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
2014-08-08 09:38:15	ga_ls8c_ard_3-0-0_094067_2014-08-08_final
2014-09-06 09:16:14	ga_ls8c_ard_3-0-0_089089_2014-09-05_final
2014-09-09 09:38:22	ga_ls8c_ard_3-0-0_094067_2014-09-09_final
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-17 09:32:15	ga_ls8c_ard_3-0-0_093068_2018-02-17_final
2018-02-17 09:33:26	ga_ls8c_ard_3-0-0_093071_2018-02-17_final
2018-02-17 09:33:50	ga_ls8c_ard_3-0-0_093072_2018-02-17_final
2018-07-29 09:22:33	ga_ls8c_ard_3-0-0_091076_2018-07-28_final
2018-07-29 09:22:56	ga_ls8c_ard_3-0-0_091077_2018-07-28_final
2018-07-29 09:23:20	ga_ls8c_ard_3-0-0_091078_2018-07-28_final
2018-07-29 09:23:44	ga_ls8c_ard_3-0-0_091079_2018-07-28_final
2018-07-29 09:24:08	ga_ls8c_ard_3-0-0_091080_2018-07-28_final
2018-07-29 09:24:32	ga_ls8c_ard_3-0-0_091081_2018-07-28_final
2018-07-31 09:13:24	ga_ls8c_ard_3-0-0_089084_2018-07-30_final
2018-07-31 09:13:48	ga_ls8c_ard_3-0-0_089085_2018-07-30_final
2018-07-31 09:14:12	ga_ls8c_ard_3-0-0_089086_2018-07-30_final
2018-07-31 09:14:36	ga_ls8c_ard_3-0-0_089087_2018-07-30_final
2018-07-31 09:15:00	ga_ls8c_ard_3-0-0_089088_2018-07-30_final
2018-07-31 09:15:24	ga_ls8c_ard_3-0-0_089089_2018-07-30_final
2018-08-19 09:37:41	ga_ls8c_ard_3-0-0_094067_2018-08-19_final
2018-09-06 09:27:03	ga_ls8c_ard_3-0-0_092071_2018-09-05_final
2018-09-06 09:27:27	ga_ls8c_ard_3-0-0_092072_2018-09-05_final
2018-09-06 09:27:51	ga_ls8c_ard_3-0-0_092073_2018-09-05_final
2018-09-06 09:28:14	ga_ls8c_ard_3-0-0_092074_2018-09-05_final
2018-09-06 09:28:38	ga_ls8c_ard_3-0-0_092075_2018-09-05_final
2018-09-06 09:29:02	ga_ls8c_ard_3-0-0_092076_2018-09-05_final
2018-09-06 09:29:26	ga_ls8c_ard_3-0-0_092077_2018-09-05_final
2018-09-08 09:18:17	ga_ls8c_ard_3-0-0_090080_2018-09-07_final
2018-09-08 09:18:41	ga_ls8c_ard_3-0-0_090081_2018-09-07_final
2018-09-08 09:19:05	ga_ls8c_ard_3-0-0_090082_2018-09-07_final
2018-09-08 09:19:29	ga_ls8c_ard_3-0-0_090083_2018-09-07_final
2018-09-08 09:19:53	ga_ls8c_ard_3-0-0_090084_2018-09-07_final
2018-09-08 09:20:17	ga_ls8c_ard_3-0-0_090085_2018-09-07_final
2018-09-13 09:33:15	ga_ls8c_ard_3-0-0_093071_2018-09-13_final
2018-09-13 09:33:39	ga_ls8c_ard_3-0-0_093072_2018-09-13_final
2018-09-15 09:22:54	ga_ls8c_ard_3-0-0_091076_2018-09-14_final
2018-09-15 09:23:18	ga_ls8c_ard_3-0-0_091077_2018-09-14_final
2018-09-15 09:23:42	ga_ls8c_ard_3-0-0_091078_2018-09-14_final
2018-09-15 09:24:06	ga_ls8c_ard_3-0-0_091079_2018-09-14_final
2018-09-15 09:24:30	ga_ls8c_ard_3-0-0_091080_2018-09-14_final
2018-09-15 09:24:54	ga_ls8c_ard_3-0-0_091081_2018-09-14_final
2018-09-24 09:18:22	ga_ls8c_ard_3-0-0_090080_2018-09-23_final
2018-09-24 09:18:46	ga_ls8c_ard_3-0-0_090081_2018-09-23_final
2018-09-24 09:19:10	ga_ls8c_ard_3-0-0_090082_2018-09-23_final
2018-09-24 09:19:34	ga_ls8c_ard_3-0-0_090083_2018-09-23_final
2018-09-24 09:19:58	ga_ls8c_ard_3-0-0_090084_2018-09-23_final
2018-09-24 09:20:22	ga_ls8c_ard_3-0-0_090085_2018-09-23_final
2018-10-26 09:18:35	ga_ls8c_ard_3-0-0_090080_2018-10-25_final
2018-10-26 09:18:59	ga_ls8c_ard_3-0-0_090081_2018-10-25_final
2018-10-26 09:19:23	ga_ls8c_ard_3-0-0_090082_2018-10-25_final
2018-10-26 09:19:47	ga_ls8c_ard_3-0-0_090083_2018-10-25_final
2018-10-26 09:20:11	ga_ls8c_ard_3-0-0_090084_2018-10-25_final
2018-10-26 09:20:35	ga_ls8c_ard_3-0-0_090085_2018-10-25_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-11-05_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-13 09:23:27	ga_ls8c_ard_3-2-1_091075_2022-11-12_final
2022-11-13 09:23:51	ga_ls8c_ard_3-2-1_091076_2022-11-12_final
2022-11-13 09:24:15	ga_ls8c_ard_3-2-1_091077_2022-11-12_final
2022-11-13 09:24:39	ga_ls8c_ard_3-2-1_091078_2022-11-12_final
2022-11-13 09:25:03	ga_ls8c_ard_3-2-1_091079_2022-11-12_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-13 09:25:51	ga_ls8c_ard_3-2-1_091081_2022-11-12_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-29 09:23:26	ga_ls8c_ard_3-2-1_091075_2022-11-28_final
2022-11-29 09:23:50	ga_ls8c_ard_3-2-1_091076_2022-11-28_final
2022-11-29 09:24:14	ga_ls8c_ard_3-2-1_091077_2022-11-28_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-29 09:25:50	ga_ls8c_ard_3-2-1_091081_2022-11-28_final
2022-12-17 09:14:34	ga_ls8c_ard_3-2-1_089084_2022-12-16_final
2022-12-17 09:14:58	ga_ls8c_ard_3-2-1_089085_2022-12-16_final
2022-12-17 09:15:22	ga_ls8c_ard_3-2-1_089086_2022-12-16_final
2022-12-17 09:16:10	ga_ls8c_ard_3-2-1_089088_2022-12-16_final
2022-12-17 09:16:34	ga_ls8c_ard_3-2-1_089089_2022-12-16_final
2023-02-03 09:16:05	ga_ls8c_ard_3-2-1_089088_2023-02-02_final
2023-02-03 09:16:29	ga_ls8c_ard_3-2-1_089089_2023-02-02_final
2023-04-13 09:27:01	ga_ls8c_ard_3-2-1_092071_2023-04-12_final
2023-04-13 09:27:25	ga_ls8c_ard_3-2-1_092072_2023-04-12_final
2023-04-13 09:27:49	ga_ls8c_ard_3-2-1_092073_2023-04-12_final
2023-04-13 09:28:13	ga_ls8c_ard_3-2-1_092074_2023-04-12_final
2023-04-13 09:28:37	ga_ls8c_ard_3-2-1_092075_2023-04-12_final
2023-04-13 09:29:01	ga_ls8c_ard_3-2-1_092076_2023-04-12_final
2023-04-13 09:29:25	ga_ls8c_ard_3-2-1_092077_2023-04-12_final
2023-04-15 09:18:15	ga_ls8c_ard_3-2-1_090080_2023-04-14_final
2023-04-15 09:18:39	ga_ls8c_ard_3-2-1_090081_2023-04-14_final
2024-01-28 09:18:42	ga_ls8c_ard_3-2-1_090080_2024-01-27_final
2024-01-28 09:19:06	ga_ls8c_ard_3-2-1_090081_2024-01-27_final
2024-01-28 09:19:30	ga_ls8c_ard_3-2-1_090082_2024-01-27_final
2024-01-28 09:19:54	ga_ls8c_ard_3-2-1_090083_2024-01-27_final
2024-01-28 09:20:18	ga_ls8c_ard_3-2-1_090084_2024-01-27_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