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
2017-07-17 09:29:18	ga_ls8c_ard_3-0-0_092076_2017-07-16_final
2017-07-17 09:29:42	ga_ls8c_ard_3-0-0_092077_2017-07-16_final
2017-07-17 11:08:11	ga_ls8c_ard_3-0-0_108076_2017-07-17_final
2017-07-17 11:08:35	ga_ls8c_ard_3-0-0_108077_2017-07-17_final
2017-07-18 10:12:34	ga_ls8c_ard_3-0-0_099076_2017-07-18_final
2017-07-18 10:12:58	ga_ls8c_ard_3-0-0_099077_2017-07-18_final
2017-07-18 11:51:27	ga_ls8c_ard_3-0-0_115076_2017-07-18_final
2017-07-18 11:51:51	ga_ls8c_ard_3-0-0_115077_2017-07-18_final
2017-07-19 09:16:57	ga_ls8c_ard_3-0-0_090076_2017-07-18_final
2017-07-19 09:17:21	ga_ls8c_ard_3-0-0_090077_2017-07-18_final
2017-07-19 10:55:50	ga_ls8c_ard_3-0-0_106076_2017-07-19_final
2017-07-19 10:56:14	ga_ls8c_ard_3-0-0_106077_2017-07-19_final
2017-07-27 10:06:28	ga_ls8c_ard_3-0-0_098076_2017-07-27_final
2017-07-27 10:06:52	ga_ls8c_ard_3-1-0_098077_2017-07-27_final
2017-07-27 11:45:21	ga_ls8c_ard_3-0-0_114076_2017-07-27_final
2017-07-27 11:45:45	ga_ls8c_ard_3-0-0_114077_2017-07-27_final
2017-07-28 09:10:51	ga_ls8c_ard_3-0-0_089076_2017-07-27_final
2017-07-28 09:11:15	ga_ls8c_ard_3-0-0_089077_2017-07-27_final
2017-07-28 10:49:44	ga_ls8c_ard_3-0-0_105076_2017-07-28_final
2017-07-28 10:50:08	ga_ls8c_ard_3-0-0_105077_2017-07-28_final
2017-07-29 09:54:07	ga_ls8c_ard_3-0-0_096076_2017-07-29_final
2017-07-29 09:54:31	ga_ls8c_ard_3-0-0_096077_2017-07-29_final
2017-07-29 11:33:00	ga_ls8c_ard_3-0-0_112076_2017-07-29_final
2017-07-29 11:33:24	ga_ls8c_ard_3-0-0_112077_2017-07-29_final
2021-10-10 11:45:50	ga_ls8c_ard_3-2-0_114076_2021-10-10_final
2021-10-10 11:46:14	ga_ls8c_ard_3-2-0_114077_2021-10-10_final
2021-10-11 09:11:20	ga_ls8c_ard_3-2-0_089076_2021-10-10_final
2021-10-11 09:11:44	ga_ls8c_ard_3-2-0_089077_2021-10-10_final
2021-10-11 10:50:13	ga_ls8c_ard_3-2-0_105076_2021-10-11_final
2021-10-11 10:50:37	ga_ls8c_ard_3-2-0_105077_2021-10-11_final
2021-10-14 09:42:14	ga_ls8c_ard_3-2-0_094076_2021-10-14_final
2021-10-14 09:42:38	ga_ls8c_ard_3-2-0_094077_2021-10-14_final
2021-10-14 11:21:07	ga_ls8c_ard_3-2-0_110076_2021-10-14_final
2021-10-14 11:21:31	ga_ls8c_ard_3-2-0_110077_2021-10-14_final
2021-10-15 10:25:30	ga_ls8c_ard_3-2-0_101076_2021-10-15_final
2021-10-15 10:25:54	ga_ls8c_ard_3-2-0_101077_2021-10-15_final
2023-07-13 09:10:37	ga_ls8c_ard_3-2-1_089076_2023-07-12_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-13 10:49:30	ga_ls8c_ard_3-2-1_105076_2023-07-13_final
2023-07-13 10:49:54	ga_ls8c_ard_3-2-1_105077_2023-07-13_final
2023-07-14 09:53:53	ga_ls8c_ard_3-2-1_096076_2023-07-14_final
2023-07-14 09:54:17	ga_ls8c_ard_3-2-1_096077_2023-07-14_final
2023-07-14 11:32:46	ga_ls8c_ard_3-2-1_112076_2023-07-14_final
2023-07-14 11:33:10	ga_ls8c_ard_3-2-1_112077_2023-07-14_final
2023-07-15 10:37:09	ga_ls8c_ard_3-2-1_103076_2023-07-15_final
2023-07-15 10:37:33	ga_ls8c_ard_3-2-1_103077_2023-07-15_final
2023-07-21 10:00:04	ga_ls8c_ard_3-2-1_097076_2023-07-21_final
2023-07-21 10:00:27	ga_ls8c_ard_3-2-1_097077_2023-07-21_final
2023-07-21 11:38:57	ga_ls8c_ard_3-2-1_113076_2023-07-21_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-22 10:43:20	ga_ls8c_ard_3-2-1_104076_2023-07-22_final
2023-07-22 10:43:44	ga_ls8c_ard_3-2-1_104077_2023-07-22_final
2023-07-23 09:47:44	ga_ls8c_ard_3-2-1_095076_2023-07-23_final
2023-07-23 09:48:08	ga_ls8c_ard_3-2-1_095077_2023-07-23_final
2023-07-23 11:27:01	ga_ls8c_ard_3-2-1_111077_2023-07-23_final
2023-07-24 10:31:01	ga_ls8c_ard_3-2-1_102076_2023-07-24_final
2023-07-24 10:31:25	ga_ls8c_ard_3-2-1_102077_2023-07-24_final
2023-07-25 09:35:24	ga_ls8c_ard_3-2-1_093076_2023-07-25_final
2023-07-25 09:35:48	ga_ls8c_ard_3-2-1_093077_2023-07-25_final
2023-07-25 11:14:17	ga_ls8c_ard_3-2-1_109076_2023-07-25_final
2023-07-25 11:14:41	ga_ls8c_ard_3-2-1_109077_2023-07-25_final
2023-07-26 10:18:41	ga_ls8c_ard_3-2-1_100076_2023-07-26_final
2023-07-26 10:19:05	ga_ls8c_ard_3-2-1_100077_2023-07-26_final
2023-07-26 11:57:34	ga_ls8c_ard_3-2-1_116076_2023-07-26_final
2023-07-26 11:57:58	ga_ls8c_ard_3-2-1_116077_2023-07-26_final
2023-09-10 10:31:16	ga_ls8c_ard_3-2-1_102076_2023-09-10_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-11 09:35:39	ga_ls8c_ard_3-2-1_093076_2023-09-11_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 11:14:33	ga_ls8c_ard_3-2-1_109076_2023-09-11_final
2023-09-11 11:14:56	ga_ls8c_ard_3-2-1_109077_2023-09-11_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-12 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-09-12_final
2023-09-12 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-09-12_final
2023-09-12 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-09-12_final
2023-09-13 09:23:19	ga_ls8c_ard_3-2-1_091076_2023-09-12_final
2023-09-13 09:23:43	ga_ls8c_ard_3-2-1_091077_2023-09-12_final
2023-09-13 11:02:12	ga_ls8c_ard_3-2-1_107076_2023-09-13_final
2023-09-13 11:02:36	ga_ls8c_ard_3-2-1_107077_2023-09-13_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-12 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-10-12_final
2023-10-13 09:35:48	ga_ls8c_ard_3-2-1_093076_2023-10-13_final
2023-10-13 09:36:12	ga_ls8c_ard_3-2-1_093077_2023-10-13_final
2023-10-13 11:14:41	ga_ls8c_ard_3-2-1_109076_2023-10-13_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_final
2023-10-14 10:19:04	ga_ls8c_ard_3-2-1_100076_2023-10-14_nrt
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_final
2023-10-14 10:19:28	ga_ls8c_ard_3-2-1_100077_2023-10-14_nrt
2023-10-14 11:57:57	ga_ls8c_ard_3-2-1_116076_2023-10-14_final
2023-10-14 11:57:57	ga_ls8c_ard_3-2-1_116076_2023-10-14_nrt
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_final
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_nrt
2023-10-15 09:23:27	ga_ls8c_ard_3-2-1_091076_2023-10-14_final
2023-10-15 09:23:27	ga_ls8c_ard_3-2-1_091076_2023-10-14_nrt
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_final
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_nrt
2023-10-15 11:02:20	ga_ls8c_ard_3-2-1_107076_2023-10-15_final
2023-10-15 11:02:20	ga_ls8c_ard_3-2-1_107076_2023-10-15_nrt
2023-10-15 11:02:44	ga_ls8c_ard_3-2-1_107077_2023-10-15_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