 11:06:07	ga_ls8c_ard_3-2-1_108070_2023-11-07_final
2023-11-08 11:51:45	ga_ls8c_ard_3-2-1_115076_2023-11-08_final
2023-11-20 10:36:29	ga_ls8c_ard_3-2-1_103073_2023-11-20_final
2023-11-26 09:59:49	ga_ls8c_ard_3-2-1_097074_2023-11-26_final
2023-12-09 09:27:59	ga_ls8c_ard_3-2-1_092072_2023-12-08_final
2023-12-09 11:05:40	ga_ls8c_ard_3-2-1_108069_2023-12-09_final
2023-12-12 10:03:18	ga_ls8c_ard_3-2-1_097083_2023-12-12_final
2023-12-16 09:37:50	ga_ls8c_ard_3-2-1_093081_2023-12-16_final
2023-12-28 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-12-28_final
2024-01-22 11:34:44	ga_ls8c_ard_3-2-1_112080_2024-01-22_final
2024-02-07 11:35:34	ga_ls8c_ard_3-2-1_112082_2024-02-07_final
2024-02-10 10:25:59	ga_ls8c_ard_3-2-1_101078_2024-02-10_final
2024-02-28 11:50:48	ga_ls8c_ard_3-2-1_115074_2024-02-28_final
2024-04-06 09:37:15	ga_ls8c_ard_3-2-1_093081_2024-04-06_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years