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
2022-01-14 10:05:34	ga_ls8c_ard_3-2-1_098073_2022-01-14_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-11 09:50:31	ga_ls8c_ard_3-2-1_095081_2022-12-11_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2023-01-02 10:51:25	ga_ls8c_ard_3-2-1_105079_2023-01-02_final
2023-01-03 09:56:35	ga_ls8c_ard_3-2-1_096081_2023-01-03_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-10 09:58:45	ga_ls8c_ard_3-2-1_097071_2023-01-10_final
2023-01-10 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-10_final
2023-01-12 09:49:57	ga_ls8c_ard_3-2-1_095080_2023-01-12_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-21 09:42:32	ga_ls8c_ard_3-2-1_094077_2023-01-21_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-01-26 10:01:08	ga_ls8c_ard_3-2-1_097077_2023-01-26_final
2023-01-30 11:16:54	ga_ls8c_ard_3-2-1_109081_2023-01-30_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-07 10:26:38	ga_ls8c_ard_3-2-1_101079_2023-02-07_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-23 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-02-23_final
2023-02-24 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-02-24_final
2023-02-24 09:32:44	ga_ls8c_ard_3-2-1_092084_2023-02-24_final
2023-02-26 10:56:26	ga_ls8c_ard_3-2-1_106077_2023-02-26_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-03 09:36:29	ga_ls8c_ard_3-2-1_093078_2023-03-03_final
2023-03-04 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-03-04_final
2023-03-05 09:24:30	ga_ls8c_ard_3-2-1_091079_2023-03-04_final
2023-03-05 09:25:42	ga_ls8c_ard_3-2-1_091082_2023-03-04_final
2023-03-08 11:34:38	ga_ls8c_ard_3-2-1_112080_2023-03-08_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_final
2023-03-10 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-03-10_final
2023-03-12 11:08:19	ga_ls8c_ard_3-2-1_108076_2023-03-12_final
2023-03-14 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-03-14_final
2023-03-15 11:38:48	ga_ls8c_ard_3-2-1_113075_2023-03-15_final
2023-03-16 10:44:22	ga_ls8c_ard_3-2-1_104078_2023-03-16_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_2023-03-16_final
2023-03-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2023-03-17_final
2023-03-17 11:26:49	ga_ls8c_ard_3-2-1_111076_2023-03-17_final
2023-03-18 10:30:23	ga_ls8c_ard_3-2-1_102074_2023-03-18_final
2023-03-19 09:36:45	ga_ls8c_ard_3-2-1_093079_2023-03-19_final
2023-03-20 10:17:36	ga_ls8c_ard_3-2-1_100073_2023-03-20_final
2023-03-22 11:47:17	ga_ls8c_ard_3-2-1_114081_2023-03-22_final
2023-03-28 11:06:34	ga_ls8c_ard_3-2-1_108072_2023-03-28_final
2023-03-29 10:11:44	ga_ls8c_ard_3-2-1_099074_2023-03-29_final
2023-03-31 10:00:33	ga_ls8c_ard_3-2-1_097077_2023-03-31_final
2023-04-02 11:28:14	ga_ls8c_ard_3-2-1_111080_2023-04-02_final
2023-04-05 10:17:24	ga_ls8c_ard_3-2-1_100073_2023-04-05_final
2023-04-05 11:57:53	ga_ls8c_ard_3-2-1_116077_2023-04-05_final
2023-04-05 11:58:17	ga_ls8c_ard_3-2-1_116078_2023-04-05_final
2023-04-08 10:51:02	ga_ls8c_ard_3-2-1_105080_2023-04-08_final
2023-04-10 10:39:25	ga_ls8c_ard_3-2-1_103082_2023-04-10_final
2023-04-13 11:10:18	ga_ls8c_ard_3-2-1_108082_2023-04-13_final
2023-04-18 11:26:01	ga_ls8c_ard_3-2-1_111075_2023-04-18_final
2023-04-19 10:29:11	ga_ls8c_ard_3-2-1_102072_2023-04-19_final
2023-04-20 09:35:33	ga_ls8c_ard_3-2-1_093077_2023-04-20_final
2023-04-24 10:49:43	ga_ls8c_ard_3-2-1_105077_2023-04-24_final
2023-04-27 09:44:07	ga_ls8c_ard_3-2-1_094083_2023-04-27_final
2023-04-29 11:09:26	ga_ls8c_ard_3-2-1_108080_2023-04-29_final
2023-04-30 10:11:48	ga_ls8c_ard_3-2-1_099075_2023-04-30_final
2023-05-01 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-04-30_final
2023-05-01 10:56:39	ga_ls8c_ard_3-2-1_106079_2023-05-01_final
2023-05-03 10:40:17	ga_ls8c_ard_3-2-1_104069_2023-05-03_final
2023-05-03 10:44:16	ga_ls8c_ard_3-2-1_104079_2023-05-03_final
2023-05-06 09:38:15	ga_ls8c_ard_3-2-1_093084_2023-05-06_final
2023-05-06 11:11:08	ga_ls8c_ard_3-2-1_109069_2023-05-06_final
2023-05-06 11:15:32	ga_ls8c_ard_3-2-1_109080_2023-05-06_final
2023-05-08 11:03:56	ga_ls8c_ard_3-2-1_107082_2023-05-08_final
2023-05-10 10:50:44	ga_ls8c_ard_3-2-1_105080_2023-05-10_final
2023-05-11 09:52:18	ga_ls8c_ard_3-2-1_096073_2023-05-11_final
2023-05-11 09:52:42	ga_ls8c_ard_3-2-1_096074_2023-05-11_final
2023-05-11 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-11_final
2023-05-16 10:10:47	ga_ls8c_ard_3-2-1_099073_2023-05-16_final
2023-05-16 10:11:35	ga_ls8c_ard_3-2-1_099075_2023-05-16_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_final
2023-05-18 10:00:01	ga_ls8c_ard_3-2-1_097077_2023-05-18_final
2023-05-19 10:40:54	ga_ls8c_ard_3-2-1_104071_2023-05-19_final
2023-05-20 09:49:16	ga_ls8c_ard_3-2-1_095081_2023-05-20_final
2023-05-20 11:27:45	ga_ls8c_ard_3-2-1_111080_2023-05-20_final
2023-05-20 11:28:33	ga_ls8c_ard_3-2-1_111082_2023-05-20_final
2023-05-21 10:30:33	ga_ls8c_ard_3-2-1_102076_2023-05-21_final
2023-05-21 10:30:57	ga_ls8c_ard_3-2-1_102077_2023-05-21_final
2023-05-22 09:34:56	ga_ls8c_ard_3-2-1_093076_2023-05-22_final
2023-05-22 09:38:07	ga_ls8c_ard_3-2-1_093084_2023-05-22_final
2023-05-26 10:49:31	ga_ls8c_ard_3-2-1_105077_2023-05-26_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