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
2019-09-27 09:23:01	ga_ls8c_ard_3-1-0_090090_2019-09-26_final
2019-10-13 09:23:04	ga_ls8c_ard_3-1-0_090090_2019-10-12_final
2019-10-29 09:23:05	ga_ls8c_ard_3-1-0_090090_2019-10-28_final
2019-11-14 09:23:02	ga_ls8c_ard_3-1-0_090090_2019-11-13_final
2019-11-30 09:23:00	ga_ls8c_ard_3-1-0_090090_2019-11-29_final
2020-01-01 09:22:54	ga_ls8c_ard_3-1-0_090090_2019-12-31_final
2020-01-17 09:22:51	ga_ls8c_ard_3-1-0_090090_2020-01-16_final
2020-02-02 09:22:46	ga_ls8c_ard_3-1-0_090090_2020-02-01_final
2020-02-18 09:22:42	ga_ls8c_ard_3-1-0_090090_2020-02-17_final
2020-03-05 09:22:37	ga_ls8c_ard_3-1-0_090090_2020-03-04_final
2020-03-21 09:22:30	ga_ls8c_ard_3-1-0_090090_2020-03-20_final
2020-04-06 09:22:21	ga_ls8c_ard_3-1-0_090090_2020-04-05_final
2020-04-22 09:22:14	ga_ls8c_ard_3-1-0_090090_2020-04-21_final
2020-05-08 09:22:05	ga_ls8c_ard_3-1-0_090090_2020-05-07_final
2020-05-24 09:22:08	ga_ls8c_ard_3-1-0_090090_2020-05-23_final
2020-06-09 09:22:16	ga_ls8c_ard_3-1-0_090090_2020-06-08_final
2020-06-25 09:22:25	ga_ls8c_ard_3-1-0_090090_2020-06-24_final
2020-07-11 09:22:32	ga_ls8c_ard_3-1-0_090090_2020-07-10_final
2020-07-27 09:22:37	ga_ls8c_ard_3-1-0_090090_2020-07-26_final
2020-09-13 09:22:55	ga_ls8c_ard_3-1-0_090090_2020-09-12_final
2020-09-29 09:23:00	ga_ls8c_ard_3-1-0_090090_2020-09-28_final
2020-10-15 09:23:01	ga_ls8c_ard_3-1-0_090090_2020-10-14_final
2020-10-31 09:23:00	ga_ls8c_ard_3-1-0_090090_2020-10-30_final
2020-11-16 09:22:59	ga_ls8c_ard_3-1-0_090090_2020-11-15_final
2020-12-02 09:23:02	ga_ls8c_ard_3-1-0_090090_2020-12-01_final
2020-12-18 09:23:02	ga_ls8c_ard_3-2-0_090090_2020-12-17_final
2021-01-03 09:22:57	ga_ls8c_ard_3-2-0_090090_2021-01-02_final
2021-01-19 09:22:50	ga_ls8c_ard_3-2-0_090090_2021-01-18_final
2021-02-04 09:22:48	ga_ls8c_ard_3-2-0_090090_2021-02-03_final
2021-03-08 09:22:37	ga_ls8c_ard_3-2-0_090090_2021-03-07_final
2021-03-24 09:22:30	ga_ls8c_ard_3-2-0_090090_2021-03-23_final
2021-04-09 09:22:25	ga_ls8c_ard_3-2-0_090090_2021-04-08_final
2021-04-25 09:22:18	ga_ls8c_ard_3-2-0_090090_2021-04-24_final
2021-05-11 09:22:13	ga_ls8c_ard_3-2-0_090090_2021-05-10_final
2021-05-27 09:22:23	ga_ls8c_ard_3-2-0_090090_2021-05-26_final
2021-06-12 09:22:30	ga_ls8c_ard_3-2-0_090090_2021-06-11_final
2021-06-28 09:22:34	ga_ls8c_ard_3-2-0_090090_2021-06-27_final
2021-07-14 09:22:36	ga_ls8c_ard_3-2-0_090090_2021-07-13_final
2021-07-30 09:22:44	ga_ls8c_ard_3-2-0_090090_2021-07-29_final
2021-08-15 09:22:50	ga_ls8c_ard_3-2-0_090090_2021-08-14_final
2021-08-31 09:22:54	ga_ls8c_ard_3-2-0_090090_2021-08-30_final
2021-09-16 09:22:58	ga_ls8c_ard_3-2-0_090090_2021-09-15_final
2021-10-02 09:23:03	ga_ls8c_ard_3-2-0_090090_2021-10-01_final
2021-10-18 09:23:07	ga_ls8c_ard_3-2-0_090090_2021-10-17_final
2021-11-03 09:23:06	ga_ls8c_ard_3-2-0_090090_2021-11-02_final
2021-11-19 09:23:01	ga_ls8c_ard_3-2-0_090090_2021-11-18_final
2021-12-05 09:23:03	ga_ls8c_ard_3-2-0_090090_2021-12-04_final
2021-12-21 09:23:00	ga_ls8c_ard_3-2-1_090090_2021-12-20_final
2022-01-06 09:22:56	ga_ls8c_ard_3-2-1_090090_2022-01-05_final
2022-01-22 09:22:52	ga_ls8c_ard_3-2-1_090090_2022-01-21_final
2022-02-07 09:22:49	ga_ls8c_ard_3-2-1_090090_2022-02-06_final
2022-02-23 09:22:43	ga_ls8c_ard_3-2-1_090090_2022-02-22_final
2022-03-11 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-03-10_final
2022-03-27 09:22:28	ga_ls8c_ard_3-2-1_090090_2022-03-26_final
2022-04-12 09:22:31	ga_ls8c_ard_3-2-1_090090_2022-04-11_final
2022-04-28 09:22:27	ga_ls8c_ard_3-2-1_090090_2022-04-27_final
2022-05-14 09:22:37	ga_ls8c_ard_3-2-1_090090_2022-05-13_final
2022-05-30 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-05-29_final
2022-06-15 09:22:51	ga_ls8c_ard_3-2-1_090090_2022-06-14_final
2022-07-01 09:22:56	ga_ls8c_ard_3-2-1_090090_2022-06-30_final
2022-07-17 09:22:55	ga_ls8c_ard_3-2-1_090090_2022-07-16_final
2022-08-02 09:23:07	ga_ls8c_ard_3-2-1_090090_2022-08-01_final
2022-08-18 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-08-17_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-19 09:23:20	ga_ls8c_ard_3-2-1_090090_2022-09-18_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-21 09:23:16	ga_ls8c_ard_3-2-1_090090_2022-10-20_final
2022-11-06 09:23:19	ga_ls8c_ard_3-2-1_090090_2022-11-05_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-12-08 09:23:14	ga_ls8c_ard_3-2-1_090090_2022-12-07_final
2022-12-24 09:23:04	ga_ls8c_ard_3-2-1_090090_2022-12-23_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-26 09:22:44	ga_ls8c_ard_3-2-1_090090_2023-02-25_final
2023-03-14 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-03-13_final
2023-03-30 09:22:29	ga_ls8c_ard_3-2-1_090090_2023-03-29_final
2023-04-15 09:22:14	ga_ls8c_ard_3-2-1_090090_2023-04-14_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-17 09:21:57	ga_ls8c_ard_3-2-1_090090_2023-05-16_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-06-18 09:22:09	ga_ls8c_ard_3-2-1_090090_2023-06-17_final
2023-07-04 09:22:20	ga_ls8c_ard_3-2-1_090090_2023-07-03_final
2023-07-20 09:22:23	ga_ls8c_ard_3-2-1_090090_2023-07-19_final
2023-08-05 09:22:33	ga_ls8c_ard_3-2-1_090090_2023-08-04_final
2023-08-21 09:22:40	ga_ls8c_ard_3-2-1_090090_2023-08-20_final
2023-09-06 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-09-05_final
2023-09-22 09:22:45	ga_ls8c_ard_3-2-1_090090_2023-09-21_final
2023-10-08 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-10-07_final
2023-10-24 09:22:52	ga_ls8c_ard_3-2-1_090090_2023-10-23_final
2023-11-09 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-11-08_final
2023-11-25 09:22:56	ga_ls8c_ard_3-2-1_090090_2023-11-24_final
2023-12-11 09:22:50	ga_ls8c_ard_3-2-1_090090_2023-12-10_final
2023-12-27 09:22:53	ga_ls8c_ard_3-2-1_090090_2023-12-26_final
2024-01-12 09:22:49	ga_ls8c_ard_3-2-1_090090_2024-01-11_final
2024-01-28 09:22:42	ga_ls8c_ard_3-2-1_090090_2024-01-27_final
2024-02-13 09:22:46	ga_ls8c_ard_3-2-1_090090_2024-02-12_final
2024-02-29 09:22:40	ga_ls8c_ard_3-2-1_090090_2024-02-28_final
2024-03-16 09:22:30	ga_ls8c_ard_3-2-1_090090_2024-03-15_nrt
2024-04-01 09:22:18	ga_ls8c_ard_3-2-1_090090_2024-03-31_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