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
2015-04-14 09:35:49	ga_ls8c_ard_3-0-0_093078_2015-04-14_final
2015-04-14 09:36:13	ga_ls8c_ard_3-0-0_093079_2015-04-14_final
2015-04-14 09:36:37	ga_ls8c_ard_3-0-0_093080_2015-04-14_final
2015-04-14 09:37:01	ga_ls8c_ard_3-0-0_093081_2015-04-14_final
2015-04-14 09:37:25	ga_ls8c_ard_3-0-0_093082_2015-04-14_final
2015-04-14 09:37:49	ga_ls8c_ard_3-0-0_093083_2015-04-14_final
2015-04-16 09:26:39	ga_ls8c_ard_3-0-0_091086_2015-04-15_final
2015-04-16 09:27:03	ga_ls8c_ard_3-0-0_091087_2015-04-15_final
2015-04-16 09:27:27	ga_ls8c_ard_3-0-0_091088_2015-04-15_final
2015-04-16 09:27:51	ga_ls8c_ard_3-0-0_091089_2015-04-15_final
2015-04-16 09:28:15	ga_ls8c_ard_3-0-0_091090_2015-04-15_final
2015-04-16 09:28:39	ga_ls8c_ard_3-0-0_091091_2015-04-15_final
2015-05-16 09:35:27	ga_ls8c_ard_3-0-0_093078_2015-05-16_final
2015-05-16 09:35:51	ga_ls8c_ard_3-0-0_093079_2015-05-16_final
2015-05-16 09:36:15	ga_ls8c_ard_3-0-0_093080_2015-05-16_final
2015-05-16 09:36:39	ga_ls8c_ard_3-0-0_093081_2015-05-16_final
2015-05-16 09:37:03	ga_ls8c_ard_3-0-0_093082_2015-05-16_final
2015-05-16 09:37:27	ga_ls8c_ard_3-0-0_093083_2015-05-16_final
2015-05-18 09:26:18	ga_ls8c_ard_3-0-0_091086_2015-05-17_final
2015-05-18 09:26:42	ga_ls8c_ard_3-0-0_091087_2015-05-17_final
2015-05-18 09:27:06	ga_ls8c_ard_3-0-0_091088_2015-05-17_final
2015-05-18 09:27:30	ga_ls8c_ard_3-0-0_091089_2015-05-17_final
2015-05-18 09:27:54	ga_ls8c_ard_3-0-0_091090_2015-05-17_final
2017-04-21 09:26:40	ga_ls8c_ard_3-0-0_091086_2017-04-20_final
2017-04-21 09:27:04	ga_ls8c_ard_3-0-0_091087_2017-04-20_final
2017-04-21 09:27:28	ga_ls8c_ard_3-0-0_091088_2017-04-20_final
2017-04-21 09:27:52	ga_ls8c_ard_3-0-0_091089_2017-04-20_final
2017-04-21 09:28:16	ga_ls8c_ard_3-0-0_091090_2017-04-20_final
2017-04-21 09:28:40	ga_ls8c_ard_3-0-0_091091_2017-04-20_final
2017-04-24 09:49:57	ga_ls8c_ard_3-0-0_096067_2017-04-24_final
2017-04-24 09:50:21	ga_ls8c_ard_3-0-0_096068_2017-04-24_final
2017-04-24 09:50:45	ga_ls8c_ard_3-0-0_096069_2017-04-24_final
2017-04-24 09:51:09	ga_ls8c_ard_3-0-0_096070_2017-04-24_final
2017-07-17 09:31:42	ga_ls8c_ard_3-0-0_092082_2017-07-17_final
2017-07-17 09:32:06	ga_ls8c_ard_3-0-0_092083_2017-07-17_final
2017-07-17 09:32:29	ga_ls8c_ard_3-0-0_092084_2017-07-17_final
2017-07-17 09:32:53	ga_ls8c_ard_3-0-0_092085_2017-07-17_final
2017-07-17 09:33:17	ga_ls8c_ard_3-0-0_092086_2017-07-17_final
2017-07-17 09:33:41	ga_ls8c_ard_3-0-0_092087_2017-07-17_final
2017-07-19 09:22:09	ga_ls8c_ard_3-0-0_090089_2017-07-18_final
2017-07-19 09:22:33	ga_ls8c_ard_3-0-0_090090_2017-07-18_final
2017-07-19 09:22:57	ga_ls8c_ard_3-0-0_090091_2017-07-18_final
2017-07-29 09:50:32	ga_ls8c_ard_3-0-0_096067_2017-07-29_final
2017-07-29 09:50:56	ga_ls8c_ard_3-0-0_096068_2017-07-29_final
2017-07-29 09:51:20	ga_ls8c_ard_3-0-0_096069_2017-07-29_final
2017-07-29 09:51:44	ga_ls8c_ard_3-0-0_096070_2017-07-29_final
2017-08-14 09:50:38	ga_ls8c_ard_3-0-0_096067_2017-08-14_final
2017-08-14 09:51:02	ga_ls8c_ard_3-0-0_096068_2017-08-14_final
2017-08-14 09:51:26	ga_ls8c_ard_3-0-0_096069_2017-08-14_final
2017-08-14 09:51:50	ga_ls8c_ard_3-0-0_096070_2017-08-14_final
2022-05-12 09:31:46	ga_ls8c_ard_3-2-1_092082_2022-05-12_final
2022-05-12 09:32:10	ga_ls8c_ard_3-2-1_092083_2022-05-12_final
2022-05-12 09:32:34	ga_ls8c_ard_3-2-1_092084_2022-05-12_final
2022-05-12 09:32:57	ga_ls8c_ard_3-2-1_092085_2022-05-12_final
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-12 09:33:45	ga_ls8c_ard_3-2-1_092087_2022-05-12_final
2022-05-14 09:22:13	ga_ls8c_ard_3-2-1_090089_2022-05-13_final
2022-05-14 09:22:37	ga_ls8c_ard_3-2-1_090090_2022-05-13_final
2022-05-14 09:23:00	ga_ls8c_ard_3-2-1_090091_2022-05-13_final
2022-10-08 09:46:35	ga_ls8c_ard_3-2-1_095071_2022-10-08_final
2022-10-08 09:46:59	ga_ls8c_ard_3-2-1_095072_2022-10-08_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-10 09:38:11	ga_ls8c_ard_3-2-1_093081_2022-10-10_final
2022-10-10 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-10-10_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-12 09:27:47	ga_ls8c_ard_3-2-1_091086_2022-10-11_final
2022-10-12 09:28:11	ga_ls8c_ard_3-2-1_091087_2022-10-11_final
2022-10-12 09:28:35	ga_ls8c_ard_3-2-1_091088_2022-10-11_final
2022-10-12 09:28:59	ga_ls8c_ard_3-2-1_091089_2022-10-11_final
2022-10-12 09:29:23	ga_ls8c_ard_3-2-1_091090_2022-10-11_final
2022-10-17 09:41:33	ga_ls8c_ard_3-2-1_094074_2022-10-17_final
2022-10-17 09:41:57	ga_ls8c_ard_3-2-1_094075_2022-10-17_final
2022-10-17 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-10-17_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-17 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-10-17_final
2022-10-19 09:32:25	ga_ls8c_ard_3-2-1_092082_2022-10-19_final
2022-10-19 09:32:49	ga_ls8c_ard_3-2-1_092083_2022-10-19_final
2022-10-19 09:33:13	ga_ls8c_ard_3-2-1_092084_2022-10-19_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-28 09:28:18	ga_ls8c_ard_3-2-1_091087_2022-10-27_final
2022-10-28 09:28:42	ga_ls8c_ard_3-2-1_091088_2022-10-27_final
2022-10-28 09:29:06	ga_ls8c_ard_3-2-1_091089_2022-10-27_final
2022-10-28 09:29:30	ga_ls8c_ard_3-2-1_091090_2022-10-27_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-20 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-11-20_final
2022-11-20 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-11-20_final
2022-11-20 09:33:58	ga_ls8c_ard_3-2-1_092086_2022-11-20_final
2022-11-20 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-11-20_final
2022-11-22 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-11-21_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-22 09:23:37	ga_ls8c_ard_3-2-1_090091_2022-11-21_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years