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:

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First 100 results (query limit)

Time (local)	Label
2017-07-26 09:28:23	ga_ls8c_ard_3-0-0_091089_2017-07-25_final
2017-07-28 09:16:02	ga_ls8c_ard_3-0-0_089089_2017-07-27_final
2017-08-02 09:34:37	ga_ls8c_ard_3-0-0_092089_2017-08-02_final
2017-08-04 09:22:16	ga_ls8c_ard_3-0-0_090089_2017-08-03_final
2017-08-11 09:28:30	ga_ls8c_ard_3-0-0_091089_2017-08-10_final
2017-08-13 09:15:45	ga_ls8c_ard_3-0-0_089088_2017-08-12_final
2017-08-13 09:16:09	ga_ls8c_ard_3-0-0_089089_2017-08-12_final
2017-08-18 09:34:43	ga_ls8c_ard_3-0-0_092089_2017-08-18_final
2017-08-20 09:22:21	ga_ls8c_ard_3-0-0_090089_2017-08-19_final
2017-08-27 09:28:34	ga_ls8c_ard_3-0-0_091089_2017-08-26_final
2017-08-29 09:15:48	ga_ls8c_ard_3-0-0_089088_2017-08-28_final
2017-08-29 09:16:12	ga_ls8c_ard_3-0-0_089089_2017-08-28_final
2017-09-01 09:46:43	ga_ls8c_ard_3-0-0_094088_2017-09-01_final
2017-09-03 09:34:45	ga_ls8c_ard_3-0-0_092089_2017-09-03_final
2017-09-05 09:22:00	ga_ls8c_ard_3-0-0_090088_2017-09-04_final
2017-09-05 09:22:24	ga_ls8c_ard_3-0-0_090089_2017-09-04_final
2017-09-17 09:46:44	ga_ls8c_ard_3-0-0_094088_2017-09-17_final
2017-09-19 09:34:48	ga_ls8c_ard_3-0-0_092089_2017-09-19_final
2017-09-21 09:22:27	ga_ls8c_ard_3-0-0_090089_2017-09-20_final
2017-09-24 09:52:58	ga_ls8c_ard_3-0-0_095088_2017-09-24_final
2017-09-28 09:28:41	ga_ls8c_ard_3-0-0_091089_2017-09-27_final
2017-09-30 09:15:56	ga_ls8c_ard_3-0-0_089088_2017-09-29_final
2017-09-30 09:16:20	ga_ls8c_ard_3-0-0_089089_2017-09-29_final
2017-10-14 09:28:45	ga_ls8c_ard_3-0-0_091089_2017-10-13_final
2017-10-16 09:16:24	ga_ls8c_ard_3-0-0_089089_2017-10-15_final
2017-12-08 09:34:48	ga_ls8c_ard_3-0-0_092089_2017-12-08_final
2018-01-02 09:28:37	ga_ls8c_ard_3-0-0_091089_2018-01-01_final
2018-01-30 09:52:42	ga_ls8c_ard_3-0-0_095088_2018-01-30_final
2018-02-03 09:28:20	ga_ls8c_ard_3-0-0_091089_2018-02-02_final
2018-02-05 09:15:58	ga_ls8c_ard_3-0-0_089089_2018-02-04_final
2018-02-10 09:34:29	ga_ls8c_ard_3-0-0_092089_2018-02-10_final
2018-02-12 09:22:07	ga_ls8c_ard_3-0-0_090089_2018-02-11_final
2018-02-19 09:28:15	ga_ls8c_ard_3-0-0_091089_2018-02-18_final
2018-02-21 09:15:52	ga_ls8c_ard_3-0-0_089089_2018-02-20_final
2018-02-26 09:34:23	ga_ls8c_ard_3-0-0_092089_2018-02-26_final
2018-02-28 09:22:00	ga_ls8c_ard_3-0-0_090089_2018-02-27_final
2018-03-07 09:28:07	ga_ls8c_ard_3-1-0_091089_2018-03-06_final
2018-03-09 09:15:44	ga_ls8c_ard_3-0-0_089089_2018-03-08_final
2018-03-14 09:34:13	ga_ls8c_ard_3-0-0_092089_2018-03-14_final
2018-03-16 09:21:51	ga_ls8c_ard_3-0-0_090089_2018-03-15_final
2018-03-23 09:27:59	ga_ls8c_ard_3-1-0_091089_2018-03-22_final
2018-03-25 09:15:37	ga_ls8c_ard_3-0-0_089089_2018-03-24_final
2018-04-08 09:27:51	ga_ls8c_ard_3-0-0_091089_2018-04-07_final
2018-04-10 09:15:28	ga_ls8c_ard_3-0-0_089089_2018-04-09_final
2018-04-15 09:33:58	ga_ls8c_ard_3-0-0_092089_2018-04-15_final
2018-04-17 09:21:35	ga_ls8c_ard_3-0-0_090089_2018-04-16_final
2018-04-24 09:27:42	ga_ls8c_ard_3-1-0_091089_2018-04-23_final
2018-04-26 09:15:19	ga_ls8c_ard_3-0-0_089089_2018-04-25_final
2018-05-01 09:33:49	ga_ls8c_ard_3-0-0_092089_2018-05-01_final
2018-05-03 09:21:26	ga_ls8c_ard_3-0-0_090089_2018-05-02_final
2018-05-10 09:27:32	ga_ls8c_ard_3-1-0_091089_2018-05-09_final
2018-05-12 09:15:10	ga_ls8c_ard_3-0-0_089089_2018-05-11_final
2018-05-17 09:33:38	ga_ls8c_ard_3-0-0_092089_2018-05-17_final
2018-05-19 09:21:15	ga_ls8c_ard_3-0-0_090089_2018-05-18_final
2018-06-02 09:33:26	ga_ls8c_ard_3-0-0_092089_2018-06-02_final
2018-06-04 09:20:40	ga_ls8c_ard_3-0-0_090088_2018-06-03_final
2018-06-04 09:21:04	ga_ls8c_ard_3-0-0_090089_2018-06-03_final
2018-06-18 09:33:34	ga_ls8c_ard_3-0-0_092089_2018-06-18_final
2018-06-20 09:20:50	ga_ls8c_ard_3-0-0_090088_2018-06-19_final
2018-06-20 09:21:14	ga_ls8c_ard_3-0-0_090089_2018-06-19_final
2018-07-04 09:33:20	ga_ls8c_ard_3-0-0_092088_2018-07-04_final
2018-07-04 09:33:44	ga_ls8c_ard_3-0-0_092089_2018-07-04_final
2018-07-06 09:20:59	ga_ls8c_ard_3-0-0_090088_2018-07-05_final
2018-07-06 09:21:23	ga_ls8c_ard_3-0-0_090089_2018-07-05_final
2018-07-20 09:33:51	ga_ls8c_ard_3-0-0_092089_2018-07-20_final
2018-07-22 09:21:06	ga_ls8c_ard_3-0-0_090088_2018-07-21_final
2018-07-22 09:21:30	ga_ls8c_ard_3-0-0_090089_2018-07-21_final
2018-08-05 09:33:59	ga_ls8c_ard_3-0-0_092089_2018-08-05_final
2018-08-07 09:21:15	ga_ls8c_ard_3-0-0_090088_2018-08-06_final
2018-08-07 09:21:39	ga_ls8c_ard_3-0-0_090089_2018-08-06_final
2018-08-19 09:46:04	ga_ls8c_ard_3-0-0_094088_2018-08-19_final
2018-08-21 09:34:08	ga_ls8c_ard_3-0-0_092089_2018-08-21_final
2018-08-23 09:21:47	ga_ls8c_ard_3-0-0_090089_2018-08-22_final
2018-09-01 09:15:16	ga_ls8c_ard_3-0-0_089088_2018-08-31_final
2018-09-01 09:15:40	ga_ls8c_ard_3-0-0_089089_2018-08-31_final
2018-09-04 09:46:11	ga_ls8c_ard_3-0-0_094088_2018-09-04_final
2018-09-06 09:33:50	ga_ls8c_ard_3-0-0_092088_2018-09-06_final
2018-09-06 09:34:14	ga_ls8c_ard_3-0-0_092089_2018-09-06_final
2018-09-08 09:21:29	ga_ls8c_ard_3-0-0_090088_2018-09-07_final
2018-09-08 09:21:53	ga_ls8c_ard_3-0-0_090089_2018-09-07_final
2019-11-12 09:35:00	ga_ls8c_ard_3-1-0_092089_2019-11-12_final
2019-11-14 09:22:38	ga_ls8c_ard_3-1-0_090089_2019-11-13_final
2020-01-15 09:34:49	ga_ls8c_ard_3-1-0_092089_2020-01-15_final
2020-01-17 09:22:03	ga_ls8c_ard_3-1-0_090088_2020-01-16_final
2020-01-17 09:22:27	ga_ls8c_ard_3-1-0_090089_2020-01-16_final
2020-06-25 09:21:37	ga_ls8c_ard_3-1-0_090088_2020-06-24_final
2020-06-25 09:22:01	ga_ls8c_ard_3-1-0_090089_2020-06-24_final
2020-07-11 09:21:44	ga_ls8c_ard_3-1-0_090088_2020-07-10_final
2020-07-11 09:22:08	ga_ls8c_ard_3-1-0_090089_2020-07-10_final
2020-08-03 09:28:25	ga_ls8c_ard_3-1-0_091089_2020-08-02_final
2020-08-08 09:46:35	ga_ls8c_ard_3-1-0_094088_2020-08-08_final
2020-08-10 09:34:37	ga_ls8c_ard_3-1-0_092089_2020-08-10_final
2020-08-12 09:21:52	ga_ls8c_ard_3-1-0_090088_2020-08-11_final
2020-08-12 09:22:16	ga_ls8c_ard_3-1-0_090089_2020-08-11_final
2020-08-15 09:52:48	ga_ls8c_ard_3-1-0_095088_2020-08-15_final
2020-08-17 09:40:27	ga_ls8c_ard_3-1-0_093088_2020-08-17_final
2020-08-21 09:16:10	ga_ls8c_ard_3-1-0_089089_2020-08-20_final
2020-08-26 09:34:21	ga_ls8c_ard_3-1-0_092088_2020-08-26_final
2020-08-26 09:34:45	ga_ls8c_ard_3-1-0_092089_2020-08-26_final
2020-08-28 09:22:25	ga_ls8c_ard_3-1-0_090089_2020-08-27_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years