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
2015-01-17 09:31:04	ga_ls8c_ard_3-0-0_092080_2015-01-17_final
2015-01-17 09:31:28	ga_ls8c_ard_3-0-0_092081_2015-01-17_final
2015-01-17 11:09:57	ga_ls8c_ard_3-0-0_108080_2015-01-17_final
2015-01-17 11:10:21	ga_ls8c_ard_3-0-0_108081_2015-01-17_final
2015-01-18 10:14:19	ga_ls8c_ard_3-0-0_099080_2015-01-18_final
2015-01-18 10:14:43	ga_ls8c_ard_3-0-0_099081_2015-01-18_final
2015-01-18 11:53:12	ga_ls8c_ard_3-0-0_115080_2015-01-18_final
2015-01-19 09:18:41	ga_ls8c_ard_3-0-0_090080_2015-01-18_final
2015-01-19 09:19:05	ga_ls8c_ard_3-0-0_090081_2015-01-18_final
2015-01-19 10:57:34	ga_ls8c_ard_3-0-0_106080_2015-01-19_final
2015-01-19 10:57:58	ga_ls8c_ard_3-0-0_106081_2015-01-19_final
2015-02-19 10:14:08	ga_ls8c_ard_3-0-0_099080_2015-02-19_final
2015-02-19 10:14:32	ga_ls8c_ard_3-0-0_099081_2015-02-19_final
2015-02-19 11:53:01	ga_ls8c_ard_3-0-0_115080_2015-02-19_final
2015-02-20 09:18:30	ga_ls8c_ard_3-0-0_090080_2015-02-19_final
2015-02-20 09:18:54	ga_ls8c_ard_3-0-0_090081_2015-02-19_final
2015-02-20 10:57:23	ga_ls8c_ard_3-0-0_106080_2015-02-20_final
2015-02-20 10:57:47	ga_ls8c_ard_3-0-0_106081_2015-02-20_final
2015-02-28 10:07:55	ga_ls8c_ard_3-0-0_098080_2015-02-28_final
2015-02-28 10:08:19	ga_ls8c_ard_3-0-0_098081_2015-02-28_final
2015-02-28 11:46:48	ga_ls8c_ard_3-0-0_114080_2015-02-28_final
2015-02-28 11:47:12	ga_ls8c_ard_3-0-0_114081_2015-02-28_final
2015-03-01 09:12:17	ga_ls8c_ard_3-0-0_089080_2015-02-28_final
2015-03-01 09:12:41	ga_ls8c_ard_3-0-0_089081_2015-02-28_final
2015-03-01 10:51:10	ga_ls8c_ard_3-0-0_105080_2015-03-01_final
2015-03-01 10:51:34	ga_ls8c_ard_3-0-0_105081_2015-03-01_final
2019-07-11 09:06:16	ga_ls8c_ard_3-1-0_088080_2019-07-10_final
2019-07-11 09:06:40	ga_ls8c_ard_3-1-0_088081_2019-07-10_final
2019-07-11 10:45:09	ga_ls8c_ard_3-1-0_104080_2019-07-11_final
2019-07-11 10:45:33	ga_ls8c_ard_3-1-0_104081_2019-07-11_final
2019-07-12 09:49:32	ga_ls8c_ard_3-1-0_095080_2019-07-12_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-07-12 11:28:25	ga_ls8c_ard_3-1-0_111080_2019-07-12_final
2019-07-12 11:28:49	ga_ls8c_ard_3-1-0_111081_2019-07-12_final
2019-07-28 09:49:37	ga_ls8c_ard_3-1-0_095080_2019-07-28_final
2019-07-28 09:50:01	ga_ls8c_ard_3-1-0_095081_2019-07-28_final
2019-07-28 11:28:30	ga_ls8c_ard_3-1-0_111080_2019-07-28_final
2019-07-28 11:28:54	ga_ls8c_ard_3-1-0_111081_2019-07-28_final
2019-07-29 10:32:53	ga_ls8c_ard_3-1-0_102080_2019-07-29_final
2019-07-29 10:33:17	ga_ls8c_ard_3-1-0_102081_2019-07-29_final
2019-08-28 09:06:31	ga_ls8c_ard_3-1-0_088080_2019-08-27_final
2019-08-28 09:06:55	ga_ls8c_ard_3-1-0_088081_2019-08-27_final
2019-08-28 10:45:24	ga_ls8c_ard_3-1-0_104080_2019-08-28_final
2019-08-28 10:45:48	ga_ls8c_ard_3-1-0_104081_2019-08-28_final
2019-08-29 09:49:47	ga_ls8c_ard_3-1-0_095080_2019-08-29_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-08-29 11:28:40	ga_ls8c_ard_3-1-0_111080_2019-08-29_final
2019-08-29 11:29:04	ga_ls8c_ard_3-1-0_111081_2019-08-29_final
2019-08-30 10:33:03	ga_ls8c_ard_3-1-0_102080_2019-08-30_final
2019-08-30 10:33:27	ga_ls8c_ard_3-1-0_102081_2019-08-30_final
2019-09-06 10:39:15	ga_ls8c_ard_3-1-0_103080_2019-09-06_final
2019-09-06 10:39:39	ga_ls8c_ard_3-1-0_103081_2019-09-06_final
2019-09-07 09:43:38	ga_ls8c_ard_3-1-0_094080_2019-09-07_final
2019-09-07 09:44:02	ga_ls8c_ard_3-1-0_094081_2019-09-07_final
2019-09-07 11:22:31	ga_ls8c_ard_3-1-0_110080_2019-09-07_final
2019-09-07 11:22:55	ga_ls8c_ard_3-1-0_110081_2019-09-07_final
2019-09-08 10:26:54	ga_ls8c_ard_3-1-0_101080_2019-09-08_final
2019-09-08 10:27:18	ga_ls8c_ard_3-1-0_101081_2019-09-08_final
2019-09-12 10:02:13	ga_ls8c_ard_3-1-0_097080_2019-09-12_final
2019-09-12 10:02:37	ga_ls8c_ard_3-1-0_097081_2019-09-12_final
2019-09-12 11:41:06	ga_ls8c_ard_3-1-0_113080_2019-09-12_final
2019-09-12 11:41:30	ga_ls8c_ard_3-1-0_113081_2019-09-12_final
2019-09-13 09:06:36	ga_ls8c_ard_3-1-0_088080_2019-09-12_final
2019-09-13 09:07:00	ga_ls8c_ard_3-1-0_088081_2019-09-12_final
2019-09-13 10:45:29	ga_ls8c_ard_3-1-0_104080_2019-09-13_final
2019-09-13 10:45:53	ga_ls8c_ard_3-1-0_104081_2019-09-13_final
2019-09-14 09:49:52	ga_ls8c_ard_3-1-0_095080_2019-09-14_final
2019-09-14 09:50:16	ga_ls8c_ard_3-1-0_095081_2019-09-14_final
2019-09-14 11:28:45	ga_ls8c_ard_3-1-0_111080_2019-09-14_final
2019-09-14 11:29:09	ga_ls8c_ard_3-1-0_111081_2019-09-14_final
2019-09-15 10:33:08	ga_ls8c_ard_3-1-0_102080_2019-09-15_final
2019-09-15 10:33:32	ga_ls8c_ard_3-1-0_102081_2019-09-15_final
2019-10-24 10:39:26	ga_ls8c_ard_3-1-0_103080_2019-10-24_final
2019-10-24 10:39:50	ga_ls8c_ard_3-1-0_103081_2019-10-24_final
2019-10-25 09:43:49	ga_ls8c_ard_3-1-0_094080_2019-10-25_final
2019-10-25 09:44:13	ga_ls8c_ard_3-1-0_094081_2019-10-25_final
2019-10-25 11:22:42	ga_ls8c_ard_3-1-0_110080_2019-10-25_final
2019-10-25 11:23:06	ga_ls8c_ard_3-1-0_110081_2019-10-25_final
2019-10-26 10:27:04	ga_ls8c_ard_3-1-0_101080_2019-10-26_final
2019-10-26 10:27:28	ga_ls8c_ard_3-1-0_101081_2019-10-26_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-03-22 11:47:17	ga_ls8c_ard_3-2-1_114081_2023-03-22_final
2023-03-23 09:12:22	ga_ls8c_ard_3-2-1_089080_2023-03-22_final
2023-03-23 09:12:45	ga_ls8c_ard_3-2-1_089081_2023-03-22_final
2023-03-23 10:51:14	ga_ls8c_ard_3-2-1_105080_2023-03-23_final
2023-03-23 10:51:38	ga_ls8c_ard_3-2-1_105081_2023-03-23_final
2023-03-24 09:55:37	ga_ls8c_ard_3-2-1_096080_2023-03-24_final
2023-03-24 09:56:00	ga_ls8c_ard_3-2-1_096081_2023-03-24_final
2023-04-11 11:21:52	ga_ls8c_ard_3-2-1_110080_2023-04-11_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-12 10:26:14	ga_ls8c_ard_3-2-1_101080_2023-04-12_final
2023-04-12 10:26:38	ga_ls8c_ard_3-2-1_101081_2023-04-12_final
2023-04-13 09:30:37	ga_ls8c_ard_3-2-1_092080_2023-04-13_final
2023-04-13 09:31:01	ga_ls8c_ard_3-2-1_092081_2023-04-13_final
2023-04-13 11:09:30	ga_ls8c_ard_3-2-1_108080_2023-04-13_final
2023-04-13 11:09:54	ga_ls8c_ard_3-2-1_108081_2023-04-13_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-14 10:14:16	ga_ls8c_ard_3-2-1_099081_2023-04-14_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-15 09:18:15	ga_ls8c_ard_3-2-1_090080_2023-04-14_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