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
2023-07-12 10:06:14	ga_ls8c_ard_3-2-1_098076_2023-07-12_final
2023-07-13 10:47:07	ga_ls8c_ard_3-2-1_105070_2023-07-13_final
2023-07-14 09:55:53	ga_ls8c_ard_3-2-1_096081_2023-07-14_final
2023-07-17 10:23:11	ga_ls8c_ard_3-2-1_101072_2023-07-17_final
2023-07-19 10:11:37	ga_ls8c_ard_3-2-1_099074_2023-07-19_final
2023-07-21 10:00:04	ga_ls8c_ard_3-2-1_097076_2023-07-21_final
2023-07-21 10:02:03	ga_ls8c_ard_3-2-1_097081_2023-07-21_final
2023-07-22 10:42:56	ga_ls8c_ard_3-2-1_104075_2023-07-22_final
2023-07-22 10:44:32	ga_ls8c_ard_3-2-1_104079_2023-07-22_final
2023-07-22 10:45:20	ga_ls8c_ard_3-2-1_104081_2023-07-22_final
2023-07-23 11:26:13	ga_ls8c_ard_3-2-1_111075_2023-07-23_final
2023-07-23 11:29:01	ga_ls8c_ard_3-2-1_111082_2023-07-23_final
2023-07-29 10:47:13	ga_ls8c_ard_3-2-1_105070_2023-07-29_final
2023-07-30 09:52:48	ga_ls8c_ard_3-2-1_096073_2023-07-30_final
2023-07-30 09:56:48	ga_ls8c_ard_3-2-1_096083_2023-07-30_final
2023-07-31 10:37:16	ga_ls8c_ard_3-2-1_103076_2023-07-31_final
2023-07-31 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-07-31_final
2023-08-04 11:50:40	ga_ls8c_ard_3-2-1_115074_2023-08-04_final
2023-08-05 09:18:33	ga_ls8c_ard_3-2-1_090080_2023-08-04_final
2023-08-06 10:00:37	ga_ls8c_ard_3-2-1_097077_2023-08-06_final
2023-08-09 10:29:31	ga_ls8c_ard_3-2-1_102072_2023-08-09_final
2023-08-09 10:30:43	ga_ls8c_ard_3-2-1_102075_2023-08-09_final
2023-08-10 09:35:30	ga_ls8c_ard_3-2-1_093076_2023-08-10_final
2023-08-11 10:19:57	ga_ls8c_ard_3-2-1_100079_2023-08-11_final
2023-08-13 10:05:38	ga_ls8c_ard_3-2-1_098074_2023-08-13_final
2023-08-13 10:06:02	ga_ls8c_ard_3-2-1_098075_2023-08-13_final
2023-08-14 10:47:42	ga_ls8c_ard_3-2-1_105071_2023-08-14_final
2023-08-15 09:52:54	ga_ls8c_ard_3-2-1_096073_2023-08-15_final
2023-08-15 11:34:58	ga_ls8c_ard_3-2-1_112081_2023-08-15_final
2023-08-20 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-08-20_final
2023-08-21 09:19:28	ga_ls8c_ard_3-2-1_090082_2023-08-20_final
2023-08-24 11:26:29	ga_ls8c_ard_3-2-1_111075_2023-08-24_final
2023-08-25 10:31:39	ga_ls8c_ard_3-2-1_102077_2023-08-25_final
2023-08-26 11:12:56	ga_ls8c_ard_3-2-1_109072_2023-08-26_final
2023-08-27 11:58:35	ga_ls8c_ard_3-2-1_116078_2023-08-27_final
2023-08-28 11:03:46	ga_ls8c_ard_3-2-1_107080_2023-08-28_final
2023-08-29 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-08-29_final
2023-08-29 10:06:32	ga_ls8c_ard_3-2-1_098076_2023-08-29_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-09-01 10:38:14	ga_ls8c_ard_3-2-1_103078_2023-09-01_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-08 10:43:12	ga_ls8c_ard_3-2-1_104075_2023-09-08_final
2023-09-10 10:30:52	ga_ls8c_ard_3-2-1_102075_2023-09-10_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-13 11:04:12	ga_ls8c_ard_3-2-1_107081_2023-09-13_final
2023-09-16 09:52:39	ga_ls8c_ard_3-2-1_096072_2023-09-16_final
2023-09-16 11:35:07	ga_ls8c_ard_3-2-1_112081_2023-09-16_final
2023-09-19 10:24:45	ga_ls8c_ard_3-2-1_101075_2023-09-19_final
2023-09-20 09:31:55	ga_ls8c_ard_3-2-1_092082_2023-09-20_final
2023-09-22 09:18:46	ga_ls8c_ard_3-2-1_090080_2023-09-21_final
2023-09-25 09:51:17	ga_ls8c_ard_3-2-1_095084_2023-09-25_final
2023-09-25 11:28:58	ga_ls8c_ard_3-2-1_111081_2023-09-25_final
2023-09-25 11:29:22	ga_ls8c_ard_3-2-1_111082_2023-09-25_final
2023-09-26 10:30:58	ga_ls8c_ard_3-2-1_102075_2023-09-26_final
2023-09-28 10:21:25	ga_ls8c_ard_3-2-1_100082_2023-09-28_final
2023-09-30 10:05:52	ga_ls8c_ard_3-2-1_098074_2023-09-30_final
2023-10-01 10:50:20	ga_ls8c_ard_3-2-1_105077_2023-10-01_final
2023-10-03 10:35:34	ga_ls8c_ard_3-2-1_103071_2023-10-03_final
2023-10-03 10:36:22	ga_ls8c_ard_3-2-1_103073_2023-10-03_final
2023-10-05 10:24:24	ga_ls8c_ard_3-2-1_101074_2023-10-05_final
2023-10-06 09:29:34	ga_ls8c_ard_3-2-1_092076_2023-10-05_final
2023-10-06 09:29:58	ga_ls8c_ard_3-2-1_092077_2023-10-05_final
2023-10-06 09:35:09	ga_ls8c_ard_3-2-1_092090_2023-10-06_final
2023-10-06 11:10:27	ga_ls8c_ard_3-2-1_108081_2023-10-06_final
2023-10-07 10:12:03	ga_ls8c_ard_3-2-1_099074_2023-10-07_final
2023-10-08 09:18:50	ga_ls8c_ard_3-2-1_090080_2023-10-07_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-09 11:40:35	ga_ls8c_ard_3-2-1_113079_2023-10-09_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-10 10:45:22	ga_ls8c_ard_3-2-1_104080_2023-10-10_final
2023-10-11 11:25:03	ga_ls8c_ard_3-2-1_111071_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:32:13	ga_ls8c_ard_3-2-1_102078_2023-10-12_final
2023-10-13 11:16:41	ga_ls8c_ard_3-2-1_109081_2023-10-13_final
2023-10-13 11:17:29	ga_ls8c_ard_3-2-1_109083_2023-10-13_final
2023-10-15 09:24:15	ga_ls8c_ard_3-2-1_091078_2023-10-14_final
2023-10-19 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-10-19_final
2023-10-20 11:23:38	ga_ls8c_ard_3-2-1_110083_2023-10-20_final
2023-10-21 10:24:26	ga_ls8c_ard_3-2-1_101074_2023-10-21_final
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-22 11:11:42	ga_ls8c_ard_3-2-1_108084_2023-10-22_final
2023-10-25 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-10-25_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-28 10:32:16	ga_ls8c_ard_3-2-1_102078_2023-10-28_final
2023-10-30 10:18:43	ga_ls8c_ard_3-2-1_100075_2023-10-30_final
2023-10-30 10:20:19	ga_ls8c_ard_3-2-1_100079_2023-10-30_final
2023-11-03 09:57:11	ga_ls8c_ard_3-2-1_096083_2023-11-03_final
2023-11-03 11:33:16	ga_ls8c_ard_3-2-1_112076_2023-11-03_final
2023-11-04 10:38:50	ga_ls8c_ard_3-2-1_103079_2023-11-04_final
2023-11-05 09:41:37	ga_ls8c_ard_3-2-1_094075_2023-11-05_final
2023-11-07 09:30:02	ga_ls8c_ard_3-2-1_092077_2023-11-07_final
2023-11-09 09:20:01	ga_ls8c_ard_3-2-1_090083_2023-11-08_final
2023-11-10 10:02:28	ga_ls8c_ard_3-2-1_097081_2023-11-10_final
2023-11-12 11:27:26	ga_ls8c_ard_3-2-1_111077_2023-11-12_final
2023-11-14 09:36:13	ga_ls8c_ard_3-2-1_093077_2023-11-14_final
2023-11-16 11:01:58	ga_ls8c_ard_3-2-1_107075_2023-11-16_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_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