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
2015-09-05 09:40:16	ga_ls8c_ard_3-0-0_093088_2015-09-05_final
2015-09-12 09:46:31	ga_ls8c_ard_3-0-0_094088_2015-09-12_final
2015-09-28 09:46:37	ga_ls8c_ard_3-0-0_094088_2015-09-28_final
2015-12-26 09:40:34	ga_ls8c_ard_3-0-0_093088_2015-12-26_final
2017-03-20 09:28:08	ga_ls8c_ard_3-0-0_091089_2017-03-19_final
2017-03-27 09:34:15	ga_ls8c_ard_3-0-0_092089_2017-03-27_final
2017-03-29 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-03-28_final
2017-04-05 09:28:01	ga_ls8c_ard_3-0-0_091089_2017-04-04_final
2017-04-12 09:34:08	ga_ls8c_ard_3-0-0_092089_2017-04-12_final
2017-04-14 09:21:45	ga_ls8c_ard_3-0-0_090089_2017-04-13_final
2017-04-21 09:27:52	ga_ls8c_ard_3-0-0_091089_2017-04-20_final
2017-04-28 09:33:57	ga_ls8c_ard_3-0-0_092089_2017-04-28_final
2017-04-30 09:21:35	ga_ls8c_ard_3-0-0_090089_2017-04-29_final
2017-05-03 09:52:04	ga_ls8c_ard_3-0-0_095088_2017-05-03_final
2017-05-07 09:27:48	ga_ls8c_ard_3-0-0_091089_2017-05-06_final
2017-05-09 09:15:04	ga_ls8c_ard_3-0-0_089088_2017-05-08_final
2017-05-09 09:15:28	ga_ls8c_ard_3-0-0_089089_2017-05-08_final
2017-05-14 09:34:04	ga_ls8c_ard_3-0-0_092089_2017-05-14_final
2017-05-16 09:21:44	ga_ls8c_ard_3-0-0_090089_2017-05-15_final
2017-05-19 09:52:16	ga_ls8c_ard_3-0-0_095088_2017-05-19_final
2017-05-23 09:27:59	ga_ls8c_ard_3-0-0_091089_2017-05-22_final
2017-05-25 09:15:39	ga_ls8c_ard_3-0-0_089089_2017-05-24_final
2017-05-28 09:46:11	ga_ls8c_ard_3-0-0_094088_2017-05-28_final
2017-05-30 09:34:14	ga_ls8c_ard_3-0-0_092089_2017-05-30_final
2017-06-01 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-05-31_final
2017-06-08 09:28:08	ga_ls8c_ard_3-0-0_091089_2017-06-07_final
2017-06-10 09:15:23	ga_ls8c_ard_3-0-0_089088_2017-06-09_final
2017-06-10 09:15:47	ga_ls8c_ard_3-0-0_089089_2017-06-09_final
2017-06-15 09:34:21	ga_ls8c_ard_3-0-0_092089_2017-06-15_final
2017-06-17 09:22:00	ga_ls8c_ard_3-0-0_090089_2017-06-16_final
2017-06-20 09:52:31	ga_ls8c_ard_3-0-0_095088_2017-06-20_final
2017-06-24 09:28:13	ga_ls8c_ard_3-0-0_091089_2017-06-23_final
2017-06-29 09:46:23	ga_ls8c_ard_3-0-0_094088_2017-06-29_final
2017-07-01 09:34:26	ga_ls8c_ard_3-0-0_092089_2017-07-01_final
2017-07-03 09:22:04	ga_ls8c_ard_3-0-0_090089_2017-07-02_final
2017-07-06 09:52:35	ga_ls8c_ard_3-0-0_095088_2017-07-06_final
2017-07-10 09:28:16	ga_ls8c_ard_3-0-0_091089_2017-07-09_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
2018-02-21 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
2018-03-09 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
2018-03-25 09:15:37	ga_ls8c_ard_3-0-0_089089_2018-03-24_final
2018-03-30 09:34:07	ga_ls8c_ard_3-0-0_092089_2018-03-30_final
2018-04-01 09:21:44	ga_ls8c_ard_3-0-0_090089_2018-03-31_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
2018-05-01 09:33:49	ga_ls8c_ard_3-0-0_092089_2018-05-01_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
2018-09-22 09:34:18	ga_ls8c_ard_3-0-0_092089_2018-09-22_final
2018-09-24 09:21:34	ga_ls8c_ard_3-0-0_090088_2018-09-23_final
2018-09-24 09:21:58	ga_ls8c_ard_3-0-0_090089_2018-09-23_final
2018-12-11 09:34:32	ga_ls8c_ard_3-0-0_092089_2018-12-11_final
2018-12-13 09:22:09	ga_ls8c_ard_3-0-0_090089_2018-12-12_final
2018-12-27 09:34:31	ga_ls8c_ard_3-0-0_092089_2018-12-27_final
2018-12-29 09:22:10	ga_ls8c_ard_3-0-0_090089_2018-12-28_final
2019-01-28 09:34:26	ga_ls8c_ard_3-0-0_092089_2019-01-28_final
2019-02-15 09:22:02	ga_ls8c_ard_3-0-0_090089_2019-02-14_final
2019-03-17 09:34:14	ga_ls8c_ard_3-1-0_092089_2019-03-17_final
2019-03-26 09:28:02	ga_ls8c_ard_3-1-0_091089_2019-03-25_final
2019-03-28 09:15:40	ga_ls8c_ard_3-1-0_089089_2019-03-27_final
2019-04-13 09:15:35	ga_ls8c_ard_3-1-0_089089_2019-04-12_final
2019-05-04 09:34:05	ga_ls8c_ard_3-0-0_092089_2019-05-04_final
2019-05-06 09:21:45	ga_ls8c_ard_3-0-0_090089_2019-05-05_final
2019-05-22 09:21:56	ga_ls8c_ard_3-0-0_090089_2019-05-21_final
2019-05-25 09:52:27	ga_ls8c_ard_3-0-0_095088_2019-05-25_final
2019-05-31 09:15:26	ga_ls8c_ard_3-0-0_089088_2019-05-30_final
2019-05-31 09:15:50	ga_ls8c_ard_3-0-0_089089_2019-05-30_final
2019-06-03 09:46:21	ga_ls8c_ard_3-0-0_094088_2019-06-03_final
2020-03-03 09:34:36	ga_ls8c_ard_3-1-0_092089_2020-03-03_final
2020-03-05 09:22:13	ga_ls8c_ard_3-1-0_090089_2020-03-04_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-28 09:28:12	ga_ls8c_ard_3-1-0_091089_2020-03-27_final
2020-03-30 09:15:49	ga_ls8c_ard_3-1-0_089089_2020-03-29_final
2020-04-04 09:34:19	ga_ls8c_ard_3-1-0_092089_2020-04-04_final
2020-04-06 09:21:57	ga_ls8c_ard_3-1-0_090089_2020-04-05_final
2020-04-22 09:21:50	ga_ls8c_ard_3-1-0_090089_2020-04-21_final
2020-04-29 09:27:57	ga_ls8c_ard_3-1-0_091089_2020-04-28_final
2020-05-01 09:15:34	ga_ls8c_ard_3-1-0_089089_2020-04-30_final
2020-05-11 09:52:11	ga_ls8c_ard_3-1-0_095088_2020-05-11_final
2020-05-13 09:39:50	ga_ls8c_ard_3-1-0_093088_2020-05-13_final
2020-05-15 09:27:53	ga_ls8c_ard_3-1-0_091089_2020-05-14_final
2020-05-17 09:15:08	ga_ls8c_ard_3-1-0_089088_2020-05-16_final
2020-05-17 09:15:32	ga_ls8c_ard_3-1-0_089089_2020-05-16_final
2020-05-27 09:52:15	ga_ls8c_ard_3-1-0_095088_2020-05-27_final
2020-05-29 09:39:53	ga_ls8c_ard_3-1-0_093088_2020-05-29_final
2020-05-31 09:27:57	ga_ls8c_ard_3-1-0_091089_2020-05-30_final
2020-06-02 09:15:37	ga_ls8c_ard_3-1-0_089089_2020-06-01_final
2020-06-05 09:46:09	ga_ls8c_ard_3-1-0_094088_2020-06-05_final
2020-06-07 09:34:13	ga_ls8c_ard_3-1-0_092089_2020-06-07_final
2020-06-09 09:21:52	ga_ls8c_ard_3-1-0_090089_2020-06-08_final
2020-06-12 09:52:24	ga_ls8c_ard_3-1-0_095088_2020-06-12_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