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
2015-06-24 09:45:56	ga_ls8c_ard_3-0-0_094088_2015-06-24_final
2015-07-10 09:46:07	ga_ls8c_ard_3-0-0_094088_2015-07-10_final
2015-07-12 09:33:46	ga_ls8c_ard_3-0-0_092088_2015-07-12_final
2015-07-12 09:34:10	ga_ls8c_ard_3-0-0_092089_2015-07-12_final
2015-07-28 09:33:51	ga_ls8c_ard_3-0-0_092088_2015-07-28_final
2015-07-28 09:34:15	ga_ls8c_ard_3-0-0_092089_2015-07-28_final
2015-08-11 09:46:17	ga_ls8c_ard_3-0-0_094088_2015-08-11_final
2015-08-13 09:33:56	ga_ls8c_ard_3-0-0_092088_2015-08-13_final
2015-08-13 09:34:20	ga_ls8c_ard_3-0-0_092089_2015-08-13_final
2015-08-27 09:46:24	ga_ls8c_ard_3-0-0_094088_2015-08-27_final
2015-08-29 09:34:27	ga_ls8c_ard_3-0-0_092089_2015-08-29_final
2015-09-19 09:52:45	ga_ls8c_ard_3-0-0_095088_2015-09-19_final
2015-10-14 09:46:37	ga_ls8c_ard_3-0-0_094088_2015-10-14_final
2015-10-16 09:34:15	ga_ls8c_ard_3-0-0_092088_2015-10-16_final
2015-10-16 09:34:39	ga_ls8c_ard_3-0-0_092089_2015-10-16_final
2015-10-27 09:15:48	ga_ls8c_ard_3-0-0_089088_2015-10-26_final
2015-10-27 09:16:12	ga_ls8c_ard_3-0-0_089089_2015-10-26_final
2015-11-15 09:46:43	ga_ls8c_ard_3-0-0_094088_2015-11-15_final
2015-11-17 09:34:46	ga_ls8c_ard_3-0-0_092089_2015-11-17_final
2018-03-16 09:21:51	ga_ls8c_ard_3-0-0_090089_2018-03-15_final
2018-04-01 09:21:44	ga_ls8c_ard_3-0-0_090089_2018-03-31_final
2018-05-03 09:21:26	ga_ls8c_ard_3-0-0_090089_2018-05-02_final
2018-05-19 09:21:15	ga_ls8c_ard_3-0-0_090089_2018-05-18_final
2018-06-23 09:51:46	ga_ls8c_ard_3-0-0_095088_2018-06-23_final
2022-05-12 09:34:09	ga_ls8c_ard_3-2-1_092088_2022-05-12_final
2022-05-12 09:34:33	ga_ls8c_ard_3-2-1_092089_2022-05-12_final
2022-05-14 09:21:49	ga_ls8c_ard_3-2-1_090088_2022-05-13_final
2022-05-14 09:22:13	ga_ls8c_ard_3-2-1_090089_2022-05-13_final
2022-05-19 09:40:22	ga_ls8c_ard_3-2-1_093088_2022-05-19_final
2022-05-21 09:28:25	ga_ls8c_ard_3-2-1_091089_2022-05-20_final
2022-05-28 09:34:10	ga_ls8c_ard_3-2-1_092088_2022-05-28_final
2022-05-28 09:34:34	ga_ls8c_ard_3-2-1_092089_2022-05-28_final
2022-05-30 09:21:51	ga_ls8c_ard_3-2-1_090088_2022-05-29_final
2022-05-30 09:22:15	ga_ls8c_ard_3-2-1_090089_2022-05-29_final
2022-06-13 09:34:24	ga_ls8c_ard_3-2-1_092088_2022-06-13_final
2022-06-13 09:34:48	ga_ls8c_ard_3-2-1_092089_2022-06-13_final
2022-06-15 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-06-14_final
2022-06-15 09:22:27	ga_ls8c_ard_3-2-1_090089_2022-06-14_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-22 09:28:17	ga_ls8c_ard_3-2-1_091088_2022-06-21_final
2022-06-22 09:28:41	ga_ls8c_ard_3-2-1_091089_2022-06-21_final
2022-06-24 09:15:56	ga_ls8c_ard_3-2-1_089088_2022-06-23_final
2022-06-24 09:16:20	ga_ls8c_ard_3-2-1_089089_2022-06-23_final
2022-06-29 09:34:29	ga_ls8c_ard_3-2-1_092088_2022-06-29_final
2022-06-29 09:34:53	ga_ls8c_ard_3-2-1_092089_2022-06-29_final
2022-07-01 09:22:32	ga_ls8c_ard_3-2-1_090089_2022-06-30_final
2022-07-06 09:40:40	ga_ls8c_ard_3-2-1_093088_2022-07-06_final
2022-07-08 09:28:43	ga_ls8c_ard_3-2-1_091089_2022-07-07_final
2022-07-10 09:15:57	ga_ls8c_ard_3-2-1_089088_2022-07-09_final
2022-07-10 09:16:21	ga_ls8c_ard_3-2-1_089089_2022-07-09_final
2022-07-15 09:34:52	ga_ls8c_ard_3-2-1_092089_2022-07-15_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_final
2022-07-17 09:22:31	ga_ls8c_ard_3-2-1_090089_2022-07-16_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-07-24 09:28:24	ga_ls8c_ard_3-2-1_091088_2022-07-23_final
2022-07-24 09:28:48	ga_ls8c_ard_3-2-1_091089_2022-07-23_final
2022-07-26 09:16:04	ga_ls8c_ard_3-2-1_089088_2022-07-25_final
2022-07-26 09:16:28	ga_ls8c_ard_3-2-1_089089_2022-07-25_final
2022-07-31 09:35:04	ga_ls8c_ard_3-2-1_092089_2022-07-31_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-02 09:22:43	ga_ls8c_ard_3-2-1_090089_2022-08-01_final
2022-08-07 09:40:54	ga_ls8c_ard_3-2-1_093088_2022-08-07_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-08-09 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-08-08_final
2022-08-11 09:16:13	ga_ls8c_ard_3-2-1_089088_2022-08-10_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-16 09:35:10	ga_ls8c_ard_3-2-1_092089_2022-08-16_final
2022-08-18 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-08-17_final
2022-08-18 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-08-17_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-27 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-08-26_final
2022-08-27 09:16:39	ga_ls8c_ard_3-2-1_089089_2022-08-26_final
2022-09-01 09:35:11	ga_ls8c_ard_3-2-1_092089_2022-09-01_final
2022-09-03 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-09-02_final
2022-09-08 09:41:00	ga_ls8c_ard_3-2-1_093088_2022-09-08_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_final
2022-09-10 09:29:04	ga_ls8c_ard_3-2-1_091089_2022-09-09_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-28 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-09-27_final
2022-10-26 09:41:03	ga_ls8c_ard_3-2-1_093088_2022-10-26_final
2022-10-28 09:29:06	ga_ls8c_ard_3-2-1_091089_2022-10-27_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-11-06 09:22:31	ga_ls8c_ard_3-2-1_090088_2022-11-05_final
2022-11-06 09:22:55	ga_ls8c_ard_3-2-1_090089_2022-11-05_final
2022-11-11 09:41:02	ga_ls8c_ard_3-2-1_093088_2022-11-11_final
2022-11-15 09:16:15	ga_ls8c_ard_3-2-1_089088_2022-11-14_final
2022-11-15 09:16:39	ga_ls8c_ard_3-2-1_089089_2022-11-14_final
2022-11-22 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-11-21_final
2022-11-29 09:29:02	ga_ls8c_ard_3-2-1_091089_2022-11-28_final
2022-12-01 09:16:40	ga_ls8c_ard_3-2-1_089089_2022-11-30_final
2022-12-06 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-12-06_final
2022-12-08 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-12-07_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-14 09:40:46	ga_ls8c_ard_3-2-1_093088_2023-01-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years