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 11:00:21	ga_ls8c_ard_3-0-0_107072_2018-02-19_final
2018-06-11 10:59:24	ga_ls8c_ard_3-0-0_107072_2018-06-11_final
2018-07-29 10:59:50	ga_ls8c_ard_3-0-0_107072_2018-07-29_final
2018-12-04 11:00:28	ga_ls8c_ard_3-0-0_107072_2018-12-04_final
2019-08-17 11:00:43	ga_ls8c_ard_3-1-0_107072_2019-08-17_final
2019-12-07 11:00:53	ga_ls8c_ard_3-1-0_107072_2019-12-07_final
2019-12-23 11:00:50	ga_ls8c_ard_3-1-0_107072_2019-12-23_final
2020-01-24 11:00:42	ga_ls8c_ard_3-1-0_107072_2020-01-24_final
2020-02-09 11:00:37	ga_ls8c_ard_3-1-0_107072_2020-02-09_final
2020-02-25 11:00:33	ga_ls8c_ard_3-1-0_107072_2020-02-25_final
2020-03-12 11:00:27	ga_ls8c_ard_3-1-0_107072_2020-03-12_final
2020-03-28 11:00:18	ga_ls8c_ard_3-1-0_107072_2020-03-28_final
2020-04-13 11:00:11	ga_ls8c_ard_3-1-0_107072_2020-04-13_final
2020-04-29 11:00:03	ga_ls8c_ard_3-1-0_107072_2020-04-29_final
2020-05-15 10:59:59	ga_ls8c_ard_3-1-0_107072_2020-05-15_final
2020-05-31 11:00:03	ga_ls8c_ard_3-1-0_107072_2020-05-31_final
2020-06-16 11:00:13	ga_ls8c_ard_3-1-0_107072_2020-06-16_final
2020-07-02 11:00:21	ga_ls8c_ard_3-1-0_107072_2020-07-02_final
2020-07-18 11:00:27	ga_ls8c_ard_3-1-0_107072_2020-07-18_final
2020-08-03 11:00:31	ga_ls8c_ard_3-1-0_107072_2020-08-03_final
2020-08-19 11:00:37	ga_ls8c_ard_3-1-0_107072_2020-08-19_final
2020-09-04 11:00:45	ga_ls8c_ard_3-1-0_107072_2020-09-04_final
2020-09-20 11:00:50	ga_ls8c_ard_3-1-0_107072_2020-09-20_final
2020-10-06 11:00:53	ga_ls8c_ard_3-1-0_107072_2020-10-06_final
2020-10-22 11:00:54	ga_ls8c_ard_3-1-0_107072_2020-10-22_final
2020-11-23 11:00:53	ga_ls8c_ard_3-1-0_107072_2020-11-23_final
2020-12-09 11:00:55	ga_ls8c_ard_3-1-0_107072_2020-12-09_final
2020-12-25 11:00:53	ga_ls8c_ard_3-2-0_107072_2020-12-25_final
2021-01-10 11:00:47	ga_ls8c_ard_3-2-0_107072_2021-01-10_final
2021-01-26 11:00:42	ga_ls8c_ard_3-2-0_107072_2021-01-26_final
2021-02-11 11:00:40	ga_ls8c_ard_3-2-0_107072_2021-02-11_final
2021-02-27 11:00:34	ga_ls8c_ard_3-2-0_107072_2021-02-27_final
2021-03-15 11:00:25	ga_ls8c_ard_3-2-0_107072_2021-03-15_final
2021-03-31 11:00:21	ga_ls8c_ard_3-2-0_107072_2021-03-31_final
2021-04-16 11:00:15	ga_ls8c_ard_3-2-0_107072_2021-04-16_final
2021-05-02 11:00:06	ga_ls8c_ard_3-2-0_107072_2021-05-02_final
2021-05-18 11:00:11	ga_ls8c_ard_3-2-0_107072_2021-05-18_final
2021-06-03 11:00:19	ga_ls8c_ard_3-2-0_107072_2021-06-03_final
2021-06-19 11:00:25	ga_ls8c_ard_3-2-0_107072_2021-06-19_final
2021-07-05 11:00:28	ga_ls8c_ard_3-2-0_107072_2021-07-05_final
2021-07-21 11:00:32	ga_ls8c_ard_3-2-0_107072_2021-07-21_final
2021-08-06 11:00:39	ga_ls8c_ard_3-2-0_107072_2021-08-06_final
2021-08-22 11:00:45	ga_ls8c_ard_3-2-0_107072_2021-08-22_final
2021-09-07 11:00:49	ga_ls8c_ard_3-2-0_107072_2021-09-07_final
2021-09-23 11:00:52	ga_ls8c_ard_3-2-0_107072_2021-09-23_final
2021-10-09 11:00:58	ga_ls8c_ard_3-2-0_107072_2021-10-09_final
2021-10-25 11:01:00	ga_ls8c_ard_3-2-0_107072_2021-10-25_final
2021-11-10 11:00:57	ga_ls8c_ard_3-2-0_107072_2021-11-10_final
2021-11-26 11:00:55	ga_ls8c_ard_3-2-0_107072_2021-11-26_final
2021-12-12 11:00:55	ga_ls8c_ard_3-2-1_107072_2021-12-12_final
2021-12-28 11:00:50	ga_ls8c_ard_3-2-1_107072_2021-12-28_final
2022-01-13 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-01-13_final
2022-01-29 11:00:42	ga_ls8c_ard_3-2-1_107072_2022-01-29_final
2022-02-14 11:00:39	ga_ls8c_ard_3-2-1_107072_2022-02-14_final
2022-03-02 11:00:35	ga_ls8c_ard_3-2-1_107072_2022-03-02_final
2022-03-18 11:00:28	ga_ls8c_ard_3-2-1_107072_2022-03-18_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-19 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-04-19_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-21 11:00:31	ga_ls8c_ard_3-2-1_107072_2022-05-21_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-22 11:00:47	ga_ls8c_ard_3-2-1_107072_2022-06-22_final
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-24 11:00:54	ga_ls8c_ard_3-2-1_107072_2022-07-24_final
2022-08-09 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-08-09_final
2022-08-25 11:01:06	ga_ls8c_ard_3-2-1_107072_2022-08-25_final
2022-09-10 11:01:10	ga_ls8c_ard_3-2-1_107072_2022-09-10_final
2022-09-26 11:01:13	ga_ls8c_ard_3-2-1_107072_2022-09-26_final
2022-10-12 11:01:05	ga_ls8c_ard_3-2-1_107072_2022-10-12_final
2022-10-28 11:01:12	ga_ls8c_ard_3-2-1_107072_2022-10-28_final
2022-11-13 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-13_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-31 11:00:59	ga_ls8c_ard_3-2-1_107072_2022-12-31_final
2023-01-16 11:00:52	ga_ls8c_ard_3-2-1_107072_2023-01-16_final
2023-02-01 11:00:57	ga_ls8c_ard_3-2-1_107072_2023-02-01_final
2023-02-17 11:00:48	ga_ls8c_ard_3-2-1_107072_2023-02-17_final
2023-03-05 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-03-05_final
2023-03-21 11:00:27	ga_ls8c_ard_3-2-1_107072_2023-03-21_final
2023-04-06 11:00:15	ga_ls8c_ard_3-2-1_107072_2023-04-06_final
2023-05-08 10:59:57	ga_ls8c_ard_3-2-1_107072_2023-05-08_final
2023-05-24 10:59:52	ga_ls8c_ard_3-2-1_107072_2023-05-24_final
2023-06-09 10:59:59	ga_ls8c_ard_3-2-1_107072_2023-06-09_final
2023-06-25 11:00:05	ga_ls8c_ard_3-2-1_107072_2023-06-25_final
2023-07-11 11:00:16	ga_ls8c_ard_3-2-1_107072_2023-07-11_final
2023-07-27 11:00:22	ga_ls8c_ard_3-2-1_107072_2023-07-27_final
2023-08-12 11:00:26	ga_ls8c_ard_3-2-1_107072_2023-08-12_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-09-13 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-09-13_final
2023-09-29 11:00:41	ga_ls8c_ard_3-2-1_107072_2023-09-29_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_nrt
2023-10-31 11:00:47	ga_ls8c_ard_3-2-1_107072_2023-10-31_final
2023-11-16 11:00:46	ga_ls8c_ard_3-2-1_107072_2023-11-16_final
2023-12-02 11:00:45	ga_ls8c_ard_3-2-1_107072_2023-12-02_final
2023-12-18 11:00:47	ga_ls8c_ard_3-2-1_107072_2023-12-18_final
2024-01-03 11:00:40	ga_ls8c_ard_3-2-1_107072_2024-01-03_final
2024-01-19 11:00:40	ga_ls8c_ard_3-2-1_107072_2024-01-19_final
2024-02-04 11:00:39	ga_ls8c_ard_3-2-1_107072_2024-02-04_final
2024-02-20 11:00:38	ga_ls8c_ard_3-2-1_107072_2024-02-20_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