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
2022-03-06 10:35:51	ga_ls8c_ard_3-2-1_103072_2022-03-06_final
2022-03-22 10:35:42	ga_ls8c_ard_3-2-1_103072_2022-03-22_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-26 11:07:19	ga_ls8c_ard_3-2-1_108074_2022-04-26_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-19 09:33:59	ga_ls8c_ard_3-2-1_093072_2022-05-19_final
2022-05-26 11:19:02	ga_ls8c_ard_3-2-1_110072_2022-05-26_final
2022-05-28 11:06:16	ga_ls8c_ard_3-2-1_108071_2022-05-28_final
2022-05-30 09:20:15	ga_ls8c_ard_3-2-1_090084_2022-05-29_final
2022-05-30 10:57:32	ga_ls8c_ard_3-2-1_106080_2022-05-30_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-24 09:16:44	ga_ls8c_ard_3-2-1_089090_2022-06-23_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-14 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-08-14_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-21 11:30:13	ga_ls8c_ard_3-2-1_111083_2022-08-21_final
2022-09-02 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-09-02_final
2022-09-05 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-09-04_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-15 11:18:32	ga_ls8c_ard_3-2-1_110069_2022-09-15_final
2022-09-17 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-09-17_final
2022-09-19 09:22:32	ga_ls8c_ard_3-2-1_090088_2022-09-18_final
2022-10-05 10:53:48	ga_ls8c_ard_3-2-1_106069_2022-10-05_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-11-06 10:56:37	ga_ls8c_ard_3-2-1_106076_2022-11-06_final
2022-11-13 11:00:45	ga_ls8c_ard_3-2-1_107071_2022-11-13_final
2022-11-15 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-11-15_final
2022-11-23 09:58:07	ga_ls8c_ard_3-2-1_097069_2022-11-23_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-12-02 11:32:50	ga_ls8c_ard_3-2-1_112074_2022-12-02_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-09 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-12-09_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2022-12-19 10:38:16	ga_ls8c_ard_3-2-1_103077_2022-12-19_final
2022-12-21 10:27:52	ga_ls8c_ard_3-2-1_101082_2022-12-21_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-23 11:51:59	ga_ls8c_ard_3-2-1_115076_2022-12-23_final
2022-12-31 09:22:06	ga_ls8c_ard_3-2-1_091072_2022-12-30_final
2023-01-12 11:26:27	ga_ls8c_ard_3-2-1_111074_2023-01-12_final
2023-01-18 09:12:23	ga_ls8c_ard_3-2-1_089079_2023-01-17_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-18 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-02-18_final
2023-02-21 10:35:36	ga_ls8c_ard_3-2-1_103071_2023-02-21_final
2023-02-24 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-02-24_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-03-13 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-03-13_final
2023-03-14 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-03-14_final
2023-03-16 09:06:17	ga_ls8c_ard_3-2-1_088080_2023-03-15_final
2023-03-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2023-03-17_final
2023-03-20 11:58:29	ga_ls8c_ard_3-2-1_116078_2023-03-20_final
2023-03-24 09:52:01	ga_ls8c_ard_3-2-1_096071_2023-03-24_final
2023-03-31 10:03:20	ga_ls8c_ard_3-2-1_097084_2023-03-31_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-10 10:39:01	ga_ls8c_ard_3-2-1_103081_2023-04-10_final
2023-04-14 10:08:41	ga_ls8c_ard_3-2-1_099067_2023-04-14_final
2023-04-19 10:32:46	ga_ls8c_ard_3-2-1_102081_2023-04-19_final
2023-04-27 09:39:20	ga_ls8c_ard_3-2-1_094071_2023-04-27_final
2023-05-10 10:48:44	ga_ls8c_ard_3-2-1_105075_2023-05-10_final
2023-05-18 11:41:18	ga_ls8c_ard_3-2-1_113083_2023-05-18_final
2023-05-19 09:06:24	ga_ls8c_ard_3-2-1_088082_2023-05-18_final
2023-05-24 09:21:47	ga_ls8c_ard_3-2-1_091074_2023-05-23_final
2023-05-26 10:48:19	ga_ls8c_ard_3-2-1_105074_2023-05-26_final
2023-05-27 11:30:47	ga_ls8c_ard_3-2-1_112072_2023-05-27_final
2023-06-02 09:21:12	ga_ls8c_ard_3-2-1_090088_2023-06-01_final
2023-06-04 10:45:21	ga_ls8c_ard_3-2-1_104082_2023-06-04_final
2023-06-09 09:22:17	ga_ls8c_ard_3-2-1_091075_2023-06-08_final
2023-06-09 09:27:29	ga_ls8c_ard_3-2-1_091088_2023-06-08_final
2023-06-13 10:38:53	ga_ls8c_ard_3-2-1_103081_2023-06-13_final
2023-06-16 11:06:36	ga_ls8c_ard_3-2-1_108073_2023-06-16_final
2023-06-16 11:07:00	ga_ls8c_ard_3-2-1_108074_2023-06-16_final
2023-06-19 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-06-19_final
2023-06-21 11:28:45	ga_ls8c_ard_3-2-1_111082_2023-06-21_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-06-25 09:21:59	ga_ls8c_ard_3-2-1_091074_2023-06-24_final
2023-06-25 11:04:28	ga_ls8c_ard_3-2-1_107083_2023-06-25_final
2023-06-27 09:10:52	ga_ls8c_ard_3-2-1_089077_2023-06-26_final
2023-07-03 10:08:46	ga_ls8c_ard_3-2-1_099067_2023-07-03_final
2023-07-05 09:59:13	ga_ls8c_ard_3-2-1_097074_2023-07-05_final
2023-07-05 10:01:13	ga_ls8c_ard_3-2-1_097079_2023-07-05_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-11 09:27:46	ga_ls8c_ard_3-2-1_091088_2023-07-10_final
2023-07-18 09:33:33	ga_ls8c_ard_3-2-1_092087_2023-07-18_final
2023-07-19 11:52:30	ga_ls8c_ard_3-2-1_115079_2023-07-19_final
2023-07-24 10:29:49	ga_ls8c_ard_3-2-1_102073_2023-07-24_final
2023-07-29 09:16:19	ga_ls8c_ard_3-2-1_089090_2023-07-28_final
2023-08-03 09:32:54	ga_ls8c_ard_3-2-1_092085_2023-08-03_final
2023-08-23 09:06:19	ga_ls8c_ard_3-2-1_088080_2023-08-22_final
2023-08-24 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-08-24_final
2023-08-28 09:22:53	ga_ls8c_ard_3-2-1_091075_2023-08-27_final
2023-09-04 09:28:38	ga_ls8c_ard_3-2-1_092074_2023-09-03_final
2023-09-09 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-09-09_final
2023-09-14 11:46:40	ga_ls8c_ard_3-2-1_114079_2023-09-14_final
2023-09-20 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-09-20_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