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
2018-08-31 11:46:34	ga_ls8c_ard_3-0-0_114080_2018-08-31_final
2018-09-16 11:46:39	ga_ls8c_ard_3-0-0_114080_2018-09-16_final
2018-11-03 11:46:56	ga_ls8c_ard_3-0-0_114080_2018-11-03_final
2018-12-05 11:46:55	ga_ls8c_ard_3-0-0_114080_2018-12-05_final
2018-12-21 11:46:54	ga_ls8c_ard_3-0-0_114080_2018-12-21_final
2019-01-22 11:46:50	ga_ls8c_ard_3-0-0_114080_2019-01-22_final
2019-02-07 11:46:47	ga_ls8c_ard_3-0-0_114080_2019-02-07_final
2019-03-11 11:46:38	ga_ls8c_ard_3-1-0_114080_2019-03-11_final
2019-05-14 11:46:35	ga_ls8c_ard_3-0-0_114080_2019-05-14_final
2019-05-30 11:46:44	ga_ls8c_ard_3-0-0_114080_2019-05-30_final
2019-07-17 11:46:58	ga_ls8c_ard_3-1-0_114080_2019-07-17_final
2019-08-02 11:47:05	ga_ls8c_ard_3-1-0_114080_2019-08-02_final
2019-08-18 11:47:10	ga_ls8c_ard_3-1-0_114080_2019-08-18_final
2019-09-03 11:47:14	ga_ls8c_ard_3-1-0_114080_2019-09-03_final
2019-09-19 11:47:19	ga_ls8c_ard_3-1-0_114080_2019-09-19_final
2019-10-05 11:47:23	ga_ls8c_ard_3-1-0_114080_2019-10-05_final
2019-10-21 11:47:25	ga_ls8c_ard_3-1-0_114080_2019-10-21_final
2019-11-06 11:47:24	ga_ls8c_ard_3-1-0_114080_2019-11-06_final
2019-11-22 11:47:20	ga_ls8c_ard_3-1-0_114080_2019-11-22_final
2019-12-08 11:47:20	ga_ls8c_ard_3-1-0_114080_2019-12-08_final
2019-12-24 11:47:17	ga_ls8c_ard_3-1-0_114080_2019-12-24_final
2020-01-09 11:47:13	ga_ls8c_ard_3-1-0_114080_2020-01-09_final
2020-01-25 11:47:09	ga_ls8c_ard_3-1-0_114080_2020-01-25_final
2020-02-10 11:47:04	ga_ls8c_ard_3-1-0_114080_2020-02-10_final
2020-03-13 11:46:54	ga_ls8c_ard_3-1-0_114080_2020-03-13_final
2020-03-29 11:46:45	ga_ls8c_ard_3-1-0_114080_2020-03-29_final
2020-04-14 11:46:38	ga_ls8c_ard_3-1-0_114080_2020-04-14_final
2020-04-30 11:46:30	ga_ls8c_ard_3-1-0_114080_2020-04-30_final
2020-07-03 11:46:49	ga_ls8c_ard_3-1-0_114080_2020-07-03_final
2020-08-04 11:46:59	ga_ls8c_ard_3-1-0_114080_2020-08-04_final
2020-08-20 11:47:05	ga_ls8c_ard_3-1-0_114080_2020-08-20_final
2020-09-05 11:47:12	ga_ls8c_ard_3-1-0_114080_2020-09-05_final
2020-09-21 11:47:18	ga_ls8c_ard_3-1-0_114080_2020-09-21_final
2020-10-07 11:47:21	ga_ls8c_ard_3-1-0_114080_2020-10-07_final
2020-10-23 11:47:21	ga_ls8c_ard_3-1-0_114080_2020-10-23_final
2020-11-24 11:47:21	ga_ls8c_ard_3-1-0_114080_2020-11-24_final
2020-12-10 11:47:22	ga_ls8c_ard_3-1-0_114080_2020-12-10_final
2020-12-26 11:47:20	ga_ls8c_ard_3-2-0_114080_2020-12-26_final
2021-01-11 11:47:14	ga_ls8c_ard_3-2-0_114080_2021-01-11_final
2021-01-27 11:47:10	ga_ls8c_ard_3-2-0_114080_2021-01-27_final
2021-02-12 11:47:07	ga_ls8c_ard_3-2-0_114080_2021-02-12_final
2021-02-28 11:47:01	ga_ls8c_ard_3-2-0_114080_2021-02-28_final
2021-03-16 11:46:52	ga_ls8c_ard_3-2-0_114080_2021-03-16_final
2021-04-01 11:46:48	ga_ls8c_ard_3-2-0_114080_2021-04-01_final
2021-04-17 11:46:42	ga_ls8c_ard_3-2-0_114080_2021-04-17_final
2021-05-03 11:46:32	ga_ls8c_ard_3-2-0_114080_2021-05-03_final
2021-05-19 11:46:39	ga_ls8c_ard_3-2-0_114080_2021-05-19_final
2021-06-04 11:46:47	ga_ls8c_ard_3-2-0_114080_2021-06-04_final
2021-06-20 11:46:53	ga_ls8c_ard_3-2-0_114080_2021-06-20_final
2021-07-06 11:46:55	ga_ls8c_ard_3-2-0_114080_2021-07-06_final
2021-07-22 11:47:00	ga_ls8c_ard_3-2-0_114080_2021-07-22_final
2021-08-07 11:47:07	ga_ls8c_ard_3-2-0_114080_2021-08-07_final
2021-08-23 11:47:12	ga_ls8c_ard_3-2-0_114080_2021-08-23_final
2021-09-08 11:47:17	ga_ls8c_ard_3-2-0_114080_2021-09-08_final
2021-09-24 11:47:20	ga_ls8c_ard_3-2-0_114080_2021-09-24_final
2021-10-10 11:47:26	ga_ls8c_ard_3-2-0_114080_2021-10-10_final
2021-10-26 11:47:27	ga_ls8c_ard_3-2-0_114080_2021-10-26_final
2021-11-11 11:47:24	ga_ls8c_ard_3-2-0_114080_2021-11-11_final
2021-11-27 11:47:23	ga_ls8c_ard_3-2-0_114080_2021-11-27_final
2021-12-13 11:47:22	ga_ls8c_ard_3-2-1_114080_2021-12-13_final
2021-12-29 11:47:17	ga_ls8c_ard_3-2-1_114080_2021-12-29_final
2022-01-14 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-01-14_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_final
2022-02-15 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-02-15_final
2022-03-03 11:47:02	ga_ls8c_ard_3-2-1_114080_2022-03-03_final
2022-03-19 11:46:55	ga_ls8c_ard_3-2-1_114080_2022-03-19_final
2022-04-04 11:46:46	ga_ls8c_ard_3-2-1_114080_2022-04-04_final
2022-04-20 11:46:51	ga_ls8c_ard_3-2-1_114080_2022-04-20_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-22 11:46:58	ga_ls8c_ard_3-2-1_114080_2022-05-22_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-07-09 11:47:16	ga_ls8c_ard_3-2-1_114080_2022-07-09_final
2022-07-25 11:47:22	ga_ls8c_ard_3-2-1_114080_2022-07-25_final
2022-08-10 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-08-10_final
2022-08-26 11:47:33	ga_ls8c_ard_3-2-1_114080_2022-08-26_final
2022-09-11 11:47:38	ga_ls8c_ard_3-2-1_114080_2022-09-11_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-10-13 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-10-13_final
2022-10-29 11:47:39	ga_ls8c_ard_3-2-1_114080_2022-10-29_final
2022-11-14 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-14_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-16 11:47:30	ga_ls8c_ard_3-2-1_114080_2022-12-16_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-02-02 11:47:24	ga_ls8c_ard_3-2-1_114080_2023-02-02_final
2023-02-02 11:47:24	ga_ls8c_ard_3-2-1_114080_2023-02-02_nrt
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-04-07 11:46:41	ga_ls8c_ard_3-2-1_114080_2023-04-07_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-25 11:46:20	ga_ls8c_ard_3-2-1_114080_2023-05-25_final
2023-06-10 11:46:26	ga_ls8c_ard_3-2-1_114080_2023-06-10_final
2023-06-26 11:46:33	ga_ls8c_ard_3-2-1_114080_2023-06-26_final
2023-07-12 11:46:43	ga_ls8c_ard_3-2-1_114080_2023-07-12_final
2023-07-28 11:46:50	ga_ls8c_ard_3-2-1_114080_2023-07-28_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-29 11:47:01	ga_ls8c_ard_3-2-1_114080_2023-08-29_final
2023-09-14 11:47:04	ga_ls8c_ard_3-2-1_114080_2023-09-14_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