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
2013-03-31 09:34:38	ga_ls8c_ard_3-0-0_092081_2013-03-31_final
2013-03-31 11:13:13	ga_ls8c_ard_3-0-0_108081_2013-03-31_final
2013-04-01 10:13:13	ga_ls8c_ard_3-0-0_099081_2013-04-01_final
2013-04-01 11:51:47	ga_ls8c_ard_3-0-0_114081_2013-04-01_final
2013-04-02 10:51:48	ga_ls8c_ard_3-0-0_105081_2013-04-02_final
2013-07-04 09:45:24	ga_ls8c_ard_3-0-0_094080_2013-07-04_final
2013-08-21 09:45:27	ga_ls8c_ard_3-0-0_094080_2013-08-21_final
2013-08-21 09:45:51	ga_ls8c_ard_3-0-0_094081_2013-08-21_final
2013-08-21 11:24:20	ga_ls8c_ard_3-0-0_110080_2013-08-21_final
2013-08-21 11:24:44	ga_ls8c_ard_3-0-0_110081_2013-08-21_final
2013-08-22 08:49:50	ga_ls8c_ard_3-2-1_085080_2013-08-21_interim
2013-08-22 08:50:14	ga_ls8c_ard_3-2-1_085081_2013-08-21_interim
2013-08-22 10:28:43	ga_ls8c_ard_3-0-0_101080_2013-08-22_final
2013-08-22 10:29:07	ga_ls8c_ard_3-0-0_101081_2013-08-22_final
2013-08-23 09:33:06	ga_ls8c_ard_3-0-0_092080_2013-08-23_final
2013-08-23 09:33:30	ga_ls8c_ard_3-0-0_092081_2013-08-23_final
2013-08-23 11:11:59	ga_ls8c_ard_3-0-0_108080_2013-08-23_final
2013-08-23 11:12:23	ga_ls8c_ard_3-0-0_108081_2013-08-23_final
2013-08-24 10:16:22	ga_ls8c_ard_3-0-0_099080_2013-08-24_final
2013-08-24 10:16:46	ga_ls8c_ard_3-0-0_099081_2013-08-24_final
2013-08-24 11:55:15	ga_ls8c_ard_3-0-0_115080_2013-08-24_final
2018-02-23 10:38:47	ga_ls8c_ard_3-0-0_103080_2018-02-23_final
2018-02-23 10:39:11	ga_ls8c_ard_3-0-0_103081_2018-02-23_final
2018-02-24 09:43:10	ga_ls8c_ard_3-0-0_094080_2018-02-24_final
2018-02-24 09:43:34	ga_ls8c_ard_3-0-0_094081_2018-02-24_final
2018-02-24 11:22:03	ga_ls8c_ard_3-0-0_110080_2018-02-24_final
2018-02-24 11:22:27	ga_ls8c_ard_3-0-0_110081_2018-02-24_final
2018-02-25 10:26:25	ga_ls8c_ard_3-0-0_101080_2018-02-25_final
2018-02-25 10:26:49	ga_ls8c_ard_3-0-0_101081_2018-02-25_final
2018-02-26 09:30:47	ga_ls8c_ard_3-0-0_092080_2018-02-26_final
2018-02-26 09:31:11	ga_ls8c_ard_3-0-0_092081_2018-02-26_final
2018-02-26 11:09:40	ga_ls8c_ard_3-0-0_108080_2018-02-26_final
2018-02-26 11:10:04	ga_ls8c_ard_3-0-0_108081_2018-02-26_final
2018-03-11 10:38:39	ga_ls8c_ard_3-0-0_103080_2018-03-11_final
2018-03-11 10:39:03	ga_ls8c_ard_3-0-0_103081_2018-03-11_final
2018-03-12 09:43:01	ga_ls8c_ard_3-0-0_094080_2018-03-12_final
2018-03-12 09:43:25	ga_ls8c_ard_3-0-0_094081_2018-03-12_final
2018-03-12 11:21:54	ga_ls8c_ard_3-0-0_110080_2018-03-12_final
2018-03-12 11:22:18	ga_ls8c_ard_3-0-0_110081_2018-03-12_final
2018-03-13 10:26:16	ga_ls8c_ard_3-0-0_101080_2018-03-13_final
2018-03-13 10:26:40	ga_ls8c_ard_3-0-0_101081_2018-03-13_final
2018-03-14 09:31:02	ga_ls8c_ard_3-0-0_092081_2018-03-14_final
2018-03-14 11:09:31	ga_ls8c_ard_3-0-0_108080_2018-03-14_final
2018-03-14 11:09:55	ga_ls8c_ard_3-0-0_108081_2018-03-14_final
2018-05-17 09:30:27	ga_ls8c_ard_3-0-0_092081_2018-05-17_final
2018-05-17 11:08:56	ga_ls8c_ard_3-0-0_108080_2018-05-17_final
2018-05-17 11:09:20	ga_ls8c_ard_3-0-0_108081_2018-05-17_final
2018-07-01 10:38:06	ga_ls8c_ard_3-0-0_103080_2018-07-01_final
2018-07-01 10:38:29	ga_ls8c_ard_3-0-0_103081_2018-07-01_final
2018-07-02 09:42:29	ga_ls8c_ard_3-0-0_094080_2018-07-02_final
2018-07-02 09:42:53	ga_ls8c_ard_3-0-0_094081_2018-07-02_final
2018-07-02 11:21:22	ga_ls8c_ard_3-0-0_110080_2018-07-02_final
2018-07-02 11:21:46	ga_ls8c_ard_3-0-0_110081_2018-07-02_final
2018-07-03 10:25:45	ga_ls8c_ard_3-0-0_101080_2018-07-03_final
2018-07-03 10:26:09	ga_ls8c_ard_3-0-0_101081_2018-07-03_final
2018-07-04 09:30:08	ga_ls8c_ard_3-0-0_092080_2018-07-04_final
2018-07-04 09:30:32	ga_ls8c_ard_3-0-0_092081_2018-07-04_final
2018-07-04 11:09:01	ga_ls8c_ard_3-0-0_108080_2018-07-04_final
2018-07-04 11:09:25	ga_ls8c_ard_3-0-0_108081_2018-07-04_final
2019-07-13 10:32:48	ga_ls8c_ard_3-1-0_102080_2019-07-13_final
2019-07-13 10:33:12	ga_ls8c_ard_3-1-0_102081_2019-07-13_final
2019-07-14 09:37:11	ga_ls8c_ard_3-1-0_093080_2019-07-14_final
2019-07-14 09:37:35	ga_ls8c_ard_3-1-0_093081_2019-07-14_final
2019-07-14 11:16:04	ga_ls8c_ard_3-1-0_109080_2019-07-14_final
2019-07-14 11:16:28	ga_ls8c_ard_3-1-0_109081_2019-07-14_final
2019-07-15 10:20:26	ga_ls8c_ard_3-1-0_100080_2019-07-15_final
2019-07-15 10:20:50	ga_ls8c_ard_3-1-0_100081_2019-07-15_final
2019-07-16 09:24:49	ga_ls8c_ard_3-1-0_091080_2019-07-15_final
2019-07-16 09:25:13	ga_ls8c_ard_3-1-0_091081_2019-07-15_final
2019-07-16 11:03:42	ga_ls8c_ard_3-1-0_107080_2019-07-16_final
2019-07-16 11:04:06	ga_ls8c_ard_3-1-0_107081_2019-07-16_final
2019-10-04 09:25:14	ga_ls8c_ard_3-1-0_091080_2019-10-03_final
2019-10-04 09:25:38	ga_ls8c_ard_3-1-0_091081_2019-10-03_final
2019-10-04 11:04:07	ga_ls8c_ard_3-1-0_107080_2019-10-04_final
2019-10-04 11:04:31	ga_ls8c_ard_3-1-0_107081_2019-10-04_final
2019-10-05 10:08:30	ga_ls8c_ard_3-1-0_098080_2019-10-05_final
2019-10-05 10:08:54	ga_ls8c_ard_3-1-0_098081_2019-10-05_final
2019-10-05 11:47:23	ga_ls8c_ard_3-1-0_114080_2019-10-05_final
2019-10-05 11:47:47	ga_ls8c_ard_3-1-0_114081_2019-10-05_final
2019-10-06 09:12:53	ga_ls8c_ard_3-1-0_089080_2019-10-05_final
2019-10-06 09:13:17	ga_ls8c_ard_3-1-0_089081_2019-10-05_final
2019-10-06 10:51:46	ga_ls8c_ard_3-1-0_105080_2019-10-06_final
2019-10-06 10:52:10	ga_ls8c_ard_3-1-0_105081_2019-10-06_final
2019-10-07 09:56:09	ga_ls8c_ard_3-1-0_096080_2019-10-07_final
2019-10-07 09:56:33	ga_ls8c_ard_3-1-0_096081_2019-10-07_final
2019-10-07 11:35:02	ga_ls8c_ard_3-1-0_112080_2019-10-07_final
2019-10-07 11:35:26	ga_ls8c_ard_3-1-0_112081_2019-10-07_final
2019-10-08 10:39:25	ga_ls8c_ard_3-1-0_103080_2019-10-08_final
2019-10-08 10:39:49	ga_ls8c_ard_3-1-0_103081_2019-10-08_final
2019-11-09 10:39:24	ga_ls8c_ard_3-1-0_103080_2019-11-09_final
2019-11-09 10:39:48	ga_ls8c_ard_3-1-0_103081_2019-11-09_final
2019-11-10 09:43:47	ga_ls8c_ard_3-1-0_094080_2019-11-10_final
2019-11-10 09:44:11	ga_ls8c_ard_3-1-0_094081_2019-11-10_final
2019-11-10 11:22:40	ga_ls8c_ard_3-1-0_110080_2019-11-10_final
2019-11-10 11:23:04	ga_ls8c_ard_3-1-0_110081_2019-11-10_final
2019-11-11 10:27:02	ga_ls8c_ard_3-1-0_101080_2019-11-11_final
2019-11-11 10:27:26	ga_ls8c_ard_3-1-0_101081_2019-11-11_final
2019-11-12 09:31:25	ga_ls8c_ard_3-1-0_092080_2019-11-12_final
2019-11-12 09:31:49	ga_ls8c_ard_3-1-0_092081_2019-11-12_final
2019-11-12 11:10:18	ga_ls8c_ard_3-1-0_108080_2019-11-12_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years