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
2018-02-19 09:27:03	ga_ls8c_ard_3-0-0_091086_2018-02-18_final
2018-02-19 09:27:27	ga_ls8c_ard_3-0-0_091087_2018-02-18_final
2018-02-19 09:27:51	ga_ls8c_ard_3-0-0_091088_2018-02-18_final
2018-02-19 09:28:15	ga_ls8c_ard_3-0-0_091089_2018-02-18_final
2018-02-19 09:28:39	ga_ls8c_ard_3-0-0_091090_2018-02-18_final
2018-02-19 09:29:03	ga_ls8c_ard_3-0-0_091091_2018-02-18_final
2018-02-22 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-02-22_final
2018-02-22 09:50:45	ga_ls8c_ard_3-0-0_096068_2018-02-22_final
2018-02-22 09:51:09	ga_ls8c_ard_3-0-0_096069_2018-02-22_final
2018-02-22 09:51:33	ga_ls8c_ard_3-0-0_096070_2018-02-22_final
2018-03-14 09:31:50	ga_ls8c_ard_3-0-0_092083_2018-03-14_final
2018-03-14 09:32:14	ga_ls8c_ard_3-0-0_092084_2018-03-14_final
2018-03-14 09:32:38	ga_ls8c_ard_3-0-0_092085_2018-03-14_final
2018-03-14 09:33:02	ga_ls8c_ard_3-0-0_092086_2018-03-14_final
2018-03-14 09:33:26	ga_ls8c_ard_3-0-0_092087_2018-03-14_final
2018-03-14 09:33:49	ga_ls8c_ard_3-0-0_092088_2018-03-14_final
2018-04-01 09:21:44	ga_ls8c_ard_3-0-0_090089_2018-03-31_final
2018-04-01 09:22:08	ga_ls8c_ard_3-0-0_090090_2018-03-31_final
2018-04-01 09:22:32	ga_ls8c_ard_3-0-0_090091_2018-03-31_final
2018-04-04 09:45:02	ga_ls8c_ard_3-0-0_095070_2018-04-04_final
2018-04-04 09:45:26	ga_ls8c_ard_3-0-0_095071_2018-04-04_final
2018-04-04 09:45:50	ga_ls8c_ard_3-0-0_095072_2018-04-04_final
2018-04-22 09:36:05	ga_ls8c_ard_3-0-0_093079_2018-04-22_final
2018-04-22 09:36:29	ga_ls8c_ard_3-0-0_093080_2018-04-22_final
2018-04-22 09:36:53	ga_ls8c_ard_3-0-0_093081_2018-04-22_final
2018-04-22 09:37:17	ga_ls8c_ard_3-0-0_093082_2018-04-22_final
2018-04-22 09:37:41	ga_ls8c_ard_3-0-0_093083_2018-04-22_final
2018-04-22 09:38:05	ga_ls8c_ard_3-0-0_093084_2018-04-22_final
2018-04-24 09:26:30	ga_ls8c_ard_3-0-0_091086_2018-04-23_final
2018-04-24 09:26:54	ga_ls8c_ard_3-0-0_091087_2018-04-23_final
2018-04-24 09:27:18	ga_ls8c_ard_3-0-0_091088_2018-04-23_final
2018-04-24 09:27:42	ga_ls8c_ard_3-1-0_091089_2018-04-23_final
2018-04-24 09:28:06	ga_ls8c_ard_3-0-0_091090_2018-04-23_final
2018-04-24 09:28:30	ga_ls8c_ard_3-0-0_091091_2018-04-23_final
2018-05-03 09:21:26	ga_ls8c_ard_3-0-0_090089_2018-05-02_final
2018-05-03 09:21:50	ga_ls8c_ard_3-0-0_090090_2018-05-02_final
2018-05-03 09:22:14	ga_ls8c_ard_3-0-0_090091_2018-05-02_final
2018-05-06 09:44:43	ga_ls8c_ard_3-0-0_095070_2018-05-06_final
2018-05-06 09:45:07	ga_ls8c_ard_3-0-0_095071_2018-05-06_final
2018-05-06 09:45:31	ga_ls8c_ard_3-0-0_095072_2018-05-06_final
2018-05-06 09:45:55	ga_ls8c_ard_3-0-0_095073_2018-05-06_final
2018-05-06 09:46:19	ga_ls8c_ard_3-0-0_095074_2018-05-06_final
2018-05-06 09:46:43	ga_ls8c_ard_3-0-0_095075_2018-05-06_final
2018-05-15 09:40:02	ga_ls8c_ard_3-0-0_094074_2018-05-15_final
2018-05-15 09:40:26	ga_ls8c_ard_3-0-0_094075_2018-05-15_final
2018-05-15 09:40:50	ga_ls8c_ard_3-0-0_094076_2018-05-15_final
2018-05-15 09:41:14	ga_ls8c_ard_3-0-0_094077_2018-05-15_final
2018-05-15 09:41:38	ga_ls8c_ard_3-0-0_094078_2018-05-15_final
2018-05-15 09:42:02	ga_ls8c_ard_3-0-0_094079_2018-05-15_final
2018-05-15 09:42:26	ga_ls8c_ard_3-0-0_094080_2018-05-15_final
2018-05-17 09:31:15	ga_ls8c_ard_3-0-0_092083_2018-05-17_final
2018-05-17 09:31:39	ga_ls8c_ard_3-0-0_092084_2018-05-17_final
2018-05-17 09:32:03	ga_ls8c_ard_3-0-0_092085_2018-05-17_final
2018-05-17 09:32:26	ga_ls8c_ard_3-0-0_092086_2018-05-17_final
2018-05-17 09:32:50	ga_ls8c_ard_3-0-0_092087_2018-05-17_final
2018-05-17 09:33:14	ga_ls8c_ard_3-0-0_092088_2018-05-17_final
2018-07-09 09:44:44	ga_ls8c_ard_3-0-0_095070_2018-07-09_final
2018-07-09 09:45:08	ga_ls8c_ard_3-0-0_095071_2018-07-09_final
2018-07-09 09:45:31	ga_ls8c_ard_3-0-0_095072_2018-07-09_final
2018-07-09 09:45:55	ga_ls8c_ard_3-0-0_095073_2018-07-09_final
2018-07-09 09:46:19	ga_ls8c_ard_3-0-0_095074_2018-07-09_final
2018-07-09 09:46:43	ga_ls8c_ard_3-0-0_095075_2018-07-09_final
2018-07-18 09:40:12	ga_ls8c_ard_3-0-0_094074_2018-07-18_final
2018-07-18 09:40:36	ga_ls8c_ard_3-0-0_094075_2018-07-18_final
2018-07-18 09:41:00	ga_ls8c_ard_3-0-0_094076_2018-07-18_final
2018-07-18 09:41:24	ga_ls8c_ard_3-0-0_094077_2018-07-18_final
2018-07-18 09:41:48	ga_ls8c_ard_3-0-0_094078_2018-07-18_final
2018-07-18 09:42:12	ga_ls8c_ard_3-0-0_094079_2018-07-18_final
2018-07-18 09:42:36	ga_ls8c_ard_3-0-0_094080_2018-07-18_final
2018-07-22 09:21:30	ga_ls8c_ard_3-0-0_090089_2018-07-21_final
2018-07-22 09:21:54	ga_ls8c_ard_3-0-0_090090_2018-07-21_final
2018-07-22 09:22:18	ga_ls8c_ard_3-0-0_090091_2018-07-21_final
2022-01-25 09:46:10	ga_ls8c_ard_3-2-1_095071_2022-01-25_final
2022-01-25 09:46:34	ga_ls8c_ard_3-2-1_095072_2022-01-25_final
2022-01-25 09:46:58	ga_ls8c_ard_3-2-1_095073_2022-01-25_final
2022-01-25 09:47:22	ga_ls8c_ard_3-2-1_095074_2022-01-25_final
2022-01-25 09:47:46	ga_ls8c_ard_3-2-1_095075_2022-01-25_final
2022-02-23 09:22:19	ga_ls8c_ard_3-2-1_090089_2022-02-22_final
2022-02-23 09:22:43	ga_ls8c_ard_3-2-1_090090_2022-02-22_final
2022-02-23 09:23:07	ga_ls8c_ard_3-2-1_090091_2022-02-22_final
2022-02-26 09:46:02	ga_ls8c_ard_3-2-1_095071_2022-02-26_final
2022-02-26 09:46:26	ga_ls8c_ard_3-2-1_095072_2022-02-26_final
2022-02-26 09:46:50	ga_ls8c_ard_3-2-1_095073_2022-02-26_final
2022-02-26 09:47:14	ga_ls8c_ard_3-2-1_095074_2022-02-26_final
2022-02-26 09:47:38	ga_ls8c_ard_3-2-1_095075_2022-02-26_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-03 09:37:51	ga_ls8c_ard_3-2-1_093082_2022-05-03_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-05 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-05-04_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-05 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-05-04_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-20 09:46:41	ga_ls8c_ard_3-2-1_095072_2022-07-20_final
2022-07-20 09:47:05	ga_ls8c_ard_3-2-1_095073_2022-07-20_final
2022-07-20 09:47:29	ga_ls8c_ard_3-2-1_095074_2022-07-20_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years