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
2017-06-08 09:19:45	ga_ls8c_ard_3-0-0_091068_2017-06-07_final
2017-06-24 09:19:50	ga_ls8c_ard_3-0-0_091068_2017-06-23_final
2017-07-10 09:19:53	ga_ls8c_ard_3-0-0_091068_2017-07-09_final
2017-07-26 09:20:00	ga_ls8c_ard_3-0-0_091068_2017-07-25_final
2017-08-11 09:20:07	ga_ls8c_ard_3-0-0_091068_2017-08-10_final
2017-08-27 09:20:11	ga_ls8c_ard_3-0-0_091068_2017-08-26_final
2017-09-12 09:20:12	ga_ls8c_ard_3-0-0_091068_2017-09-11_final
2017-09-28 09:20:18	ga_ls8c_ard_3-0-0_091068_2017-09-27_final
2017-10-14 09:20:22	ga_ls8c_ard_3-0-0_091068_2017-10-13_final
2017-10-30 09:20:23	ga_ls8c_ard_3-0-0_091068_2017-10-29_final
2017-11-15 09:20:20	ga_ls8c_ard_3-0-0_091068_2017-11-14_final
2017-12-01 09:20:14	ga_ls8c_ard_3-0-0_091068_2017-11-30_final
2017-12-17 09:20:16	ga_ls8c_ard_3-0-0_091068_2017-12-16_final
2018-01-02 09:20:14	ga_ls8c_ard_3-0-0_091068_2018-01-01_final
2018-01-18 09:20:07	ga_ls8c_ard_3-0-0_091068_2018-01-17_final
2018-02-03 09:19:57	ga_ls8c_ard_3-0-0_091068_2018-02-02_final
2018-02-19 09:19:52	ga_ls8c_ard_3-0-0_091068_2018-02-18_final
2018-03-07 09:19:44	ga_ls8c_ard_3-0-0_091068_2018-03-06_final
2018-03-23 09:19:36	ga_ls8c_ard_3-0-0_091068_2018-03-22_final
2018-04-24 09:19:19	ga_ls8c_ard_3-0-0_091068_2018-04-23_final
2018-05-10 09:19:10	ga_ls8c_ard_3-0-0_091068_2018-05-09_final
2018-05-26 09:18:58	ga_ls8c_ard_3-0-0_091068_2018-05-25_final
2018-06-11 09:18:56	ga_ls8c_ard_3-0-0_091068_2018-06-10_final
2018-06-27 09:19:06	ga_ls8c_ard_3-0-0_091068_2018-06-26_final
2018-07-13 09:19:14	ga_ls8c_ard_3-0-0_091068_2018-07-12_final
2018-07-29 09:19:21	ga_ls8c_ard_3-0-0_091068_2018-07-28_final
2018-08-14 09:19:30	ga_ls8c_ard_3-0-0_091068_2018-08-13_final
2018-08-30 09:19:38	ga_ls8c_ard_3-0-0_091068_2018-08-29_final
2018-09-15 09:19:42	ga_ls8c_ard_3-0-0_091068_2018-09-14_final
2018-10-01 09:19:49	ga_ls8c_ard_3-0-0_091068_2018-09-30_final
2018-10-17 09:19:56	ga_ls8c_ard_3-0-0_091068_2018-10-16_final
2018-11-02 09:20:00	ga_ls8c_ard_3-0-0_091068_2018-11-01_final
2018-11-18 09:20:01	ga_ls8c_ard_3-0-0_091068_2018-11-17_final
2018-12-04 09:20:00	ga_ls8c_ard_3-0-0_091068_2018-12-03_final
2018-12-20 09:19:58	ga_ls8c_ard_3-0-0_091068_2018-12-19_final
2019-01-05 09:19:57	ga_ls8c_ard_3-0-0_091068_2019-01-04_final
2019-01-21 09:19:54	ga_ls8c_ard_3-0-0_091068_2019-01-20_final
2019-02-06 09:19:51	ga_ls8c_ard_3-0-0_091068_2019-02-05_final
2019-02-22 09:19:48	ga_ls8c_ard_3-0-0_091068_2019-02-21_final
2019-03-10 09:19:43	ga_ls8c_ard_3-1-0_091068_2019-03-09_final
2019-03-26 09:19:39	ga_ls8c_ard_3-1-0_091068_2019-03-25_final
2019-04-11 09:19:35	ga_ls8c_ard_3-1-0_091068_2019-04-10_final
2019-04-27 09:19:29	ga_ls8c_ard_3-0-0_091068_2019-04-26_final
2019-05-13 09:19:38	ga_ls8c_ard_3-0-0_091068_2019-05-12_final
2019-05-29 09:19:47	ga_ls8c_ard_3-0-0_091068_2019-05-28_final
2019-06-14 09:19:54	ga_ls8c_ard_3-1-0_091068_2019-06-13_final
2019-06-30 09:19:59	ga_ls8c_ard_3-1-0_091068_2019-06-29_final
2019-07-16 09:20:02	ga_ls8c_ard_3-1-0_091068_2019-07-15_final
2019-08-01 09:20:08	ga_ls8c_ard_3-1-0_091068_2019-07-31_final
2019-08-17 09:20:14	ga_ls8c_ard_3-1-0_091068_2019-08-16_final
2019-09-02 09:20:17	ga_ls8c_ard_3-1-0_091068_2019-09-01_final
2019-09-18 09:20:23	ga_ls8c_ard_3-1-0_091068_2019-09-17_final
2019-10-04 09:20:27	ga_ls8c_ard_3-1-0_091068_2019-10-03_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-11-05 09:20:28	ga_ls8c_ard_3-1-0_091068_2019-11-04_final
2019-11-21 09:20:24	ga_ls8c_ard_3-1-0_091068_2019-11-20_final
2019-12-07 09:20:24	ga_ls8c_ard_3-1-0_091068_2019-12-06_final
2019-12-23 09:20:21	ga_ls8c_ard_3-1-0_091068_2019-12-22_final
2020-01-08 09:20:17	ga_ls8c_ard_3-1-0_091068_2020-01-07_final
2020-01-24 09:20:13	ga_ls8c_ard_3-1-0_091068_2020-01-23_final
2020-02-09 09:20:08	ga_ls8c_ard_3-1-0_091068_2020-02-08_final
2020-02-25 09:20:05	ga_ls8c_ard_3-1-0_091068_2020-02-24_final
2020-03-12 09:19:58	ga_ls8c_ard_3-1-0_091068_2020-03-11_final
2020-03-28 09:19:49	ga_ls8c_ard_3-1-0_091068_2020-03-27_final
2020-04-13 09:19:42	ga_ls8c_ard_3-1-0_091068_2020-04-12_final
2020-04-29 09:19:34	ga_ls8c_ard_3-1-0_091068_2020-04-28_final
2020-05-15 09:19:30	ga_ls8c_ard_3-1-0_091068_2020-05-14_final
2020-05-31 09:19:34	ga_ls8c_ard_3-1-0_091068_2020-05-30_final
2020-06-16 09:19:44	ga_ls8c_ard_3-1-0_091068_2020-06-15_final
2020-07-02 09:19:52	ga_ls8c_ard_3-1-0_091068_2020-07-01_final
2020-07-18 09:19:58	ga_ls8c_ard_3-1-0_091068_2020-07-17_final
2020-08-03 09:20:02	ga_ls8c_ard_3-1-0_091068_2020-08-02_final
2020-08-19 09:20:08	ga_ls8c_ard_3-1-0_091068_2020-08-18_final
2020-09-04 09:20:16	ga_ls8c_ard_3-1-0_091068_2020-09-03_final
2020-09-20 09:20:21	ga_ls8c_ard_3-1-0_091068_2020-09-19_final
2020-10-06 09:20:25	ga_ls8c_ard_3-1-0_091068_2020-10-05_final
2020-10-22 09:20:25	ga_ls8c_ard_3-1-0_091068_2020-10-21_final
2020-11-23 09:20:25	ga_ls8c_ard_3-1-0_091068_2020-11-22_final
2020-12-09 09:20:26	ga_ls8c_ard_3-1-0_091068_2020-12-08_final
2020-12-25 09:20:24	ga_ls8c_ard_3-2-0_091068_2020-12-24_final
2021-01-10 09:20:18	ga_ls8c_ard_3-2-0_091068_2021-01-09_final
2021-01-26 09:20:14	ga_ls8c_ard_3-2-0_091068_2021-01-25_final
2021-02-11 09:20:11	ga_ls8c_ard_3-2-0_091068_2021-02-10_final
2021-02-27 09:20:05	ga_ls8c_ard_3-2-0_091068_2021-02-26_final
2021-03-15 09:19:56	ga_ls8c_ard_3-2-0_091068_2021-03-14_final
2021-03-31 09:19:52	ga_ls8c_ard_3-2-0_091068_2021-03-30_final
2021-04-16 09:19:46	ga_ls8c_ard_3-2-0_091068_2021-04-15_final
2021-05-02 09:19:37	ga_ls8c_ard_3-2-0_091068_2021-05-01_final
2021-05-18 09:19:42	ga_ls8c_ard_3-2-0_091068_2021-05-17_final
2021-06-03 09:19:51	ga_ls8c_ard_3-2-0_091068_2021-06-02_final
2021-06-19 09:19:56	ga_ls8c_ard_3-2-0_091068_2021-06-18_final
2021-07-05 09:19:59	ga_ls8c_ard_3-2-0_091068_2021-07-04_final
2021-07-21 09:20:03	ga_ls8c_ard_3-2-0_091068_2021-07-20_final
2021-08-06 09:20:11	ga_ls8c_ard_3-2-0_091068_2021-08-05_final
2021-08-22 09:20:16	ga_ls8c_ard_3-2-0_091068_2021-08-21_final
2021-09-07 09:20:21	ga_ls8c_ard_3-2-0_091068_2021-09-06_final
2021-09-23 09:20:23	ga_ls8c_ard_3-2-0_091068_2021-09-22_final
2021-10-09 09:20:29	ga_ls8c_ard_3-2-0_091068_2021-10-08_final
2021-10-25 09:20:31	ga_ls8c_ard_3-2-0_091068_2021-10-24_final
2021-11-10 09:20:28	ga_ls8c_ard_3-2-0_091068_2021-11-09_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