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
2022-06-09 09:52:17	ga_ls8c_ard_3-2-1_096071_2022-06-09_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-25 11:35:17	ga_ls8c_ard_3-2-1_112081_2022-06-25_final
2022-06-27 11:23:44	ga_ls8c_ard_3-2-1_110083_2022-06-27_final
2022-07-06 09:36:17	ga_ls8c_ard_3-2-1_093077_2022-07-06_final
2022-07-11 11:33:18	ga_ls8c_ard_3-2-1_112076_2022-07-11_final
2022-07-19 10:44:41	ga_ls8c_ard_3-2-1_104078_2022-07-19_final
2022-07-24 09:25:37	ga_ls8c_ard_3-2-1_091081_2022-07-23_final
2022-08-09 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-08-09_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-15 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-08-15_final
2022-08-16 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-08-16_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-08-27 10:51:56	ga_ls8c_ard_3-2-1_105080_2022-08-27_final
2022-08-29 10:35:59	ga_ls8c_ard_3-2-1_103071_2022-08-29_final
2022-08-31 10:25:13	ga_ls8c_ard_3-2-1_101075_2022-08-31_final
2022-09-06 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-09-06_final
2022-09-07 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-09-07_final
2022-09-17 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-09-17_final
2022-09-19 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-09-18_final
2022-09-29 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-09-29_final
2022-09-30 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-09-30_final
2022-10-17 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-10-17_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-26 09:36:16	ga_ls8c_ard_3-2-1_093076_2022-10-26_final
2022-10-28 09:25:06	ga_ls8c_ard_3-2-1_091079_2022-10-27_final
2022-10-31 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-10-31_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-30 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-30_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-11 09:50:31	ga_ls8c_ard_3-2-1_095081_2022-12-11_final
2022-12-15 09:26:10	ga_ls8c_ard_3-2-1_091082_2022-12-14_final
2022-12-18 09:56:37	ga_ls8c_ard_3-2-1_096081_2022-12-18_final
2022-12-18 11:35:54	ga_ls8c_ard_3-2-1_112082_2022-12-18_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-21 11:22:37	ga_ls8c_ard_3-2-1_110080_2023-01-21_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-22 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-02-22_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-14 10:56:45	ga_ls8c_ard_3-2-1_106078_2023-03-14_final
2023-03-19 09:37:57	ga_ls8c_ard_3-2-1_093082_2023-03-19_final
2023-03-20 11:57:41	ga_ls8c_ard_3-2-1_116076_2023-03-20_final
2023-03-23 10:51:38	ga_ls8c_ard_3-2-1_105081_2023-03-23_final
2023-03-28 09:30:04	ga_ls8c_ard_3-2-1_092078_2023-03-28_final
2023-03-29 10:12:08	ga_ls8c_ard_3-2-1_099075_2023-03-29_final
2023-04-06 09:23:45	ga_ls8c_ard_3-2-1_091078_2023-04-05_final
2023-04-08 09:13:45	ga_ls8c_ard_3-2-1_089084_2023-04-07_final
2023-04-09 09:55:47	ga_ls8c_ard_3-2-1_096081_2023-04-09_final
2023-04-16 10:02:18	ga_ls8c_ard_3-2-1_097082_2023-04-16_final
2023-04-18 11:29:12	ga_ls8c_ard_3-2-1_111083_2023-04-18_final
2023-04-20 11:12:26	ga_ls8c_ard_3-2-1_109072_2023-04-20_final
2023-04-21 10:20:24	ga_ls8c_ard_3-2-1_100081_2023-04-21_final
2023-04-24 09:14:02	ga_ls8c_ard_3-2-1_089085_2023-04-23_final
2023-04-25 11:34:34	ga_ls8c_ard_3-2-1_112081_2023-04-25_final
2023-05-06 11:15:32	ga_ls8c_ard_3-2-1_109080_2023-05-06_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-13 09:42:42	ga_ls8c_ard_3-2-1_094080_2023-05-13_final
2023-05-15 11:10:01	ga_ls8c_ard_3-2-1_108082_2023-05-15_final
2023-05-18 09:59:37	ga_ls8c_ard_3-2-1_097076_2023-05-18_final
2023-05-21 10:30:57	ga_ls8c_ard_3-2-1_102077_2023-05-21_final
2023-05-22 11:12:13	ga_ls8c_ard_3-2-1_109072_2023-05-22_final
2023-05-26 09:14:13	ga_ls8c_ard_3-2-1_089086_2023-05-25_final
2023-05-27 09:52:18	ga_ls8c_ard_3-2-1_096073_2023-05-27_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_final
2023-05-28 10:37:33	ga_ls8c_ard_3-2-1_103078_2023-05-28_final
2023-06-10 10:05:34	ga_ls8c_ard_3-2-1_098075_2023-06-10_final
2023-06-11 10:50:50	ga_ls8c_ard_3-2-1_105080_2023-06-11_final
2023-06-16 11:06:13	ga_ls8c_ard_3-2-1_108072_2023-06-16_final
2023-06-19 10:01:49	ga_ls8c_ard_3-2-1_097081_2023-06-19_final
2023-06-20 10:45:05	ga_ls8c_ard_3-2-1_104081_2023-06-20_final
2023-06-26 10:05:40	ga_ls8c_ard_3-2-1_098075_2023-06-26_final
2023-07-02 11:09:10	ga_ls8c_ard_3-2-1_108079_2023-07-02_final
2023-07-09 11:15:00	ga_ls8c_ard_3-2-1_109078_2023-07-09_final
2023-07-18 09:32:21	ga_ls8c_ard_3-2-1_092084_2023-07-18_final
2023-07-28 10:08:44	ga_ls8c_ard_3-2-1_098082_2023-07-28_final
2023-08-04 11:52:39	ga_ls8c_ard_3-2-1_115079_2023-08-04_final
2023-08-16 10:34:35	ga_ls8c_ard_3-2-1_103069_2023-08-16_final
2023-08-25 10:32:51	ga_ls8c_ard_3-2-1_102080_2023-08-25_final
2023-08-26 11:16:07	ga_ls8c_ard_3-2-1_109080_2023-08-26_final
2023-08-26 11:16:55	ga_ls8c_ard_3-2-1_109082_2023-08-26_final
2023-09-06 10:57:08	ga_ls8c_ard_3-2-1_106079_2023-09-06_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years