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
2018-03-12 09:41:01	ga_ls8c_ard_3-0-0_094075_2018-03-12_final
2018-03-12 09:41:25	ga_ls8c_ard_3-0-0_094076_2018-03-12_final
2018-03-12 09:41:49	ga_ls8c_ard_3-0-0_094077_2018-03-12_final
2018-03-12 09:42:13	ga_ls8c_ard_3-0-0_094078_2018-03-12_final
2018-03-12 09:42:37	ga_ls8c_ard_3-0-0_094079_2018-03-12_final
2018-03-12 09:43:01	ga_ls8c_ard_3-0-0_094080_2018-03-12_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
2018-03-26 09:50:05	ga_ls8c_ard_3-0-0_096067_2018-03-26_final
2018-03-26 09:50:29	ga_ls8c_ard_3-0-0_096068_2018-03-26_final
2018-03-26 09:50:53	ga_ls8c_ard_3-0-0_096069_2018-03-26_final
2018-03-26 09:51:17	ga_ls8c_ard_3-0-0_096070_2018-03-26_final
2018-03-26 09:51:41	ga_ls8c_ard_3-0-0_096071_2018-03-26_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 09:26:54	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
2018-05-15 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
2018-07-16 09:49:46	ga_ls8c_ard_3-0-0_096067_2018-07-16_final
2018-07-16 09:50:10	ga_ls8c_ard_3-0-0_096068_2018-07-16_final
2018-07-16 09:50:34	ga_ls8c_ard_3-0-0_096069_2018-07-16_final
2018-07-16 09:50:58	ga_ls8c_ard_3-0-0_096070_2018-07-16_final
2018-07-16 09:51:21	ga_ls8c_ard_3-0-0_096071_2018-07-16_final
2019-02-04 09:36:36	ga_ls8c_ard_3-0-0_093079_2019-02-04_final
2019-02-04 09:37:00	ga_ls8c_ard_3-0-0_093080_2019-02-04_final
2019-02-04 09:37:24	ga_ls8c_ard_3-0-0_093081_2019-02-04_final
2019-02-04 09:37:48	ga_ls8c_ard_3-0-0_093082_2019-02-04_final
2019-02-04 09:38:12	ga_ls8c_ard_3-0-0_093083_2019-02-04_final
2019-02-04 09:38:36	ga_ls8c_ard_3-0-0_093084_2019-02-04_final
2019-02-06 09:27:26	ga_ls8c_ard_3-0-0_091087_2019-02-05_final
2019-02-06 09:27:50	ga_ls8c_ard_3-0-0_091088_2019-02-05_final
2019-02-06 09:28:14	ga_ls8c_ard_3-0-0_091089_2019-02-05_final
2019-02-06 09:28:38	ga_ls8c_ard_3-0-0_091090_2019-02-05_final
2019-02-06 09:29:02	ga_ls8c_ard_3-0-0_091091_2019-02-05_final
2019-02-18 09:45:20	ga_ls8c_ard_3-0-0_095070_2019-02-18_final
2019-02-18 09:45:44	ga_ls8c_ard_3-0-0_095071_2019-02-18_final
2019-02-18 09:46:08	ga_ls8c_ard_3-0-0_095072_2019-02-18_final
2019-02-18 09:46:32	ga_ls8c_ard_3-0-0_095073_2019-02-18_final
2019-02-18 09:46:56	ga_ls8c_ard_3-0-0_095074_2019-02-18_final
2019-02-18 09:47:20	ga_ls8c_ard_3-0-0_095075_2019-02-18_final
2019-02-18 09:47:44	ga_ls8c_ard_3-0-0_095076_2019-02-18_final
2019-02-20 09:36:34	ga_ls8c_ard_3-0-0_093079_2019-02-20_final
2019-02-20 09:36:58	ga_ls8c_ard_3-0-0_093080_2019-02-20_final
2019-02-20 09:37:22	ga_ls8c_ard_3-0-0_093081_2019-02-20_final
2019-02-20 09:37:45	ga_ls8c_ard_3-0-0_093082_2019-02-20_final
2019-02-20 09:38:09	ga_ls8c_ard_3-0-0_093083_2019-02-20_final
2019-02-20 09:38:33	ga_ls8c_ard_3-0-0_093084_2019-02-20_final
2019-02-22 09:27:23	ga_ls8c_ard_3-0-0_091087_2019-02-21_final
2019-02-22 09:27:47	ga_ls8c_ard_3-0-0_091088_2019-02-21_final
2019-02-22 09:28:11	ga_ls8c_ard_3-0-0_091089_2019-02-21_final
2019-02-22 09:28:35	ga_ls8c_ard_3-0-0_091090_2019-02-21_final
2019-02-22 09:28:59	ga_ls8c_ard_3-0-0_091091_2019-02-21_final
2019-03-15 09:41:01	ga_ls8c_ard_3-1-0_094075_2019-03-15_final
2019-03-15 09:41:25	ga_ls8c_ard_3-1-0_094076_2019-03-15_final
2019-03-15 09:41:49	ga_ls8c_ard_3-1-0_094077_2019-03-15_final
2019-03-15 09:42:13	ga_ls8c_ard_3-1-0_094078_2019-03-15_final
2019-03-15 09:42:37	ga_ls8c_ard_3-1-0_094079_2019-03-15_final
2019-03-15 09:43:01	ga_ls8c_ard_3-1-0_094080_2019-03-15_final
2019-06-10 09:45:24	ga_ls8c_ard_3-0-0_095070_2019-06-10_final
2019-06-10 09:45:48	ga_ls8c_ard_3-0-0_095071_2019-06-10_final
2019-06-10 09:46:12	ga_ls8c_ard_3-0-0_095072_2019-06-10_final
2019-06-12 09:36:38	ga_ls8c_ard_3-1-0_093079_2019-06-12_final
2019-06-12 09:37:02	ga_ls8c_ard_3-1-0_093080_2019-06-12_final
2019-06-12 09:37:26	ga_ls8c_ard_3-1-0_093081_2019-06-12_final
2019-06-12 09:37:50	ga_ls8c_ard_3-1-0_093082_2019-06-12_final
2019-06-12 09:38:14	ga_ls8c_ard_3-1-0_093083_2019-06-12_final
2019-06-12 09:38:38	ga_ls8c_ard_3-1-0_093084_2019-06-12_final
2019-06-19 09:41:16	ga_ls8c_ard_3-1-0_094075_2019-06-19_final
2019-06-19 09:41:40	ga_ls8c_ard_3-1-0_094076_2019-06-19_final
2019-06-19 09:42:04	ga_ls8c_ard_3-1-0_094077_2019-06-19_final
2019-06-19 09:42:28	ga_ls8c_ard_3-1-0_094078_2019-06-19_final
2019-06-19 09:42:52	ga_ls8c_ard_3-1-0_094079_2019-06-19_final
2019-06-19 09:43:16	ga_ls8c_ard_3-1-0_094080_2019-06-19_final
2019-06-30 09:27:10	ga_ls8c_ard_3-1-0_091086_2019-06-29_final
2019-06-30 09:27:34	ga_ls8c_ard_3-1-0_091087_2019-06-29_final
2019-06-30 09:27:58	ga_ls8c_ard_3-1-0_091088_2019-06-29_final
2019-06-30 09:28:22	ga_ls8c_ard_3-1-0_091089_2019-06-29_final
2019-06-30 09:28:46	ga_ls8c_ard_3-1-0_091090_2019-06-29_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