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
2015-04-14 09:38:37	ga_ls8c_ard_3-0-0_093085_2015-04-14_final
2015-04-14 11:17:30	ga_ls8c_ard_3-0-0_109085_2015-04-14_final
2015-04-15 10:21:53	ga_ls8c_ard_3-0-0_100085_2015-04-15_final
2015-04-16 09:26:15	ga_ls8c_ard_3-0-0_091085_2015-04-15_final
2015-04-16 11:05:08	ga_ls8c_ard_3-0-0_107085_2015-04-16_final
2015-04-30 09:38:29	ga_ls8c_ard_3-0-0_093085_2015-04-30_final
2015-05-02 09:26:05	ga_ls8c_ard_3-0-0_091085_2015-05-01_final
2017-03-20 09:26:32	ga_ls8c_ard_3-0-0_091085_2017-03-19_final
2017-03-21 10:09:47	ga_ls8c_ard_3-0-0_098085_2017-03-21_final
2017-03-22 09:14:09	ga_ls8c_ard_3-0-0_089085_2017-03-21_final
2017-03-23 09:57:24	ga_ls8c_ard_3-0-0_096085_2017-03-23_final
2017-03-23 11:36:17	ga_ls8c_ard_3-0-0_112085_2017-03-23_final
2017-04-26 09:44:45	ga_ls8c_ard_3-0-0_094085_2017-04-26_final
2017-04-26 11:23:38	ga_ls8c_ard_3-0-0_110085_2017-04-26_final
2017-04-28 09:31:58	ga_ls8c_ard_3-0-0_092084_2017-04-28_final
2017-04-28 09:32:22	ga_ls8c_ard_3-0-0_092085_2017-04-28_final
2017-04-28 11:10:51	ga_ls8c_ard_3-0-0_108084_2017-04-28_final
2017-04-28 11:11:15	ga_ls8c_ard_3-0-0_108085_2017-04-28_final
2017-06-13 09:44:42	ga_ls8c_ard_3-0-0_094084_2017-06-13_final
2017-06-13 09:45:06	ga_ls8c_ard_3-0-0_094085_2017-06-13_final
2017-06-13 11:23:35	ga_ls8c_ard_3-0-0_110084_2017-06-13_final
2017-06-13 11:23:59	ga_ls8c_ard_3-0-0_110085_2017-06-13_final
2017-06-14 10:27:58	ga_ls8c_ard_3-0-0_101084_2017-06-14_final
2017-06-15 09:32:21	ga_ls8c_ard_3-0-0_092084_2017-06-15_final
2017-06-15 09:32:45	ga_ls8c_ard_3-0-0_092085_2017-06-15_final
2017-06-15 11:11:14	ga_ls8c_ard_3-0-0_108084_2017-06-15_final
2017-06-15 11:11:38	ga_ls8c_ard_3-0-0_108085_2017-06-15_final
2017-06-22 09:38:34	ga_ls8c_ard_3-0-0_093084_2017-06-22_final
2017-06-22 09:38:58	ga_ls8c_ard_3-0-0_093085_2017-06-22_final
2017-06-22 11:17:27	ga_ls8c_ard_3-0-0_109084_2017-06-22_final
2017-06-22 11:17:51	ga_ls8c_ard_3-0-0_109085_2017-06-22_final
2017-06-23 10:21:50	ga_ls8c_ard_3-0-0_100084_2017-06-23_final
2017-06-23 10:22:14	ga_ls8c_ard_3-0-0_100085_2017-06-23_final
2017-06-24 09:26:37	ga_ls8c_ard_3-0-0_091085_2017-06-23_final
2017-06-24 11:05:06	ga_ls8c_ard_3-0-0_107084_2017-06-24_final
2017-06-24 11:05:30	ga_ls8c_ard_3-0-0_107085_2017-06-24_final
2017-07-31 09:44:58	ga_ls8c_ard_3-0-0_094084_2017-07-31_final
2017-07-31 09:45:22	ga_ls8c_ard_3-0-0_094085_2017-07-31_final
2017-07-31 11:23:51	ga_ls8c_ard_3-0-0_110084_2017-07-31_final
2017-07-31 11:24:15	ga_ls8c_ard_3-0-0_110085_2017-07-31_final
2017-08-01 10:28:14	ga_ls8c_ard_3-0-0_101084_2017-08-01_final
2017-08-02 09:32:37	ga_ls8c_ard_3-0-0_092084_2017-08-02_final
2017-08-02 09:33:01	ga_ls8c_ard_3-0-0_092085_2017-08-02_final
2017-08-02 11:11:30	ga_ls8c_ard_3-0-0_108084_2017-08-02_final
2017-08-02 11:11:54	ga_ls8c_ard_3-0-0_108085_2017-08-02_final
2017-08-09 09:38:51	ga_ls8c_ard_3-0-0_093084_2017-08-09_final
2017-08-09 09:39:15	ga_ls8c_ard_3-0-0_093085_2017-08-09_final
2017-08-09 11:17:44	ga_ls8c_ard_3-0-0_109084_2017-08-09_final
2017-08-09 11:18:08	ga_ls8c_ard_3-0-0_109085_2017-08-09_final
2017-08-10 10:22:07	ga_ls8c_ard_3-0-0_100084_2017-08-10_final
2017-08-10 10:22:31	ga_ls8c_ard_3-0-0_100085_2017-08-10_final
2017-08-11 09:26:30	ga_ls8c_ard_3-0-0_091084_2017-08-10_final
2017-08-11 09:26:54	ga_ls8c_ard_3-0-0_091085_2017-08-10_final
2017-08-11 11:05:23	ga_ls8c_ard_3-0-0_107084_2017-08-11_final
2017-08-11 11:05:47	ga_ls8c_ard_3-0-0_107085_2017-08-11_final
2017-08-16 09:45:28	ga_ls8c_ard_3-0-0_094085_2017-08-16_final
2017-08-16 11:23:57	ga_ls8c_ard_3-0-0_110084_2017-08-16_final
2017-08-16 11:24:21	ga_ls8c_ard_3-0-0_110085_2017-08-16_final
2017-08-17 10:28:20	ga_ls8c_ard_3-0-0_101084_2017-08-17_final
2017-08-18 09:33:07	ga_ls8c_ard_3-0-0_092085_2017-08-18_final
2017-08-18 11:11:36	ga_ls8c_ard_3-0-0_108084_2017-08-18_final
2017-08-18 11:12:00	ga_ls8c_ard_3-0-0_108085_2017-08-18_final
2017-08-25 09:38:55	ga_ls8c_ard_3-0-0_093084_2017-08-25_final
2017-08-25 09:39:19	ga_ls8c_ard_3-0-0_093085_2017-08-25_final
2017-08-25 11:17:48	ga_ls8c_ard_3-0-0_109084_2017-08-25_final
2017-08-25 11:18:12	ga_ls8c_ard_3-0-0_109085_2017-08-25_final
2017-08-26 10:22:11	ga_ls8c_ard_3-0-0_100084_2017-08-26_final
2017-08-26 10:22:35	ga_ls8c_ard_3-0-0_100085_2017-08-26_final
2017-08-27 09:26:58	ga_ls8c_ard_3-0-0_091085_2017-08-26_final
2017-08-27 11:05:27	ga_ls8c_ard_3-0-0_107084_2017-08-27_final
2017-08-27 11:05:51	ga_ls8c_ard_3-0-0_107085_2017-08-27_final
2022-07-22 09:39:32	ga_ls8c_ard_3-2-1_093085_2022-07-22_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-24 11:05:41	ga_ls8c_ard_3-2-1_107084_2022-07-24_final
2022-07-25 10:10:05	ga_ls8c_ard_3-2-1_098084_2022-07-25_final
2022-07-25 10:10:29	ga_ls8c_ard_3-2-1_098085_2022-07-25_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-07-29 09:45:24	ga_ls8c_ard_3-2-1_094084_2022-07-29_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-07-31 09:33:28	ga_ls8c_ard_3-2-1_092085_2022-07-31_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-01 10:16:44	ga_ls8c_ard_3-2-1_099085_2022-08-01_final
2022-09-04 11:42:58	ga_ls8c_ard_3-2-1_113084_2022-09-04_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-06 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-09-06_final
2022-09-08 09:39:25	ga_ls8c_ard_3-2-1_093084_2022-09-08_final
2022-09-08 09:39:49	ga_ls8c_ard_3-2-1_093085_2022-09-08_final
2022-09-08 11:18:18	ga_ls8c_ard_3-2-1_109084_2022-09-08_final
2022-10-26 09:39:27	ga_ls8c_ard_3-2-1_093084_2022-10-26_final
2022-10-26 09:39:51	ga_ls8c_ard_3-2-1_093085_2022-10-26_final
2022-10-28 09:27:30	ga_ls8c_ard_3-2-1_091085_2022-10-27_final
2022-10-28 11:05:59	ga_ls8c_ard_3-2-1_107084_2022-10-28_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-10-29_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