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
2018-03-05 11:11:24	ga_ls8c_ard_3-0-0_109069_2018-03-05_final
2018-04-06 11:11:08	ga_ls8c_ard_3-0-0_109069_2018-04-06_final
2018-05-24 11:10:38	ga_ls8c_ard_3-0-0_109069_2018-05-24_final
2018-07-11 11:10:52	ga_ls8c_ard_3-0-0_109069_2018-07-11_final
2018-07-27 11:10:58	ga_ls8c_ard_3-0-0_109069_2018-07-27_final
2018-11-16 11:11:40	ga_ls8c_ard_3-0-0_109069_2018-11-16_final
2019-01-03 11:11:36	ga_ls8c_ard_3-0-0_109069_2019-01-03_final
2019-03-08 11:11:22	ga_ls8c_ard_3-1-0_109069_2019-03-08_final
2019-04-09 11:11:14	ga_ls8c_ard_3-1-0_109069_2019-04-09_final
2019-05-11 11:11:15	ga_ls8c_ard_3-0-0_109069_2019-05-11_final
2019-08-31 11:11:56	ga_ls8c_ard_3-1-0_109069_2019-08-31_final
2019-11-03 11:12:07	ga_ls8c_ard_3-1-0_109069_2019-11-03_final
2019-12-05 11:12:03	ga_ls8c_ard_3-1-0_109069_2019-12-05_final
2020-01-06 11:11:56	ga_ls8c_ard_3-1-0_109069_2020-01-06_final
2020-02-07 11:11:47	ga_ls8c_ard_3-1-0_109069_2020-02-07_final
2020-04-11 11:11:21	ga_ls8c_ard_3-1-0_109069_2020-04-11_final
2020-04-27 11:11:14	ga_ls8c_ard_3-1-0_109069_2020-04-27_final
2020-05-13 11:11:08	ga_ls8c_ard_3-1-0_109069_2020-05-13_final
2020-05-29 11:11:12	ga_ls8c_ard_3-1-0_109069_2020-05-29_final
2020-06-14 11:11:22	ga_ls8c_ard_3-1-0_109069_2020-06-14_final
2020-06-30 11:11:30	ga_ls8c_ard_3-1-0_109069_2020-06-30_final
2020-07-16 11:11:36	ga_ls8c_ard_3-1-0_109069_2020-07-16_final
2020-08-01 11:11:41	ga_ls8c_ard_3-1-0_109069_2020-08-01_final
2020-08-17 11:11:45	ga_ls8c_ard_3-1-0_109069_2020-08-17_final
2020-09-02 11:11:54	ga_ls8c_ard_3-1-0_109069_2020-09-02_final
2020-09-18 11:11:59	ga_ls8c_ard_3-1-0_109069_2020-09-18_final
2020-10-04 11:12:03	ga_ls8c_ard_3-1-0_109069_2020-10-04_final
2020-10-20 11:12:04	ga_ls8c_ard_3-1-0_109069_2020-10-20_final
2020-11-21 11:12:03	ga_ls8c_ard_3-1-0_109069_2020-11-21_final
2020-12-07 11:12:05	ga_ls8c_ard_3-1-0_109069_2020-12-07_final
2021-03-13 11:11:36	ga_ls8c_ard_3-2-0_109069_2021-03-13_final
2021-03-29 11:11:31	ga_ls8c_ard_3-2-0_109069_2021-03-29_final
2021-04-14 11:11:26	ga_ls8c_ard_3-2-0_109069_2021-04-14_final
2021-04-30 11:11:17	ga_ls8c_ard_3-2-0_109069_2021-04-30_final
2021-05-16 11:11:19	ga_ls8c_ard_3-2-0_109069_2021-05-16_final
2021-06-01 11:11:28	ga_ls8c_ard_3-2-0_109069_2021-06-01_final
2021-06-17 11:11:34	ga_ls8c_ard_3-2-0_109069_2021-06-17_final
2021-07-03 11:11:38	ga_ls8c_ard_3-2-0_109069_2021-07-03_final
2021-07-19 11:11:40	ga_ls8c_ard_3-2-0_109069_2021-07-19_final
2021-08-04 11:11:48	ga_ls8c_ard_3-2-0_109069_2021-08-04_final
2021-08-20 11:11:54	ga_ls8c_ard_3-2-0_109069_2021-08-20_final
2021-09-05 11:11:59	ga_ls8c_ard_3-2-0_109069_2021-09-05_final
2021-09-21 11:12:02	ga_ls8c_ard_3-2-0_109069_2021-09-21_final
2021-10-07 11:12:07	ga_ls8c_ard_3-2-0_109069_2021-10-07_final
2021-10-23 11:12:10	ga_ls8c_ard_3-2-0_109069_2021-10-23_final
2021-11-08 11:12:08	ga_ls8c_ard_3-2-0_109069_2021-11-08_final
2021-11-24 11:12:05	ga_ls8c_ard_3-2-0_109069_2021-11-24_final
2021-12-10 11:12:05	ga_ls8c_ard_3-2-1_109069_2021-12-10_final
2021-12-26 11:12:01	ga_ls8c_ard_3-2-1_109069_2021-12-26_final
2022-01-11 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-01-11_final
2022-01-27 11:11:52	ga_ls8c_ard_3-2-1_109069_2022-01-27_final
2022-02-12 11:11:50	ga_ls8c_ard_3-2-1_109069_2022-02-12_final
2022-02-28 11:11:45	ga_ls8c_ard_3-2-1_109069_2022-02-28_final
2022-03-16 11:11:39	ga_ls8c_ard_3-2-1_109069_2022-03-16_final
2022-04-01 11:11:28	ga_ls8c_ard_3-2-1_109069_2022-04-01_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-05-03 11:11:33	ga_ls8c_ard_3-2-1_109069_2022-05-03_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-07-06 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-07-06_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-09-08 11:12:19	ga_ls8c_ard_3-2-1_109069_2022-09-08_final
2022-09-24 11:12:23	ga_ls8c_ard_3-2-1_109069_2022-09-24_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-27 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-11-27_final
2022-12-13 11:12:14	ga_ls8c_ard_3-2-1_109069_2022-12-13_final
2022-12-29 11:12:08	ga_ls8c_ard_3-2-1_109069_2022-12-29_final
2023-01-14 11:12:04	ga_ls8c_ard_3-2-1_109069_2023-01-14_final
2023-01-30 11:12:07	ga_ls8c_ard_3-2-1_109069_2023-01-30_final
2023-02-15 11:12:00	ga_ls8c_ard_3-2-1_109069_2023-02-15_final
2023-03-03 11:11:47	ga_ls8c_ard_3-2-1_109069_2023-03-03_final
2023-03-19 11:11:39	ga_ls8c_ard_3-2-1_109069_2023-03-19_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-05-06 11:11:08	ga_ls8c_ard_3-2-1_109069_2023-05-06_final
2023-05-22 11:11:01	ga_ls8c_ard_3-2-1_109069_2023-05-22_final
2023-06-07 11:11:07	ga_ls8c_ard_3-2-1_109069_2023-06-07_final
2023-06-23 11:11:12	ga_ls8c_ard_3-2-1_109069_2023-06-23_final
2023-07-09 11:11:25	ga_ls8c_ard_3-2-1_109069_2023-07-09_final
2023-07-25 11:11:30	ga_ls8c_ard_3-2-1_109069_2023-07-25_final
2023-08-10 11:11:35	ga_ls8c_ard_3-2-1_109069_2023-08-10_final
2023-08-26 11:11:44	ga_ls8c_ard_3-2-1_109069_2023-08-26_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-27 11:11:50	ga_ls8c_ard_3-2-1_109069_2023-09-27_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-29 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-10-29_final
2023-11-14 11:11:55	ga_ls8c_ard_3-2-1_109069_2023-11-14_final
2023-11-30 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-11-30_final
2023-12-16 11:11:56	ga_ls8c_ard_3-2-1_109069_2023-12-16_final
2024-01-01 11:11:52	ga_ls8c_ard_3-2-1_109069_2024-01-01_final
2024-01-17 11:11:51	ga_ls8c_ard_3-2-1_109069_2024-01-17_final
2024-02-02 11:11:48	ga_ls8c_ard_3-2-1_109069_2024-02-02_final
2024-02-18 11:11:48	ga_ls8c_ard_3-2-1_109069_2024-02-18_final
2024-03-05 11:11:38	ga_ls8c_ard_3-2-1_109069_2024-03-05_final
2024-03-21 11:11:29	ga_ls8c_ard_3-2-1_109069_2024-03-21_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