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
2015-04-30 09:36:53	ga_ls8c_ard_3-0-0_093081_2015-04-30_final
2015-04-30 11:15:46	ga_ls8c_ard_3-0-0_109081_2015-04-30_final
2015-05-01 10:20:08	ga_ls8c_ard_3-0-0_100081_2015-05-01_final
2015-05-14 09:49:00	ga_ls8c_ard_3-0-0_095081_2015-05-14_final
2015-05-14 11:27:53	ga_ls8c_ard_3-0-0_111081_2015-05-14_final
2015-05-15 10:31:52	ga_ls8c_ard_3-0-0_102080_2015-05-15_final
2015-05-15 10:32:15	ga_ls8c_ard_3-0-0_102081_2015-05-15_final
2015-05-16 09:36:15	ga_ls8c_ard_3-0-0_093080_2015-05-16_final
2015-05-16 09:36:39	ga_ls8c_ard_3-0-0_093081_2015-05-16_final
2015-05-16 11:15:08	ga_ls8c_ard_3-0-0_109080_2015-05-16_final
2015-05-16 11:15:32	ga_ls8c_ard_3-0-0_109081_2015-05-16_final
2015-05-17 10:19:31	ga_ls8c_ard_3-0-0_100080_2015-05-17_final
2015-05-17 10:19:55	ga_ls8c_ard_3-0-0_100081_2015-05-17_final
2015-07-26 09:43:01	ga_ls8c_ard_3-0-0_094080_2015-07-26_final
2015-07-26 09:43:25	ga_ls8c_ard_3-0-0_094081_2015-07-26_final
2015-07-26 11:21:54	ga_ls8c_ard_3-0-0_110080_2015-07-26_final
2015-07-26 11:22:18	ga_ls8c_ard_3-0-0_110081_2015-07-26_final
2015-07-27 10:26:17	ga_ls8c_ard_3-0-0_101080_2015-07-27_final
2015-07-27 10:26:41	ga_ls8c_ard_3-0-0_101081_2015-07-27_final
2015-08-02 09:49:13	ga_ls8c_ard_3-0-0_095080_2015-08-02_final
2015-08-02 09:49:37	ga_ls8c_ard_3-0-0_095081_2015-08-02_final
2015-08-02 11:28:06	ga_ls8c_ard_3-0-0_111080_2015-08-02_final
2015-08-02 11:28:30	ga_ls8c_ard_3-0-0_111081_2015-08-02_final
2015-08-03 10:32:29	ga_ls8c_ard_3-0-0_102080_2015-08-03_final
2015-08-03 10:32:53	ga_ls8c_ard_3-0-0_102081_2015-08-03_final
2015-08-04 09:36:51	ga_ls8c_ard_3-0-0_093080_2015-08-04_final
2015-08-04 09:37:15	ga_ls8c_ard_3-0-0_093081_2015-08-04_final
2015-08-04 11:15:44	ga_ls8c_ard_3-0-0_109080_2015-08-04_final
2015-08-04 11:16:08	ga_ls8c_ard_3-0-0_109081_2015-08-04_final
2015-08-05 10:20:07	ga_ls8c_ard_3-0-0_100080_2015-08-05_final
2015-08-05 10:20:31	ga_ls8c_ard_3-0-0_100081_2015-08-05_final
2018-09-16 10:07:46	ga_ls8c_ard_3-0-0_098080_2018-09-16_final
2018-09-16 10:08:10	ga_ls8c_ard_3-0-0_098081_2018-09-16_final
2018-09-16 11:46:39	ga_ls8c_ard_3-0-0_114080_2018-09-16_final
2018-09-16 11:47:03	ga_ls8c_ard_3-0-0_114081_2018-09-16_final
2018-09-17 09:12:09	ga_ls8c_ard_3-0-0_089080_2018-09-16_final
2018-09-17 09:12:33	ga_ls8c_ard_3-0-0_089081_2018-09-16_final
2018-09-17 10:51:02	ga_ls8c_ard_3-0-0_105080_2018-09-17_final
2018-09-17 10:51:26	ga_ls8c_ard_3-0-0_105081_2018-09-17_final
2018-10-04 09:55:32	ga_ls8c_ard_3-0-0_096080_2018-10-04_final
2018-10-04 09:55:56	ga_ls8c_ard_3-0-0_096081_2018-10-04_final
2018-10-04 11:34:25	ga_ls8c_ard_3-0-0_112080_2018-10-04_final
2018-10-04 11:34:49	ga_ls8c_ard_3-0-0_112081_2018-10-04_final
2018-10-05 10:38:48	ga_ls8c_ard_3-0-0_103080_2018-10-05_final
2018-10-05 10:39:12	ga_ls8c_ard_3-0-0_103081_2018-10-05_final
2018-10-06 09:43:11	ga_ls8c_ard_3-0-0_094080_2018-10-06_final
2018-10-06 09:43:35	ga_ls8c_ard_3-0-0_094081_2018-10-06_final
2018-10-06 11:22:05	ga_ls8c_ard_3-0-0_110080_2018-10-06_final
2018-10-06 11:22:29	ga_ls8c_ard_3-0-0_110081_2018-10-06_final
2018-10-07 10:26:28	ga_ls8c_ard_3-0-0_101080_2018-10-07_final
2018-10-07 10:26:52	ga_ls8c_ard_3-0-0_101081_2018-10-07_final
2018-12-23 09:55:39	ga_ls8c_ard_3-0-0_096080_2018-12-23_final
2018-12-23 09:56:03	ga_ls8c_ard_3-0-0_096081_2018-12-23_final
2018-12-23 11:34:32	ga_ls8c_ard_3-0-0_112080_2018-12-23_final
2018-12-23 11:34:56	ga_ls8c_ard_3-0-0_112081_2018-12-23_final
2018-12-24 10:38:55	ga_ls8c_ard_3-0-0_103080_2018-12-24_final
2018-12-24 10:39:19	ga_ls8c_ard_3-0-0_103081_2018-12-24_final
2018-12-25 09:43:18	ga_ls8c_ard_3-0-0_094080_2018-12-25_final
2018-12-25 09:43:41	ga_ls8c_ard_3-0-0_094081_2018-12-25_final
2018-12-25 11:22:35	ga_ls8c_ard_3-0-0_110081_2018-12-25_final
2018-12-26 10:26:33	ga_ls8c_ard_3-0-0_101080_2018-12-26_final
2018-12-26 10:26:57	ga_ls8c_ard_3-0-0_101081_2018-12-26_final
2019-01-06 10:08:24	ga_ls8c_ard_3-0-0_098081_2019-01-06_final
2019-01-06 11:47:17	ga_ls8c_ard_3-0-0_114081_2019-01-06_final
2019-01-07 09:12:23	ga_ls8c_ard_3-0-0_089080_2019-01-06_final
2019-01-07 09:12:47	ga_ls8c_ard_3-0-0_089081_2019-01-06_final
2019-01-07 10:51:16	ga_ls8c_ard_3-0-0_105080_2019-01-07_final
2019-01-07 10:51:39	ga_ls8c_ard_3-0-0_105081_2019-01-07_final
2023-03-02 10:33:18	ga_ls8c_ard_3-2-1_102081_2023-03-02_final
2023-03-04 10:20:56	ga_ls8c_ard_3-2-1_100081_2023-03-04_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-05 09:25:18	ga_ls8c_ard_3-2-1_091081_2023-03-04_final
2023-08-14 10:51:18	ga_ls8c_ard_3-2-1_105080_2023-08-14_final
2023-08-14 10:51:42	ga_ls8c_ard_3-2-1_105081_2023-08-14_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-15 09:56:05	ga_ls8c_ard_3-2-1_096081_2023-08-15_final
2023-08-15 11:34:35	ga_ls8c_ard_3-2-1_112080_2023-08-15_final
2023-08-15 11:34:58	ga_ls8c_ard_3-2-1_112081_2023-08-15_final
2023-08-16 10:38:58	ga_ls8c_ard_3-2-1_103080_2023-08-16_final
2023-08-16 10:39:22	ga_ls8c_ard_3-2-1_103081_2023-08-16_final
2023-08-17 09:43:21	ga_ls8c_ard_3-2-1_094080_2023-08-17_final
2023-08-17 09:43:45	ga_ls8c_ard_3-2-1_094081_2023-08-17_final
2023-08-17 11:22:14	ga_ls8c_ard_3-2-1_110080_2023-08-17_final
2023-08-17 11:22:38	ga_ls8c_ard_3-2-1_110081_2023-08-17_final
2023-08-22 10:02:20	ga_ls8c_ard_3-2-1_097081_2023-08-22_final
2023-08-24 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-08-24_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-25 10:32:51	ga_ls8c_ard_3-2-1_102080_2023-08-25_final
2023-08-25 10:33:15	ga_ls8c_ard_3-2-1_102081_2023-08-25_final
2023-08-26 09:37:14	ga_ls8c_ard_3-2-1_093080_2023-08-26_final
2023-08-26 09:37:38	ga_ls8c_ard_3-2-1_093081_2023-08-26_final
2023-08-26 11:16:07	ga_ls8c_ard_3-2-1_109080_2023-08-26_final
2023-08-26 11:16:31	ga_ls8c_ard_3-2-1_109081_2023-08-26_final
2023-08-28 11:03:46	ga_ls8c_ard_3-2-1_107080_2023-08-28_final
2023-08-28 11:04:10	ga_ls8c_ard_3-2-1_107081_2023-08-28_final
2023-08-31 09:55:46	ga_ls8c_ard_3-2-1_096080_2023-08-31_final
2023-08-31 09:56:10	ga_ls8c_ard_3-2-1_096081_2023-08-31_final
2023-08-31 11:34:39	ga_ls8c_ard_3-2-1_112080_2023-08-31_final
2023-08-31 11:35:03	ga_ls8c_ard_3-2-1_112081_2023-08-31_final
2023-09-01 10:39:02	ga_ls8c_ard_3-2-1_103080_2023-09-01_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