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
2018-01-20 09:12:31	ga_ls8c_ard_3-0-0_089080_2018-01-19_final
2018-02-05 09:12:22	ga_ls8c_ard_3-0-0_089080_2018-02-04_final
2018-03-25 09:12:01	ga_ls8c_ard_3-0-0_089080_2018-03-24_final
2018-04-10 09:11:53	ga_ls8c_ard_3-0-0_089080_2018-04-09_final
2018-05-28 09:11:21	ga_ls8c_ard_3-0-0_089080_2018-05-27_final
2018-06-13 09:11:23	ga_ls8c_ard_3-0-0_089080_2018-06-12_final
2018-07-31 09:11:48	ga_ls8c_ard_3-0-0_089080_2018-07-30_final
2018-09-17 09:12:09	ga_ls8c_ard_3-0-0_089080_2018-09-16_final
2018-10-03 09:12:16	ga_ls8c_ard_3-0-0_089080_2018-10-02_final
2018-10-19 09:12:22	ga_ls8c_ard_3-0-0_089080_2018-10-18_final
2018-11-04 09:12:26	ga_ls8c_ard_3-0-0_089080_2018-11-03_final
2018-11-20 09:12:27	ga_ls8c_ard_3-0-0_089080_2018-11-19_final
2018-12-06 09:12:25	ga_ls8c_ard_3-0-0_089080_2018-12-05_final
2018-12-22 09:12:23	ga_ls8c_ard_3-0-0_089080_2018-12-21_final
2019-01-23 09:12:19	ga_ls8c_ard_3-0-0_089080_2019-01-22_final
2019-02-24 09:12:13	ga_ls8c_ard_3-0-0_089080_2019-02-23_final
2019-03-12 09:12:08	ga_ls8c_ard_3-1-0_089080_2019-03-11_final
2019-04-13 09:11:59	ga_ls8c_ard_3-1-0_089080_2019-04-12_final
2019-04-29 09:11:55	ga_ls8c_ard_3-0-0_089080_2019-04-28_final
2019-05-31 09:12:14	ga_ls8c_ard_3-0-0_089080_2019-05-30_final
2019-06-16 09:12:21	ga_ls8c_ard_3-1-0_089080_2019-06-15_final
2019-07-18 09:12:28	ga_ls8c_ard_3-1-0_089080_2019-07-17_final
2019-08-03 09:12:35	ga_ls8c_ard_3-1-0_089080_2019-08-02_final
2019-08-19 09:12:40	ga_ls8c_ard_3-1-0_089080_2019-08-18_final
2019-09-04 09:12:43	ga_ls8c_ard_3-1-0_089080_2019-09-03_final
2019-09-20 09:12:49	ga_ls8c_ard_3-1-0_089080_2019-09-19_final
2019-10-06 09:12:53	ga_ls8c_ard_3-1-0_089080_2019-10-05_final
2019-10-22 09:12:55	ga_ls8c_ard_3-1-0_089080_2019-10-21_final
2019-11-23 09:12:50	ga_ls8c_ard_3-1-0_089080_2019-11-22_final
2019-12-09 09:12:49	ga_ls8c_ard_3-1-0_089080_2019-12-08_final
2019-12-25 09:12:46	ga_ls8c_ard_3-1-0_089080_2019-12-24_final
2020-01-10 09:12:42	ga_ls8c_ard_3-1-0_089080_2020-01-09_final
2020-01-26 09:12:38	ga_ls8c_ard_3-1-0_089080_2020-01-25_final
2020-02-11 09:12:34	ga_ls8c_ard_3-1-0_089080_2020-02-10_final
2020-02-27 09:12:30	ga_ls8c_ard_3-1-0_089080_2020-02-26_final
2020-03-14 09:12:23	ga_ls8c_ard_3-1-0_089080_2020-03-13_final
2020-03-30 09:12:14	ga_ls8c_ard_3-1-0_089080_2020-03-29_final
2020-04-15 09:12:07	ga_ls8c_ard_3-1-0_089080_2020-04-14_final
2020-05-01 09:11:59	ga_ls8c_ard_3-1-0_089080_2020-04-30_final
2020-05-17 09:11:56	ga_ls8c_ard_3-1-0_089080_2020-05-16_final
2020-06-02 09:12:01	ga_ls8c_ard_3-1-0_089080_2020-06-01_final
2020-06-18 09:12:11	ga_ls8c_ard_3-1-0_089080_2020-06-17_final
2020-07-04 09:12:19	ga_ls8c_ard_3-1-0_089080_2020-07-03_final
2020-07-20 09:12:25	ga_ls8c_ard_3-1-0_089080_2020-07-19_final
2020-08-05 09:12:28	ga_ls8c_ard_3-1-0_089080_2020-08-04_final
2020-09-06 09:12:42	ga_ls8c_ard_3-1-0_089080_2020-09-05_final
2020-09-22 09:12:48	ga_ls8c_ard_3-1-0_089080_2020-09-21_final
2020-10-08 09:12:51	ga_ls8c_ard_3-1-0_089080_2020-10-07_final
2020-10-24 09:12:51	ga_ls8c_ard_3-1-0_089080_2020-10-23_final
2020-11-25 09:12:51	ga_ls8c_ard_3-1-0_089080_2020-11-24_final
2020-12-11 09:12:52	ga_ls8c_ard_3-1-0_089080_2020-12-10_final
2021-03-17 09:12:21	ga_ls8c_ard_3-2-0_089080_2021-03-16_final
2021-04-02 09:12:17	ga_ls8c_ard_3-2-0_089080_2021-04-01_final
2021-04-18 09:12:11	ga_ls8c_ard_3-2-0_089080_2021-04-17_final
2021-05-04 09:12:01	ga_ls8c_ard_3-2-0_089080_2021-05-03_final
2021-05-20 09:12:09	ga_ls8c_ard_3-2-0_089080_2021-05-19_final
2021-06-05 09:12:17	ga_ls8c_ard_3-2-0_089080_2021-06-04_final
2021-06-21 09:12:23	ga_ls8c_ard_3-2-0_089080_2021-06-20_final
2021-07-07 09:12:25	ga_ls8c_ard_3-2-0_089080_2021-07-06_final
2021-07-23 09:12:30	ga_ls8c_ard_3-2-0_089080_2021-07-22_final
2021-08-08 09:12:37	ga_ls8c_ard_3-2-0_089080_2021-08-07_final
2021-08-24 09:12:42	ga_ls8c_ard_3-2-0_089080_2021-08-23_final
2021-09-09 09:12:47	ga_ls8c_ard_3-2-0_089080_2021-09-08_final
2021-09-25 09:12:50	ga_ls8c_ard_3-2-0_089080_2021-09-24_final
2021-10-11 09:12:55	ga_ls8c_ard_3-2-0_089080_2021-10-10_final
2021-10-27 09:12:57	ga_ls8c_ard_3-2-0_089080_2021-10-26_final
2021-11-12 09:12:53	ga_ls8c_ard_3-2-0_089080_2021-11-11_final
2021-11-28 09:12:52	ga_ls8c_ard_3-2-0_089080_2021-11-27_final
2021-12-14 09:12:52	ga_ls8c_ard_3-2-1_089080_2021-12-13_final
2021-12-30 09:12:46	ga_ls8c_ard_3-2-1_089080_2021-12-29_final
2022-01-15 09:12:44	ga_ls8c_ard_3-2-1_089080_2022-01-14_final
2022-01-31 09:12:39	ga_ls8c_ard_3-2-1_089080_2022-01-30_final
2022-02-16 09:12:35	ga_ls8c_ard_3-2-1_089080_2022-02-15_final
2022-03-04 09:12:31	ga_ls8c_ard_3-2-1_089080_2022-03-03_final
2022-03-20 09:12:24	ga_ls8c_ard_3-2-1_089080_2022-03-19_final
2022-04-05 09:12:16	ga_ls8c_ard_3-2-1_089080_2022-04-04_final
2022-04-21 09:12:20	ga_ls8c_ard_3-2-1_089080_2022-04-20_final
2022-05-07 09:12:22	ga_ls8c_ard_3-2-1_089080_2022-05-06_final
2022-05-23 09:12:27	ga_ls8c_ard_3-2-1_089080_2022-05-22_final
2022-06-08 09:12:36	ga_ls8c_ard_3-2-1_089080_2022-06-07_final
2022-06-24 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-06-23_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-26 09:12:52	ga_ls8c_ard_3-2-1_089080_2022-07-25_final
2022-08-11 09:13:01	ga_ls8c_ard_3-2-1_089080_2022-08-10_final
2022-08-27 09:13:03	ga_ls8c_ard_3-2-1_089080_2022-08-26_final
2022-09-12 09:13:08	ga_ls8c_ard_3-2-1_089080_2022-09-11_final
2022-09-28 09:13:10	ga_ls8c_ard_3-2-1_089080_2022-09-27_final
2022-10-14 09:13:00	ga_ls8c_ard_3-2-1_089080_2022-10-13_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-12-01 09:13:05	ga_ls8c_ard_3-2-1_089080_2022-11-30_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-23 09:12:22	ga_ls8c_ard_3-2-1_089080_2023-03-22_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-24 09:12:02	ga_ls8c_ard_3-2-1_089080_2023-04-23_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years