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
2019-02-12 10:26:26	ga_ls8c_ard_3-0-0_101080_2019-02-12_final
2019-02-28 10:26:22	ga_ls8c_ard_3-0-0_101080_2019-02-28_final
2019-03-16 10:26:16	ga_ls8c_ard_3-1-0_101080_2019-03-16_final
2019-04-01 10:26:13	ga_ls8c_ard_3-1-0_101080_2019-04-01_final
2019-05-19 10:26:17	ga_ls8c_ard_3-0-0_101080_2019-05-19_final
2019-06-04 10:26:26	ga_ls8c_ard_3-0-0_101080_2019-06-04_final
2019-06-20 10:26:32	ga_ls8c_ard_3-1-0_101080_2019-06-20_final
2019-07-06 10:26:36	ga_ls8c_ard_3-1-0_101080_2019-07-06_final
2019-08-07 10:26:46	ga_ls8c_ard_3-1-0_101080_2019-08-07_final
2019-08-23 10:26:51	ga_ls8c_ard_3-1-0_101080_2019-08-23_final
2019-10-10 10:27:03	ga_ls8c_ard_3-1-0_101080_2019-10-10_final
2019-11-11 10:27:02	ga_ls8c_ard_3-1-0_101080_2019-11-11_final
2019-11-27 10:27:00	ga_ls8c_ard_3-1-0_101080_2019-11-27_final
2020-01-14 10:26:51	ga_ls8c_ard_3-1-0_101080_2020-01-14_final
2020-01-30 10:26:47	ga_ls8c_ard_3-1-0_101080_2020-01-30_final
2020-02-15 10:26:43	ga_ls8c_ard_3-1-0_101080_2020-02-15_final
2020-03-18 10:26:31	ga_ls8c_ard_3-1-0_101080_2020-03-18_final
2020-04-03 10:26:21	ga_ls8c_ard_3-1-0_101080_2020-04-03_final
2020-04-19 10:26:15	ga_ls8c_ard_3-1-0_101080_2020-04-19_final
2020-05-21 10:26:07	ga_ls8c_ard_3-1-0_101080_2020-05-21_final
2020-06-06 10:26:14	ga_ls8c_ard_3-1-0_101080_2020-06-06_final
2020-07-08 10:26:30	ga_ls8c_ard_3-1-0_101080_2020-07-08_final
2020-07-24 10:26:36	ga_ls8c_ard_3-1-0_101080_2020-07-24_final
2020-08-09 10:26:39	ga_ls8c_ard_3-1-0_101080_2020-08-09_final
2020-10-12 10:27:01	ga_ls8c_ard_3-1-0_101080_2020-10-12_final
2020-10-28 10:27:00	ga_ls8c_ard_3-1-0_101080_2020-10-28_final
2020-11-29 10:27:01	ga_ls8c_ard_3-1-0_101080_2020-11-29_final
2020-12-15 10:27:01	ga_ls8c_ard_3-1-0_101080_2020-12-15_final
2021-02-01 10:26:48	ga_ls8c_ard_3-2-0_101080_2021-02-01_final
2021-03-05 10:26:38	ga_ls8c_ard_3-2-0_101080_2021-03-05_final
2021-03-21 10:26:29	ga_ls8c_ard_3-2-0_101080_2021-03-21_final
2021-04-06 10:26:26	ga_ls8c_ard_3-2-0_101080_2021-04-06_final
2021-04-22 10:26:19	ga_ls8c_ard_3-2-0_101080_2021-04-22_final
2021-05-08 10:26:11	ga_ls8c_ard_3-2-0_101080_2021-05-08_final
2021-05-24 10:26:21	ga_ls8c_ard_3-2-0_101080_2021-05-24_final
2021-06-09 10:26:29	ga_ls8c_ard_3-2-0_101080_2021-06-09_final
2021-06-25 10:26:33	ga_ls8c_ard_3-2-0_101080_2021-06-25_final
2021-07-11 10:26:35	ga_ls8c_ard_3-2-0_101080_2021-07-11_final
2021-07-27 10:26:42	ga_ls8c_ard_3-2-0_101080_2021-07-27_final
2021-08-12 10:26:48	ga_ls8c_ard_3-2-0_101080_2021-08-12_final
2021-08-28 10:26:53	ga_ls8c_ard_3-2-0_101080_2021-08-28_final
2021-09-13 10:26:57	ga_ls8c_ard_3-2-0_101080_2021-09-13_final
2021-09-29 10:27:01	ga_ls8c_ard_3-2-0_101080_2021-09-29_final
2021-10-15 10:27:06	ga_ls8c_ard_3-2-0_101080_2021-10-15_final
2021-10-31 10:27:06	ga_ls8c_ard_3-2-0_101080_2021-10-31_final
2021-11-16 10:27:01	ga_ls8c_ard_3-2-0_101080_2021-11-16_final
2021-12-02 10:27:02	ga_ls8c_ard_3-2-0_101080_2021-12-02_final
2021-12-18 10:27:01	ga_ls8c_ard_3-2-1_101080_2021-12-18_final
2022-01-03 10:26:55	ga_ls8c_ard_3-2-1_101080_2022-01-03_final
2022-01-19 10:26:53	ga_ls8c_ard_3-2-1_101080_2022-01-19_final
2022-02-04 10:26:49	ga_ls8c_ard_3-2-1_101080_2022-02-04_final
2022-02-20 10:26:42	ga_ls8c_ard_3-2-1_101080_2022-02-20_final
2022-03-08 10:26:40	ga_ls8c_ard_3-2-1_101080_2022-03-08_final
2022-03-24 10:26:30	ga_ls8c_ard_3-2-1_101080_2022-03-24_final
2022-04-09 10:26:29	ga_ls8c_ard_3-2-1_101080_2022-04-09_final
2022-04-25 10:26:28	ga_ls8c_ard_3-2-1_101080_2022-04-25_final
2022-05-11 10:26:35	ga_ls8c_ard_3-2-1_101080_2022-05-11_final
2022-05-27 10:26:36	ga_ls8c_ard_3-2-1_101080_2022-05-27_final
2022-06-12 10:26:49	ga_ls8c_ard_3-2-1_101080_2022-06-12_final
2022-06-28 10:26:55	ga_ls8c_ard_3-2-1_101080_2022-06-28_final
2022-07-14 10:26:54	ga_ls8c_ard_3-2-1_101080_2022-07-14_final
2022-07-30 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-07-30_final
2022-08-15 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-15_final
2022-08-31 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-08-31_final
2022-09-16 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-09-16_final
2022-10-02 10:27:18	ga_ls8c_ard_3-2-1_101080_2022-10-02_final
2022-10-18 10:27:13	ga_ls8c_ard_3-2-1_101080_2022-10-18_final
2022-11-03 10:27:19	ga_ls8c_ard_3-2-1_101080_2022-11-03_final
2022-11-19 10:27:12	ga_ls8c_ard_3-2-1_101080_2022-11-19_final
2022-12-05 10:27:14	ga_ls8c_ard_3-2-1_101080_2022-12-05_final
2022-12-21 10:27:05	ga_ls8c_ard_3-2-1_101080_2022-12-21_final
2023-01-06 10:27:05	ga_ls8c_ard_3-2-1_101080_2023-01-06_final
2023-01-22 10:27:01	ga_ls8c_ard_3-2-1_101080_2023-01-22_final
2023-02-07 10:27:02	ga_ls8c_ard_3-2-1_101080_2023-02-07_final
2023-02-23 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-02-23_final
2023-03-11 10:26:39	ga_ls8c_ard_3-2-1_101080_2023-03-11_final
2023-03-27 10:26:30	ga_ls8c_ard_3-2-1_101080_2023-03-27_final
2023-04-12 10:26:14	ga_ls8c_ard_3-2-1_101080_2023-04-12_final
2023-04-28 10:26:11	ga_ls8c_ard_3-2-1_101080_2023-04-28_final
2023-05-14 10:25:58	ga_ls8c_ard_3-2-1_101080_2023-05-14_final
2023-05-30 10:25:59	ga_ls8c_ard_3-2-1_101080_2023-05-30_final
2023-06-15 10:26:08	ga_ls8c_ard_3-2-1_101080_2023-06-15_final
2023-07-01 10:26:17	ga_ls8c_ard_3-2-1_101080_2023-07-01_final
2023-07-17 10:26:23	ga_ls8c_ard_3-2-1_101080_2023-07-17_final
2023-08-02 10:26:31	ga_ls8c_ard_3-2-1_101080_2023-08-02_final
2023-08-18 10:26:38	ga_ls8c_ard_3-2-1_101080_2023-08-18_final
2023-09-03 10:26:40	ga_ls8c_ard_3-2-1_101080_2023-09-03_final
2023-09-19 10:26:45	ga_ls8c_ard_3-2-1_101080_2023-09-19_final
2023-10-05 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-10-05_final
2023-10-21 10:26:50	ga_ls8c_ard_3-2-1_101080_2023-10-21_final
2023-11-06 10:26:52	ga_ls8c_ard_3-2-1_101080_2023-11-06_final
2023-11-22 10:26:55	ga_ls8c_ard_3-2-1_101080_2023-11-22_final
2023-12-08 10:26:47	ga_ls8c_ard_3-2-1_101080_2023-12-08_final
2023-12-24 10:26:53	ga_ls8c_ard_3-2-1_101080_2023-12-24_final
2024-01-09 10:26:47	ga_ls8c_ard_3-2-1_101080_2024-01-09_final
2024-01-25 10:26:42	ga_ls8c_ard_3-2-1_101080_2024-01-25_final
2024-02-10 10:26:47	ga_ls8c_ard_3-2-1_101080_2024-02-10_final
2024-02-26 10:26:42	ga_ls8c_ard_3-2-1_101080_2024-02-26_final
2024-03-13 10:26:31	ga_ls8c_ard_3-2-1_101080_2024-03-13_nrt
2024-03-29 10:26:16	ga_ls8c_ard_3-2-1_101080_2024-03-29_nrt

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