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
2017-10-10 08:10:59	ga_ls8c_ard_3-2-1_079080_2017-10-09_final
2022-06-04 11:15:21	ga_ls8c_ard_3-2-1_109078_2022-06-04_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-15 09:19:40	ga_ls8c_ard_3-2-1_090082_2022-06-14_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-29 11:06:59	ga_ls8c_ard_3-2-1_108072_2022-06-29_final
2022-07-11 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-07-11_final
2022-08-12 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-08-12_final
2022-08-15 10:24:48	ga_ls8c_ard_3-2-1_101074_2022-08-15_final
2022-08-23 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-08-23_final
2022-08-23 11:15:51	ga_ls8c_ard_3-2-1_109078_2022-08-23_final
2022-08-25 11:05:54	ga_ls8c_ard_3-2-1_107084_2022-08-25_final
2022-08-27 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-08-27_final
2022-08-31 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-31_final
2022-09-01 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-09-01_final
2022-09-04 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-09-04_final
2022-09-09 11:57:59	ga_ls8c_ard_3-2-1_116075_2022-09-09_final
2022-09-11 11:47:38	ga_ls8c_ard_3-2-1_114080_2022-09-11_final
2022-09-25 10:19:09	ga_ls8c_ard_3-2-1_100075_2022-09-25_final
2022-10-03 09:30:29	ga_ls8c_ard_3-2-1_092077_2022-10-03_final
2022-10-06 11:40:14	ga_ls8c_ard_3-2-1_113077_2022-10-06_final
2022-10-09 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-10-09_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-23 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-23_final
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-29 11:48:03	ga_ls8c_ard_3-2-1_114081_2022-10-29_final
2022-11-18 11:22:01	ga_ls8c_ard_3-2-1_110078_2022-11-18_final
2022-12-16 10:06:13	ga_ls8c_ard_3-2-1_098074_2022-12-16_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2022-12-24 10:56:46	ga_ls8c_ard_3-2-1_106077_2022-12-24_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-12 09:51:57	ga_ls8c_ard_3-2-1_095085_2023-01-12_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-18 10:48:53	ga_ls8c_ard_3-2-1_105073_2023-01-18_final
2023-02-21 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-02-21_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-07 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-03-07_final
2023-03-13 10:12:42	ga_ls8c_ard_3-2-1_099076_2023-03-13_final
2023-03-16 10:43:10	ga_ls8c_ard_3-2-1_104075_2023-03-16_final
2023-03-21 11:05:14	ga_ls8c_ard_3-2-1_107084_2023-03-21_final
2023-03-22 11:45:41	ga_ls8c_ard_3-2-1_114077_2023-03-22_final
2023-04-15 10:56:44	ga_ls8c_ard_3-2-1_106079_2023-04-15_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-05-25 10:05:03	ga_ls8c_ard_3-2-1_098074_2023-05-25_final
2023-06-01 10:11:38	ga_ls8c_ard_3-2-1_099075_2023-06-01_final
2023-06-11 09:11:09	ga_ls8c_ard_3-2-1_089078_2023-06-10_final
2023-06-23 09:36:42	ga_ls8c_ard_3-2-1_093080_2023-06-23_final
2023-07-02 09:30:40	ga_ls8c_ard_3-2-1_092080_2023-07-02_final
2023-07-06 10:43:17	ga_ls8c_ard_3-2-1_104076_2023-07-06_final
2023-07-09 09:36:55	ga_ls8c_ard_3-2-1_093080_2023-07-09_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-07-13 10:49:54	ga_ls8c_ard_3-2-1_105077_2023-07-13_final
2023-07-20 09:19:35	ga_ls8c_ard_3-2-1_090083_2023-07-19_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-28 10:07:56	ga_ls8c_ard_3-2-1_098080_2023-07-28_final
2023-08-01 11:22:56	ga_ls8c_ard_3-2-1_110082_2023-08-01_final
2023-08-15 09:56:53	ga_ls8c_ard_3-2-1_096083_2023-08-15_final
2023-08-21 09:23:04	ga_ls8c_ard_3-2-1_090091_2023-08-20_final
2023-08-25 10:30:51	ga_ls8c_ard_3-2-1_102075_2023-08-25_final
2023-08-26 09:35:38	ga_ls8c_ard_3-2-1_093076_2023-08-26_final
2023-08-29 11:45:02	ga_ls8c_ard_3-2-1_114075_2023-08-29_final
2023-09-06 09:18:15	ga_ls8c_ard_3-2-1_090079_2023-09-05_final
2023-09-18 11:21:34	ga_ls8c_ard_3-2-1_110078_2023-09-18_final
2023-10-04 09:43:56	ga_ls8c_ard_3-2-1_094081_2023-10-04_final
2023-10-18 09:55:56	ga_ls8c_ard_3-2-1_096080_2023-10-18_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-27 09:49:48	ga_ls8c_ard_3-2-1_095080_2023-10-27_final
2023-10-30 11:58:24	ga_ls8c_ard_3-2-1_116077_2023-10-30_final
2023-11-13 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-11-13_final
2023-11-19 11:32:54	ga_ls8c_ard_3-2-1_112075_2023-11-19_final
2023-11-22 10:26:31	ga_ls8c_ard_3-2-1_101079_2023-11-22_final
2023-11-23 11:10:35	ga_ls8c_ard_3-2-1_108081_2023-11-23_final
2023-11-30 09:37:51	ga_ls8c_ard_3-2-1_093081_2023-11-30_final
2023-12-10 10:12:27	ga_ls8c_ard_3-2-1_099075_2023-12-10_final
2023-12-17 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-12-17_final
2023-12-18 11:04:22	ga_ls8c_ard_3-2-1_107081_2023-12-18_final
2023-12-29 10:44:35	ga_ls8c_ard_3-2-1_104078_2023-12-29_final
2023-12-30 09:49:21	ga_ls8c_ard_3-2-1_095079_2023-12-30_final
2024-01-01 11:15:03	ga_ls8c_ard_3-2-1_109077_2024-01-01_final
2024-01-10 11:10:27	ga_ls8c_ard_3-2-1_108081_2024-01-10_final
2024-01-12 10:57:18	ga_ls8c_ard_3-2-1_106079_2024-01-12_final
2024-01-19 11:03:28	ga_ls8c_ard_3-2-1_107079_2024-01-19_final
2024-01-26 11:11:32	ga_ls8c_ard_3-2-1_108084_2024-01-26_final
2024-02-06 10:51:30	ga_ls8c_ard_3-2-1_105080_2024-02-06_final
2024-02-07 09:55:53	ga_ls8c_ard_3-2-1_096080_2024-02-07_final
2024-02-10 10:23:59	ga_ls8c_ard_3-2-1_101073_2024-02-10_final
2024-03-06 11:58:04	ga_ls8c_ard_3-2-1_116077_2024-03-06_final
2024-03-12 09:44:04	ga_ls8c_ard_3-2-1_094082_2024-03-12_final
2024-03-17 11:41:27	ga_ls8c_ard_3-2-1_113082_2024-03-17_final
2024-03-19 09:46:59	ga_ls8c_ard_3-2-1_095074_2024-03-19_final
2024-03-20 10:29:26	ga_ls8c_ard_3-2-1_102072_2024-03-20_final
2024-03-21 11:15:28	ga_ls8c_ard_3-2-1_109079_2024-03-21_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years